Professor Kai-Mei Fu elected American Physical Society Fellow
UW ECE and Physics Professor Kai-Mei Fu has been elected an APS Fellow for research that has applications in quantum computing, quantum networks, and sensing technologies.
https://www.ece.uw.edu/spotlight/professor-kai-mei-fu-elected-american-physical-society-fellow/
https://www.washington.edu/news/2024/09/23/how-the-remote-hub-lab-can-prepare-engineering-students-for-their-future-careers/
How the Remote Hub Lab is preparing engineering students for their future careers
The Remote Hub Lab, founded and led by UW ECE Associate Teaching Professor Rania Hussein, allows students to access physical engineering equipment from anywhere in the world.
https://www.ece.uw.edu/spotlight/2024-uw-ece-welcomes-six-new-faculty/
UW ECE welcomes six new faculty members
Beginning this fall and extending through autumn quarter 2025, UW ECE is welcoming six new faculty members who will bring a wide breadth of knowledge and technical expertise to the Department.
https://www.ece.uw.edu/spotlight/arpita-ghosh-dacy-mrs-universe/
Arpita Ghosh Dacy — tech leader, mentor, and Mrs. Universe America
After almost a decade developing products built on artificial intelligence, data science, and machine learning, UW ECE alumna Arpita Ghosh Dacy (BSEE '10) was introduced to beauty pageants, which led her down an unexpected road that culminated in being crowned Mrs. Universe America 2023–24.
https://www.ece.uw.edu/spotlight/uwece-gpu-certificate-2024/
UW ECE Certificate Program in GPU-Accelerated Computing & Visualization to be offered this fall
This Certificate Program is designed for working professionals and graduate students. The three-quarter, online course of study takes students on a deep dive into the graphics processing unit, or GPU, a critical piece of modern computer architecture.
https://www.ece.uw.edu/spotlight/new-textbook-uw-ece-power-systems-2024/
New textbook provides a fresh perspective on modern power systems
This fall, a new textbook by UW ECE Professor Daniel Kirschen will be introduced into the Department's power and energy systems undergraduate curriculum.
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[_finalHTML:protected] => https://www.ece.uw.edu/spotlight/professor-kai-mei-fu-elected-american-physical-society-fellow/Professor Kai-Mei Fu elected American Physical Society Fellow
UW ECE and Physics Professor Kai-Mei Fu has been elected an APS Fellow for research that has applications in quantum computing, quantum networks, and sensing technologies.
How the Remote Hub Lab is preparing engineering students for their future careers
The Remote Hub Lab, founded and led by UW ECE Associate Teaching Professor Rania Hussein, allows students to access physical engineering equipment from anywhere in the world.
UW ECE welcomes six new faculty members
Beginning this fall and extending through autumn quarter 2025, UW ECE is welcoming six new faculty members who will bring a wide breadth of knowledge and technical expertise to the Department.
Arpita Ghosh Dacy — tech leader, mentor, and Mrs. Universe America
After almost a decade developing products built on artificial intelligence, data science, and machine learning, UW ECE alumna Arpita Ghosh Dacy (BSEE '10) was introduced to beauty pageants, which led her down an unexpected road that culminated in being crowned Mrs. Universe America 2023–24.
UW ECE Certificate Program in GPU-Accelerated Computing & Visualization to be offered this fall
This Certificate Program is designed for working professionals and graduate students. The three-quarter, online course of study takes students on a deep dive into the graphics processing unit, or GPU, a critical piece of modern computer architecture.
New textbook provides a fresh perspective on modern power systems
This fall, a new textbook by UW ECE Professor Daniel Kirschen will be introduced into the Department's power and energy systems undergraduate curriculum.
UW ECE and Physics Professor Kai-Mei Fu has been elected an APS Fellow for research that has applications in quantum computing, quantum networks, and sensing technologies. Photo by Ryan Hoover / UW ECE[/caption]
Kai-Mei Fu, the Virginia and Prentice Bloedel Professor of Physics and Electrical and Computer Engineering at the University of Washington, has been elected an American Physical Society Fellow. Fu was recently elected to the APS Division of Quantum Information Fellowship for foundational contributions to fundamental and applied research on the optical and spin properties of quantum point defects in crystals. Fu was also recognized for their service and leadership in the quantum community.
Fu directs the Quantum Defect Laboratory at the UW, where their research focuses on identifying and controlling the quantum properties of point defects in crystals, which have a wide array of applications in quantum computing, quantum networks, and sensing technologies. Fu is also the director of the University’s NSF National Research Training program: Accelerating Quantum-Enabled Technologies and is co-chair of the University’s interdisciplinary QuantumX Steering Committee. They are the deputy director of the U.S. Department of Energy’s National Quantum Initiative Co-design Center for Quantum Advantage, and they hold a joint appointment with the Pacific Northwest National Laboratory.
Among other notable accomplishments, Fu has been instrumental in leading the establishment of the UW Graduate Certificate in Quantum Information Science and Engineering at the University. In addition to the APS Fellowship, Fu has received several other awards and honors for their work in research and education, including an NSF CAREER Award, a Cottrell Scholar Award and a UW College of Engineering Junior Faculty Award.
The APS recognizes its members for their outstanding efforts to advance physics and becoming an APS Fellow is considered to be a great honor. Each year, no more than one half of one percent of APS membership are elected as Fellows. The APS only elects members to Fellowship who have contributed to the advancement of physics by independent, original research or who have rendered other special service to the cause of the sciences.
More information about Professor Kai-Mei Fu can be found on their UW ECE bio page.
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[post_content] => By Wayne Gillam / UW ECE News
[caption id="attachment_35170" align="alignright" width="575"]
Incoming UW ECE faculty are (from left to right, clockwise): Ang Li, Yiyue Luo, Dinuka Sahabandu, Vasileios Charisopoulos, Banghua Zhu, Jing Yu. Photo collage by Isaiah Hoagland / UW ECE[/caption]
Beginning this fall and extending through autumn quarter 2025, UW ECE is welcoming six new faculty members who will bring a wide breadth of knowledge and technical expertise to the Department. Each of these outstanding new hires are making significant contributions to their respective fields, and they are pushing technology development forward in exciting, innovative ways. With these new additions, the Department will be adding faculty expertise in computer architecture, reconfigurable integrated systems, data science, and creative applications of artificial intelligence and machine learning to areas such as power and energy systems, cybersecurity, and intelligent textiles.
“I am excited to welcome these new faculty members to the Department,” said UW ECE Professor and Chair Eric Klavins. “Each is at the leading edge of their field and brings knowledge and unique skills that are sure to benefit our students, research efforts, and collaborations across the University.”
Ang Li
This month, Ang Li will become a tenure-track assistant professor in the Department. He is currently a UW ECE affiliate assistant professor and a visiting postdoctoral scholar for AMD, where he works with state-of-the-art microprocessors.
“I’m excited to join UW ECE and start my academic career,” Li said. “I’m looking forward to collaborating with the Department’s leading researchers across many disciplines and working with smart and hard-working students with diverse backgrounds.”
Li received his bachelor’s degree in electrical engineering from Tsinghua University and his master’s degree in electrical engineering from Princeton University, where he also received his doctoral degree in electrical and computer engineering. At the UW, Li will direct the PN Computer Engineering Lab, which will focus on innovating a variety of different devices ranging from computing systems to semiconductor circuits. The lab will also explore the interplay between classic and emerging computing technologies.
In his doctoral research, Li developed a silicon-proven, open-source field programmable gate array, or FPGA, research and prototyping framework called the Princeton Reconfigurable Gate Array, or PRGA. He also studied tightly integrated, manycore-eFPGA, system-on-chip, or SoC, architectures. He has been a leading member in two multi-university teams who successfully developed two silicon prototypes, including a 2.2 billion-transistor, Linux-capable, fully cache-coherent, manycore-accelerator-eFPGA SoC, which is one of the biggest academic tape-outs of its kind to date.
Yiyue Luo
Also this month, Yiyue Luo will become a tenure-track assistant professor in the Department. Luo is currently a UW ECE affiliate assistant professor and a research assistant in the Computational Design & Fabrication Group at the Massachusetts Institute of Technology, or MIT.
“I’m thrilled to be joining UW ECE! I look forward to joining this vibrant, multidisciplinary, and collaborative community,” Luo said. “The extensive resources in digital fabrication, world-class education and research programs, and the opportunity to work alongside incredible researchers with a wide range of expertise make the UW a perfect place for me!”
Luo received her bachelor’s degree in materials science and engineering from the University of Illinois Urbana-Champaign before going on to earn her master’s degree in electrical engineering from MIT, where she also received her doctoral degree in electrical and electronics engineering.
Her research interests are at the intersection of digital fabrication, human-computer/robot interaction, and applied artificial intelligence. She creates intelligent textiles that incorporate sensors and other technologies into knitted fabrics. Her projects include machine-knitted pneumatic actuators, digitally embroidered smart gloves, machine-knitted haptic textiles, and much more.
Luo’s research has been published in interdisciplinary journals, such as Nature Electronics and Nature Communications; presented at top human-computer interaction, robotics, and learning venues; featured in prominent media outlets; and shown in public museums and World Congress exhibitions. This year, she was listed as one of the Forbes 30 Under 30 in Science, North America.
Dinuka Sahabandu
Dinuka Sahabandu will become an assistant teaching professor in the Department in December 2024. Sahabandu is currently a postdoctoral researcher in the Network Security Lab, which is led by UW ECE Professor and former Chair Radha Poovendran. There, Sahabandu works on projects involving machine learning, artificial intelligence, and cybersecurity.
“I'm excited to join UW ECE and collaborate with its world-class faculty and students, which offers an unparalleled environment for learning and growth,” Sahabandu said. “The opportunity to integrate cutting-edge research from the UW and well-established top-tier industries in the Seattle area into my teaching is a thrilling start to my career as an educator. I'm also looking forward to being part of a diverse and inclusive UW ECE community that fosters innovation and collaboration from all perspectives.”
Sahabandu received his bachelor’s and master’s degrees in electrical and electronics engineering from Washington State University and his doctoral degree in electrical and computer engineering from UW ECE.
Sahabandu is an expert at developing scalable machine learning and reinforcement learning algorithms to produce tools and solutions that ensure the security of cyber and physical systems. His doctoral research has been transitioned to high-level stakeholders, such as the U.S. Naval Research Laboratory as well as commercialized by Argus AI under the sponsorship of the U.S. Army Research Laboratory.
Vasileios Charisopoulos
In September 2025, Vasileios Charisopoulos will become a tenure-track assistant professor in the Department. He is currently a UW ECE affiliate assistant professor and an AI & Science postdoctoral scholar at the University of Chicago Data Science Institute.
“I am very excited to join UW ECE!” Charisopoulos said. “I think the department is uniquely positioned to produce transformative research given its highly collaborative culture, its representation and leadership in several interdisciplinary research centers across UW, and its ties with industry within the greater Seattle area.”
Charisopoulos received his Diploma in electrical and computer engineering from the National Technical University of Athens. He went on to receive his doctoral degree from Cornell University in operations research and information engineering.
Charisopoulos’ research interests include developing numerical optimization methods for machine learning, signal processing, and scientific computing. His interests encompass the mathematics of data science, with an emphasis on the interplay of optimization, high-dimensional statistical estimation, and numerical linear algebra.
In 2023, Charisopoulos was recognized as a Rising Star in Computational and Data Sciences by the Oden Institute at the University of Texas, Austin. He also received the Cornelia Ye Outstanding Teaching Assistant Award from Cornell University in 2021. His other awards and honors include receiving an Andreas G. Leventis Scholarship in 2020, a Schloss-Dagstuhl Support Grant for Junior Researchers in 2018, and a Cornell University Fellowship in 2017.
Jing Yu
Also in September 2025, Jing Yu will become a tenure-track assistant professor in the Department. She is currently a UW ECE affiliate assistant professor and a postdoctoral scholar at the University of Michigan. In spring 2025, she will join the University of Illinois Urbana-Champaign as a Grainger College of Engineering Distinguished Postdoctoral Fellow.
“I am thrilled to be joining UW ECE and collaborating with its talented and diverse faculty and students!” Yu said. “The vibrant research community here offers incredible opportunities for interdisciplinary collaboration, making UW ECE an ideal place for cutting-edge research at the intersection of control theory, machine learning, optimization, and sustainable energy systems.”
Yu received her bachelor’s degree in mechanical engineering from the Georgia Institute of Technology. She went on to earn her doctoral degree in control and dynamical systems from the California Institute of Technology, also known as Caltech.
Yu’s research interests include the interplay between control theory and machine learning, with a focus on online decision-making and distributed algorithms for large-scale sustainable energy systems. She was named an Amazon AI4Science fellow in 2023. She was also the recipient of several awards, including the Best Paper Finalist award in the Association for Computing Machinery, or ACM, e-Energy Conference in 2022 and the Caltech Amori Doctoral Prize in 2024.
Banghua Zhu
Banghua Zhu will also become a tenure-track assistant professor in the Department in September 2025. Zhu is currently a UW ECE affiliate assistant professor, and he works at a startup he co-founded, Nexusflow, which leverages cutting-edge research to create generative AI agents for business enterprises.
“I’m excited to join UW ECE and contribute to its world-class research and educational programs,” Zhu said. “The Department’s strong foundation in machine learning, combined with Seattle’s vibrant tech industry, creates an ideal environment for advancing research in language model training, evaluation, and serving. I look forward to collaborating with talented colleagues and students to push the boundaries of AI and large language models, while leveraging the unique opportunities that the UW and the Seattle area offer in bridging academic research with real-world applications.”
Zhu received his bachelor’s degree in electrical and electronics engineering from Tsinghua University and his doctoral degree in electrical engineering and computer science from the University of California, Berkeley.
His research focuses on improving the efficiency and safety of foundation models, specifically large language models. He is dedicated to creating open-source datasets and tools for public access. His research interests include training and evaluation of language models, game theory, reinforcement learning, human-AI interactions, and machine learning systems. He is a recipient of the 2023 David Sakrison Memorial Prize for outstanding research at the UC Berkeley Department of Electrical Engineering and Computer Sciences.
UW ECE would like to thank the faculty search committee, which was chaired in 2023–24 by UW ECE and Allen School Professor Georg Seelig and in 2024–25 by UW ECE and Physics Professor Kai-Mei Fu. The Department appreciates the committee members’ careful reviews, engaged participation, and generous welcome toward the candidates.
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[post_content] => By Wayne Gillam / UW ECE News
[caption id="attachment_35061" align="alignright" width="550"]
After almost a decade in a successful career developing products built on artificial intelligence, data science, and machine learning, UW ECE alumna Arpita Ghosh Dacy (BSEE '10) was introduced by a friend to beauty pageants, which led her down an unexpected road that culminated in being crowned Mrs. Universe America 2023–24. Photo by Jasmeet K Photography[/caption]
UW ECE alumna Arpita Ghosh Dacy (BSEE ‘10) is a person who doesn’t limit herself. She is enthusiastic about trying new things and has learned first-hand the value of stepping outside her comfort zone. This was demonstrated early in her career, when she worked with cutting-edge technologies that were considered risky and unproven in the marketplace but later became widely adopted. Her openness to new experiences in both her business and personal life continues today.
Three years ago, after almost a decade in a successful career developing products built on artificial intelligence, data science, and machine learning, Dacy was introduced by a friend to beauty pageants, which led her down an unexpected road that culminated in being crowned Mrs. Universe America 2023–24. Now, in addition to taking on this new role while continuing to work in a leadership position at Amazon, Dacy gives back to a wide range of charitable organizations by volunteering her time as a workshop and program leader, mentor, and motivational speaker.
“When I first started to work in artificial intelligence 10 years ago, it was a very new field, and working primarily in machine learning and AI was thought by many to be a risk. But just look at how these areas are booming now! So, taking that chance, that calculated risk led by curiosity, paid off,” Dacy said. “I think it’s never too late to learn something new about yourself and explore new things. When I first entered beauty pageants, I stepped way outside of my comfort zone. But it was amazing. It broadened my point of view, and I grew as a person.”
Technical leader at Amazon
[caption id="attachment_35065" align="alignright" width="450"]
In the Alexa Kids Experience team at Amazon, Dacy leads development of a wide range of products from concept to delivery that are designed to help children play, learn, and grow. Shown above, Alexa Echo Dot devices that look and talk like owls and dragons. Photo courtesy of Amazon.[/caption]
At Amazon, Dacy is a senior technical program manager in the Alexa Kids Experience team. There, she leads development of a wide range of products from concept to delivery that are designed to help children play, learn, and grow. Most recently, her team has been launching pioneering Alexa features, such as the “Hey Disney!” voice assistant, kid-friendly character voices for Alexa, and Explore with Alexa — Amazon’s very first conversational feature for kids that leverages Alexa’s large language model technology to present fun facts and trivia questions.
Dacy said that products such as these are designed to inspire a child’s creativity, curiosity, and imagination. For example, Alexa applications, such as Amazon Math, are designed to help kids build basic math skills, interactive books encourage creative thinking and reading, and Morning Routines help children foster independence by building their own routine for starting the day.
“Alexa Kids aims to provide an engaging learning experience for kids,” Dacy said. “My daughter loves the kid-friendly Alexa features, and I love what a safe and engaging educational resource they have been for our family.”
As a technical program manager and a mother of a seven-year-old daughter who uses Alexa and Echo devices, Dacy said that safety was paramount. She also said that she enjoys the transparency Alexa Kids provides in monitoring her own child’s activity and is proud to help bring that vision of greater transparency to her everyday work.
Mrs. Universe America
[caption id="attachment_35068" align="alignright" width="360"]
On December 10, 2023, Dacy was crowned Mrs. Universe America 2023–24 at the 11th annual Global Women Festival hosted by AmPowering in Seattle, Washington. In October, she will compete for the Mrs. Universe 2024 worldwide title in Incheon, South Korea. Photo by Jasmeet K Photography.[/caption]
In fact, it was Dacy’s daughter, Aishani, who was instrumental in bringing her into beauty pageants. Dacy was first introduced to this world in 2021 by a friend who invited her to attend a pageant sponsored by AmPowering, a non-profit organization founded by Menka Soni, which is committed to empowering women and youth, enriching families, and transforming communities. At the event, Dacy noticed that there were opportunities for children to participate in fashion shows and pageants. After talking with Aishani and learning that she was excited about getting involved, Dacy took her to get a headshot done for a Macy’s Kids segment in the North America Fashion Week show. As they were leaving the photoshoot, a modeling coach noticed Dacy and insisted she have her photo taken as well. From there, Dacy was discovered by the modeling industry, and designers reached out, encouraging her to participate in modeling and beauty pageants. So, Dacy took the plunge and ended up achieving a whirlwind string of successes. On December 10, 2023, she won the national title and was crowned Mrs. Universe America 2023–24 at the 11th annual Global Women Festival hosted by AmPowering in Seattle, Washington. In October, Dacy will compete for the Mrs. Universe 2024 worldwide title in Incheon, South Korea.
The experience of participating in beauty pageants pushed Dacy far outside her comfort zone.
“I have no modeling or pageantry background. I come from engineering, a tech background,” Dacy said. “A good thing about AmPowering’s pageant process is that it has a lot of mentors and training. My coach, Shivani Singh (co-founder of Coachnista), taught me everything I know about pageant presentations. There’s so much that goes into this, and I’m still her student, prepping for Mrs. Universe worldwide.”
During her reign as Mrs. Universe America, Dacy discovered that success in this venue opened doors and created experiences that otherwise would not have been possible for her. Since earning her title, she’s been invited to more events to talk about her life in engineering and balancing roles as a tech leader, mother, and mentor. She also has been able to promote her Mrs. Universe America platform, which is focused on empowering women, and in particular, women in STEM fields.
A mentor who gives back to the community
In keeping with her Mrs. Universe America platform, Dacy is passionate about supporting women and providing them with the tools they need to succeed. In addition to AmPowering, she is involved in several other charitable organizations that help women, including Helen’s Place women’s shelter, the New Bethlehem Project for families, and API Chaya. In 2023, she spoke at the Grace Hopper Conference for Women in Technology and mentored many individuals involved with the organization. She also is a mentor and speaker for women at Amazon and provides learning and discussion sessions focused on achieving better work-life balance.
At the UW, Dacy has been involved with Women Engineers Rise, or WE Rise, in the UW College of Engineering since she was an undergraduate student. Today, she is a professional advisory board member in the organization, mentors students, and recently spoke at the WE Rise annual conference as well as the We Rise 2024 Graduation Celebration and Thank You Celebration Tea. She is also a professional alumni member in the UW chapter of the Sigma Lambda Gamma National Sorority, which she has been actively involved with since her undergraduate years. Other organizations Dacy was affiliated with while attending the UW include the Society of Women Engineers and the National Society of Collegiate Scholars.
“Being a woman of color and in the STEM field, sometimes imposter syndrome looms large. But when you get these opportunities to meet others who have crossed these barriers and are making it, that is huge.” — UW ECE alumna Arpita Ghosh Dacy (BSEE '10)
As an undergraduate student at UW ECE, Dacy performed electrical and biomedical engineering research, tutored pre-engineering students in math and science, and graduated on the Dean’s List. She said that Cathryne Jordan, from the CoE’s Office of Inclusive Excellence, was her academic adviser and an influential mentor during this time. Since then, Jordan has remained a mentor and friend to Dacy for over 18 years.
“Being a woman of color and in the STEM field, sometimes imposter syndrome looms large. But when you get these opportunities to meet others who have crossed these barriers and are making it, that is huge,” Dacy said. “I will forever be grateful to Cathryne for providing me with guidance and opportunities when I was an undergrad and then inviting me to come back and talk to students as an alumna and industry executive.”
Looking ahead, Dacy said she would like to continue the trajectory she is on, working with products built on AI and new technologies. She is aiming to develop and innovate products that can improve and enhance people’s lives and leverage AI’s capabilities for good. She is particularly interested in large language models and how that technology could be applied in the marketplace. She is also looking forward to representing America this fall at the Mrs. Universe 2024 worldwide pageant.
When asked what advice she might give to students in engineering and STEM, Dacy was forthright and emphasized the importance of courage.
“Do not be afraid, and don’t let imposter syndrome get in the way of your success. Try to find mentors and join groups and organizations that uplift you,” she said. “Step out of your comfort zone. Don’t be afraid to take a risk. Don't let negativity stop you. Stretch your potential.”
More information about Arpita Ghosh Dacy can be found on her personal website and at her LinkedIn profile.
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[post_content] => By Wayne Gillam / UW ECE News
[caption id="attachment_34944" align="alignright" width="550"]
UW ECE's Certificate Program in GPU-Accelerated Computing & Visualization is designed for working professionals and graduate students. This three-quarter, online program takes students on a deep dive into the graphics processing unit, or GPU, a critical piece of modern computer architecture.[/caption]
Starting autumn quarter 2024, UW ECE will again be providing the Certificate Program in GPU-Accelerated Computing & Visualization for working professionals and graduate students. This three-quarter, online program is affiliated with the Professional Master’s Program, and it takes students on a deep dive into the graphics processing unit, or GPU, which is a critical piece of modern computer architecture. Besides enabling the graphics seen on desktop computers, laptops, and mobile devices, GPUs also provide computing power for a wide range of other data-intensive applications, such as gaming, cloud computing, scientific computing, machine learning and artificial intelligence, robotics, and much more.
The Certificate Program is taught by UW ECE Affiliate Assistant Professor Colin Reinhardt, who is a UW alumnus (BSEE ‘05, BS Physics ‘05, Ph.D. ‘10) and an engineer in the U.S. Navy, where he leads a team of software engineers and scientists that specialize in GPU computing for physics-based modeling and simulation. Reinhardt is an expert on GPU application programming interfaces, or APIs, such as CUDA, OpenCL, Vulkan, and OpenGL. He also has expertise in a wide range of GPU applications, including scientific computing and visualization, physically based rendering, 3D-modeling and simulation, predictive rendering, machine/deep learning, and neural networks. Below are questions and answers with Reinhardt about GPUs and the Certificate Program that explain more details about this exciting course of study.
What is a graphics processing unit, or GPU?
[caption id="attachment_34951" align="alignright" width="450"]
UW ECE Affiliate Assistant Professor Colin Reinhardt[/caption]
A graphics processing unit, which is commonly called “GPU” for short, is a specialized microprocessor subsystem that most computers today have, whether it’s a desktop workstation, laptop, or a mobile smartphone. All these devices have GPUs inside of them, and they work alongside the computer's central processing unit, or CPU (which is the main “brain” of your computer). You can think of the GPU as the workhorse of your computer for many compute-intensive tasks.
Fundamentally, the GPU is about massively parallel multiprocessing capability. It allows you to do a lot of computation, faster. But there are challenges in how you write the code and how you structure your algorithms to use this power effectively. For example, there are certain conditions that must be met for an algorithm to be parallelizable. And then, if you want your algorithm to be parallelized, how do you do that efficiently for a given GPU architecture? That’s a major focus in this Program, particularly in the GPU computing course.
What sorts of things do GPUs make possible?
The original, driving purpose for GPUs was to accelerate the production of 3D graphics. They are optimized for this and are still used heavily for that purpose. Another place that GPUs are critical is in image processing. So, in scientific fields, for example, GPUs are used for doing physically based algorithms to process video. Anytime there are large numbers of pixels and large images being processed, such as for additional post-processing, special effects, or image analysis — GPUs are well suited for all those problems.
Biomedical applications are another big area. GPUs are used for biomedical image analysis, image fusion, and 3D-computed tomography. And as GPU capabilities progress, the ability to deliver solutions progresses as well. We’re now seeing real-time 3D visualization of fused biomedical images that include positron emission tomography, computed tomography, and magnetic resonance imagery. All these different modalities that are imaging into the human body and producing critical diagnostic and therapeutic imagery are fundamentally driven and accelerated by GPUs.
One of the biggest applications of GPUs today is for machine learning and artificial intelligence. Deep learning models, natural language processing models, and large language models, such as ChatGPT, DALL-E, and Microsoft CoPilot all critically depend on GPUs for training. GPUs also help engineers and scientists deal with massive amounts of data, known as “big data,” because GPUs enable us to compute faster. Furthermore, one step removed, they allow us to train these deep learning models and other machine learning tools at massive scale, which can then help to process more data even faster, and even in real time. So, overall, I think GPUs are a critical tool that are only going to continue to become more important and powerful as the technology continues to progress.
Could you tell me more about your background as it relates to GPUs and this Certificate Program?
I’m an alumnus of the Department. I received a double bachelor’s degree in physics and electrical engineering from the UW in 2005, and then I went on to earn my doctoral degree from UW ECE in 2010. As a graduate student, I did research in an area related to GPUs, free space optical communication, which is a very compute-intensive field.
After completing my doctoral degree, I went to work for the U.S. Navy, where I continued to work in free space optical communications and related areas involving LiDAR, laser systems, and a lot of computational and numerical modeling of the atmosphere. These are places where computational demands are extremely high. So, use of the GPU in my work became very important, and I started to explore using these tools for the work I did with the Navy. That led me to become familiar with GPU capabilities early on. I also had a desire to teach, give back, and support the UW. So, in 2017, I became an affiliate assistant professor in the Department. Today, in addition to my teaching duties at UW ECE, I still work as a Navy engineer, where I lead a distributed team of software engineers and scientists that do GPU computing and hardware-accelerated algorithm development.
Teaching in the Professional Master’s Program is very inspiring for me because of the quality of the students that I’ve had a chance to work with. I’ve been very impressed with the creativity, skill, and the diligence of the students that I’ve worked with over the years in this Program. I’ve seen a lot of impressive projects done by students in these classes that are applicable to many different fields ranging from mechanical engineering to biomedical and scientific applications.
There’s a huge industry demand for students who have this knowledge and can put it into practice. So, in my curriculum, I focus on the practical skills you will need to use these tools and frameworks, as opposed to just learning a bunch of theory, where there could be a gap between that theory and how you apply it to real world tasks. All the classes that I teach have a major project-based element to them, which gives students a chance to work through the whole design-development-testing life cycle in a practical way and apply the GPU theory and methods we’ve learned.
What will students learn in this Certificate Program?
The Certificate Program is all online and consists of three courses, one each quarter. Typically, we offer these in autumn, winter, and spring, consecutively. The first quarter course is titled “Applied High-Performance GPU Computing.” It is focused on the fundamentals of how GPUs work, GPU hardware architecture as well as software, algorithm analysis and requirements, and analytical methods to determine when an algorithm is parallelizable. I also teach techniques to map your algorithm to the GPU hardware. We do this using primarily CUDA, which is a Nvidia-specific GPU language.
The second quarter course is called “GPU-Accelerated Interactive Scientific Visualization Techniques.” This title emphasizes the fact that we make use of GPU capabilities to accelerate graphics visualization at interactive rates. The course starts off with the basics of 3D-computer graphics because you need to understand the structures and the methods for a traditional 3D-computer graphics pipeline. Then, we talk about how those different steps in the 3D-computer graphics pipeline map to the GPU hardware. We look at OpenGL and Vulkan, which are the two major open-source industry standard APIs for using the GPU to do 3D-computer graphics. The focus in this course is not just on game graphics, but on more general scientific visualization, in particular, biomedical image visualization. But this is also applicable to just about any kind of general engineering visualization, or even more generally, data visualization, which moves into this important new domain of visualizing and understanding deep learning and machine learning models. So, there’s some interesting methods that utilize 3D and multi-dimensional visualization techniques to look inside deep learning networks and try to understand what they’re doing. We will look at some of those methods as well as more traditional, scientific visualization with fluid dynamics and computational electromagnetics.
The third quarter is what I call “Advanced GPU Computing and Visualization.” In this course, we bring together both scientific visualization and GPU computing. This is the culmination of the curriculum, and it integrates what you’ve learned in the first two quarters. We discuss how to develop a system that might be doing both visualization and heavy computing simultaneously. Most production-scale systems need to do this kind of thing. But there are additional challenges, such as tying together your algorithms between, say, Vulkan and CUDA or Vulkan and OpenCL. Furthermore, we cover some advanced techniques leveraging new, specialized GPU hardware features. For instance, we look at programming tensor cores, which offer even more speedup for particular computation types, and we’ll also look at the programming of the new Nvidia ray-tracing cores. This is hardware-accelerated ray tracing inside the latest Nvidia RTX GPUs. This is an exciting new area that’s just starting to be leveraged.
I also teach what I call “black art techniques.” These are programming skills that are generally not taught in schools or in theoretical textbooks. They are not well documented. Manufacturers are extremely careful with their hardware architecture information. They don’t publish it. They protect it and don’t disclose it. So, it’s difficult to learn. This is something that I wrestle with as an engineer myself: How do you know what’s happening in this black box that your code is running on? And so, there are reverse engineering and micro-benchmarking techniques that can be used to tease out particulars that could be critical in optimizing your code. We get into some of those things as well as how you can infer or learn particulars that could be very useful in writing highly performant code on the device when the vendors are not going to tell you that information.
Who is a good fit for this Program?
This Program is a good fit for any student who is interested in increasing their marketability in machine learning, 3D graphics, image processing, or computer vision. All these areas are well suited to having a strong foundation in low-level GPUs and scientific visualization. This Program is also for professionals who are wrestling with compute-intensive problems, where either their current code or systems are not fast enough (maybe they’re not processing as much data as they want to or need to, maybe their accuracy is limited). All these areas can be enhanced and accelerated by using GPUs. So, anybody who is a professional wrestling with those kinds of problems and wants to learn techniques to improve their system is another good candidate.
How could skills gained in this Program benefit an individual’s career?
I think that the skills learned in this program can benefit an individual’s career by providing them with a low-level understanding of GPU architecture as well as how to write tuned code for GPUs and think in parallel software development framework, which is not something that is traditionally taught in software engineering. All these things will help an individual become a valuable contributor to software or system development teams or potentially continue their education to do further research in the field.
What sorts of tools and technologies will students have access to?
We use a lot of tools and technologies in the Program. First, we use Amazon Web Services, or AWS, as a framework for the whole curriculum development. We also use it to provide GPUs that the students will use in doing their exercises and doing their programming. So, you don’t need to have a device with an Nvidia GPU to do this course. You will get access to a real GPU on the AWS cloud, and students have dedicated use of Nvidia GPU time on their cloud instances. So, that’s nice. And because it’s through AWS, you can log in remotely. You could do this from a variety of places and access the system from many types of client devices.
Then, for the actual curriculum content, students will obviously be studying GPU architecture. In particular, we will be looking at the Nvidia GPUs, but I will also talk about the other key players in the GPU market space, which are AMD and Intel. We’ll look at their GPU architectures and the similarities and differences between what they are doing compared to Nvidia.
We will look primarily at CUDA, the latest generation of the CUDA toolbox, and we’ll be using that to program the Nvidia GPUs. We’ll also talk about OpenCL, which is an open industry Khronos standard analogous to CUDA but device agnostic. So, it’s not tied to any one vendor, although I will say Intel and AMD are strong proponents of OpenCL.
Then, when it comes to scientific visualization, we’ll be focusing on two other Khronos standards, which are OpenGL, which was the traditional, dominant API for 3D-graphics programming, but in the last few years has been replaced and superseded by Vulkan, which is the new, modern GPU-centric graphics API. So, we will be using Vulkan.
And then we’ll be using several other Nvidia tools that come along with the CUDA toolkit to do analysis and profiling. We’ll learn the CUDA compiler tool, some of the CUDA extensions, and some of the other CUDA libraries that are included that have pre-written, GPU capabilities. There are also other profilers and analysis tools that we’ll be using.
Is there anything else students might want to know?
They might be curious about prerequisites. The official set of required and recommended prerequisites for the track is provided on the website. However, I just want to comment that there is a margin of flexibility, where, if you are coming in slightly underprepared, it is possible to compensate by doing a bit of extra work alongside the regular curriculum to supplement and enrich your understanding of the background knowledge areas. But it does take a serious commitment to doing the extra work and not falling behind in your assignments!
For example, having an intermediate to advanced skill level in C and C++ programming is strongly recommended. It is highly beneficial and will make your life easier if you have that level of experience, but it is not necessarily a showstopper. I have had students who didn’t know C and C++ very well coming in. They had a little bit more of a learning curve to surmount, but they were able to do it. I certainly will do what I can to assist. So, if you’re motivated and willing to put in the extra work, you can still complete the Program.
The same thing applies for the stated recommended prerequisite about having computer architecture background experience. We do get into topics such as microprocessor architecture, memory hierarchies, and cache architectures, which are important on these devices to make them run most efficiently. But again, it’s certainly something that a student could pick up on their own while they do the coursework. So, in the spirit of parallel programming, if you’re willing to learn and work at the same time, you can do it. But it will require more biological neural flops! Sorry, I had to squeeze in a computer/AI nerd joke!
For more information, visit the UW ECE Certificate Program in GPU-Accelerated Computing & Visualization webpage and the UW ECE Professional Master’s Program webpage. Learn more about UW ECE Affiliate Assistant Professor Colin Reinhardt on his bio page.
[post_title] => UW ECE Certificate Program in GPU-Accelerated Computing & Visualization to be offered this fall
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[post_content] => By Wayne Gillam / UW ECE News
[caption id="attachment_34887" align="alignright" width="575"]
This fall, a new textbook by UW ECE Professor Daniel Kirschen (above) will be introduced into the UW ECE power and energy systems undergraduate curriculum. “Power Systems: Fundamental Concepts and the Transition to Sustainability” helps students learn the ins and outs of how power systems work as well as the fundamental constraints that guide design and operation of these complex technologies. Photo by Ryan Hoover / UW ECE[/caption]
This fall, a new textbook providing students with an up-to-date overview of modern power systems will be introduced into the UW ECE power and energy systems undergraduate curriculum. “Power Systems: Fundamental Concepts and the Transition to Sustainability” helps students learn the ins and outs of how power systems work as well as the fundamental constraints that guide design and operation of these complex technologies. The textbook will also help to prepare students to engineer power systems capable of incorporating large amounts of renewable energy into electrical grids, which supports efforts across the globe aimed at protecting the environment and addressing climate change. This textbook is on-track to become an integral part of the UW ECE power and energy systems research and education program, which is viewed by academics and professionals alike to be one of the best of its kind in the nation and in the world.
The textbook was written by Daniel Kirschen, who is the Donald W. and Ruth Mary Close Endowed Professor in Electrical Engineering at UW ECE. Kirschen is a member of the Clean Energy Institute at the UW; is an Institute of Electrical and Electronics Engineers (IEEE) Fellow; is the editor in chief of the journal IEEE Transactions on Energy Markets, Policy and Regulation; and he is known internationally for his power and energy systems research at the Renewable Energy Analysis Lab. He was recently elected to the Washington State Academy of Sciences in recognition of his work on the integration of renewable energy sources into electrical grids. Kirschen is also well known for co-authoring “Fundamentals of Power System Economics,” a textbook that is considered to be essential reading for graduate students and practicing engineers working with power systems.
Over the last few years, Kirschen noticed that power systems textbooks for undergraduate students were becoming outdated.
“The existing textbooks for undergraduate students did not cover material that students need to know to be prepared to support the transition to sustainable power systems,” Kirschen said. “My new textbook provides a more recent, modern perspective on power systems. It also acknowledges that things are changing and will continue to change for several years.”
An undergraduate textbook based on UW ECE curriculum
[caption id="attachment_34891" align="alignright" width="250"]
Kirschen’s textbook will help to prepare students to engineer power systems capable of incorporating large amounts of renewable energy into electrical grids, which supports efforts across the globe aimed at protecting the environment and addressing climate change.[/caption]
This new textbook is based on courses Kirschen teaches at UW ECE. He said that the book also encapsulates the way power and energy systems are taught in the Department by a wide range of outstanding instructors. Other professors that teach about power and energy systems at UW ECE include Jungwon Choi, Scott Dunham, June Lukuyu, Alex Mamishev, Joshua Smith, and Baosen Zhang. Both Lukuyu and Zhang contributed to the textbook.
Kirschen’s textbook covers important topics that are essential to understanding power systems, such as the modeling of power system components, power flow, fault calculations, and maintaining power system stability. In addition, the textbook includes a detailed discussion of the demand for electricity and how that affects the operation of power systems, an overview of the various forms of conventional and renewable energy conversion, a primer on electronic power conversion, a careful analysis of the technical and economic issues involved in load generation balancing, and an introduction to electricity markets.
Kirschen said that he wrote the textbook with the intent of explaining not only the “what” and the “how” about power systems but also the “why.” This approach helps the reader better understand standard processes and procedures used in power systems and provides a knowledge base for developing solutions to modern problems resulting from rapid change. He aimed to keep the topics and the language he used accessible to undergraduate students.
“I’ve written a textbook in a very student-friendly manner, trying to keep the explanations very clear,” Kirschen said. “I focused first on providing students with an intuitive understanding of the material and then related it to the more rigorous matters later, after they have acquired this more intuitive understanding.”
On the horizon — an updated textbook for graduate students
[caption id="attachment_34896" align="alignright" width="250"]
Kirschen is also working on the third edition of his popular textbook for graduate students, “Fundamentals of Power System Economics.”[/caption]
Now that he has completed this undergraduate-level textbook, and it is making its way into UW ECE curriculum, Kirschen has begun working on the third edition of his textbook for graduate students (mentioned above). He anticipates that this updated version will be published within the next couple of years. He noted that power systems economics has been very much affected by the increasing reliance on renewable energy sources, and the landscape has changed greatly since the last edition of his graduate-level textbook, which was published in 2019.
“The world of power systems is changing rapidly, and so there is a tremendous demand from industry, government, and nonprofit organizations for people who understand our systems and could help drive these changes. Our responsibility as educators is to provide students with an education that provides them with the basics and the ability to understand and solve new problems,” Kirschen said. “The basic principles remain the same, but the applications keep changing so fast. Really being on top of the new research and new ideas and being able to incorporate those in your teaching is essential.”
Learn more about UW ECE Professor Daniel Kirschen on his bio page. More information about the Department’s power and energy systems research, graduate program, and undergraduate curriculum is located on our website.
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[post_content] => [caption id="attachment_35445" align="alignright" width="525"] UW ECE and Physics Professor Kai-Mei Fu has been elected an APS Fellow for research that has applications in quantum computing, quantum networks, and sensing technologies. Photo by Ryan Hoover / UW ECE[/caption]
Kai-Mei Fu, the Virginia and Prentice Bloedel Professor of Physics and Electrical and Computer Engineering at the University of Washington, has been elected an American Physical Society Fellow. Fu was recently elected to the APS Division of Quantum Information Fellowship for foundational contributions to fundamental and applied research on the optical and spin properties of quantum point defects in crystals. Fu was also recognized for their service and leadership in the quantum community.
Fu directs the Quantum Defect Laboratory at the UW, where their research focuses on identifying and controlling the quantum properties of point defects in crystals, which have a wide array of applications in quantum computing, quantum networks, and sensing technologies. Fu is also the director of the University’s NSF National Research Training program: Accelerating Quantum-Enabled Technologies and is co-chair of the University’s interdisciplinary QuantumX Steering Committee. They are the deputy director of the U.S. Department of Energy’s National Quantum Initiative Co-design Center for Quantum Advantage, and they hold a joint appointment with the Pacific Northwest National Laboratory.
Among other notable accomplishments, Fu has been instrumental in leading the establishment of the UW Graduate Certificate in Quantum Information Science and Engineering at the University. In addition to the APS Fellowship, Fu has received several other awards and honors for their work in research and education, including an NSF CAREER Award, a Cottrell Scholar Award and a UW College of Engineering Junior Faculty Award.
The APS recognizes its members for their outstanding efforts to advance physics and becoming an APS Fellow is considered to be a great honor. Each year, no more than one half of one percent of APS membership are elected as Fellows. The APS only elects members to Fellowship who have contributed to the advancement of physics by independent, original research or who have rendered other special service to the cause of the sciences.
More information about Professor Kai-Mei Fu can be found on their UW ECE bio page.
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[post_content] => [caption id="attachment_35445" align="alignright" width="525"] UW ECE and Physics Professor Kai-Mei Fu has been elected an APS Fellow for research that has applications in quantum computing, quantum networks, and sensing technologies. Photo by Ryan Hoover / UW ECE[/caption]
Kai-Mei Fu, the Virginia and Prentice Bloedel Professor of Physics and Electrical and Computer Engineering at the University of Washington, has been elected an American Physical Society Fellow. Fu was recently elected to the APS Division of Quantum Information Fellowship for foundational contributions to fundamental and applied research on the optical and spin properties of quantum point defects in crystals. Fu was also recognized for their service and leadership in the quantum community.
Fu directs the Quantum Defect Laboratory at the UW, where their research focuses on identifying and controlling the quantum properties of point defects in crystals, which have a wide array of applications in quantum computing, quantum networks, and sensing technologies. Fu is also the director of the University’s NSF National Research Training program: Accelerating Quantum-Enabled Technologies and is co-chair of the University’s interdisciplinary QuantumX Steering Committee. They are the deputy director of the U.S. Department of Energy’s National Quantum Initiative Co-design Center for Quantum Advantage, and they hold a joint appointment with the Pacific Northwest National Laboratory.
Among other notable accomplishments, Fu has been instrumental in leading the establishment of the UW Graduate Certificate in Quantum Information Science and Engineering at the University. In addition to the APS Fellowship, Fu has received several other awards and honors for their work in research and education, including an NSF CAREER Award, a Cottrell Scholar Award and a UW College of Engineering Junior Faculty Award.
The APS recognizes its members for their outstanding efforts to advance physics and becoming an APS Fellow is considered to be a great honor. Each year, no more than one half of one percent of APS membership are elected as Fellows. The APS only elects members to Fellowship who have contributed to the advancement of physics by independent, original research or who have rendered other special service to the cause of the sciences.
More information about Professor Kai-Mei Fu can be found on their UW ECE bio page.
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[post_title] => How the Remote Hub Lab is preparing engineering students for their future careers
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[post_content] => By Wayne Gillam / UW ECE News
[caption id="attachment_35170" align="alignright" width="575"] Incoming UW ECE faculty are (from left to right, clockwise): Ang Li, Yiyue Luo, Dinuka Sahabandu, Vasileios Charisopoulos, Banghua Zhu, Jing Yu. Photo collage by Isaiah Hoagland / UW ECE[/caption]
Beginning this fall and extending through autumn quarter 2025, UW ECE is welcoming six new faculty members who will bring a wide breadth of knowledge and technical expertise to the Department. Each of these outstanding new hires are making significant contributions to their respective fields, and they are pushing technology development forward in exciting, innovative ways. With these new additions, the Department will be adding faculty expertise in computer architecture, reconfigurable integrated systems, data science, and creative applications of artificial intelligence and machine learning to areas such as power and energy systems, cybersecurity, and intelligent textiles.
“I am excited to welcome these new faculty members to the Department,” said UW ECE Professor and Chair Eric Klavins. “Each is at the leading edge of their field and brings knowledge and unique skills that are sure to benefit our students, research efforts, and collaborations across the University.”
Ang Li
This month, Ang Li will become a tenure-track assistant professor in the Department. He is currently a UW ECE affiliate assistant professor and a visiting postdoctoral scholar for AMD, where he works with state-of-the-art microprocessors.
“I’m excited to join UW ECE and start my academic career,” Li said. “I’m looking forward to collaborating with the Department’s leading researchers across many disciplines and working with smart and hard-working students with diverse backgrounds.”
Li received his bachelor’s degree in electrical engineering from Tsinghua University and his master’s degree in electrical engineering from Princeton University, where he also received his doctoral degree in electrical and computer engineering. At the UW, Li will direct the PN Computer Engineering Lab, which will focus on innovating a variety of different devices ranging from computing systems to semiconductor circuits. The lab will also explore the interplay between classic and emerging computing technologies.
In his doctoral research, Li developed a silicon-proven, open-source field programmable gate array, or FPGA, research and prototyping framework called the Princeton Reconfigurable Gate Array, or PRGA. He also studied tightly integrated, manycore-eFPGA, system-on-chip, or SoC, architectures. He has been a leading member in two multi-university teams who successfully developed two silicon prototypes, including a 2.2 billion-transistor, Linux-capable, fully cache-coherent, manycore-accelerator-eFPGA SoC, which is one of the biggest academic tape-outs of its kind to date.
Yiyue Luo
Also this month, Yiyue Luo will become a tenure-track assistant professor in the Department. Luo is currently a UW ECE affiliate assistant professor and a research assistant in the Computational Design & Fabrication Group at the Massachusetts Institute of Technology, or MIT.
“I’m thrilled to be joining UW ECE! I look forward to joining this vibrant, multidisciplinary, and collaborative community,” Luo said. “The extensive resources in digital fabrication, world-class education and research programs, and the opportunity to work alongside incredible researchers with a wide range of expertise make the UW a perfect place for me!”
Luo received her bachelor’s degree in materials science and engineering from the University of Illinois Urbana-Champaign before going on to earn her master’s degree in electrical engineering from MIT, where she also received her doctoral degree in electrical and electronics engineering.
Her research interests are at the intersection of digital fabrication, human-computer/robot interaction, and applied artificial intelligence. She creates intelligent textiles that incorporate sensors and other technologies into knitted fabrics. Her projects include machine-knitted pneumatic actuators, digitally embroidered smart gloves, machine-knitted haptic textiles, and much more.
Luo’s research has been published in interdisciplinary journals, such as Nature Electronics and Nature Communications; presented at top human-computer interaction, robotics, and learning venues; featured in prominent media outlets; and shown in public museums and World Congress exhibitions. This year, she was listed as one of the Forbes 30 Under 30 in Science, North America.
Dinuka Sahabandu
Dinuka Sahabandu will become an assistant teaching professor in the Department in December 2024. Sahabandu is currently a postdoctoral researcher in the Network Security Lab, which is led by UW ECE Professor and former Chair Radha Poovendran. There, Sahabandu works on projects involving machine learning, artificial intelligence, and cybersecurity.
“I'm excited to join UW ECE and collaborate with its world-class faculty and students, which offers an unparalleled environment for learning and growth,” Sahabandu said. “The opportunity to integrate cutting-edge research from the UW and well-established top-tier industries in the Seattle area into my teaching is a thrilling start to my career as an educator. I'm also looking forward to being part of a diverse and inclusive UW ECE community that fosters innovation and collaboration from all perspectives.”
Sahabandu received his bachelor’s and master’s degrees in electrical and electronics engineering from Washington State University and his doctoral degree in electrical and computer engineering from UW ECE.
Sahabandu is an expert at developing scalable machine learning and reinforcement learning algorithms to produce tools and solutions that ensure the security of cyber and physical systems. His doctoral research has been transitioned to high-level stakeholders, such as the U.S. Naval Research Laboratory as well as commercialized by Argus AI under the sponsorship of the U.S. Army Research Laboratory.
Vasileios Charisopoulos
In September 2025, Vasileios Charisopoulos will become a tenure-track assistant professor in the Department. He is currently a UW ECE affiliate assistant professor and an AI & Science postdoctoral scholar at the University of Chicago Data Science Institute.
“I am very excited to join UW ECE!” Charisopoulos said. “I think the department is uniquely positioned to produce transformative research given its highly collaborative culture, its representation and leadership in several interdisciplinary research centers across UW, and its ties with industry within the greater Seattle area.”
Charisopoulos received his Diploma in electrical and computer engineering from the National Technical University of Athens. He went on to receive his doctoral degree from Cornell University in operations research and information engineering.
Charisopoulos’ research interests include developing numerical optimization methods for machine learning, signal processing, and scientific computing. His interests encompass the mathematics of data science, with an emphasis on the interplay of optimization, high-dimensional statistical estimation, and numerical linear algebra.
In 2023, Charisopoulos was recognized as a Rising Star in Computational and Data Sciences by the Oden Institute at the University of Texas, Austin. He also received the Cornelia Ye Outstanding Teaching Assistant Award from Cornell University in 2021. His other awards and honors include receiving an Andreas G. Leventis Scholarship in 2020, a Schloss-Dagstuhl Support Grant for Junior Researchers in 2018, and a Cornell University Fellowship in 2017.
Jing Yu
Also in September 2025, Jing Yu will become a tenure-track assistant professor in the Department. She is currently a UW ECE affiliate assistant professor and a postdoctoral scholar at the University of Michigan. In spring 2025, she will join the University of Illinois Urbana-Champaign as a Grainger College of Engineering Distinguished Postdoctoral Fellow.
“I am thrilled to be joining UW ECE and collaborating with its talented and diverse faculty and students!” Yu said. “The vibrant research community here offers incredible opportunities for interdisciplinary collaboration, making UW ECE an ideal place for cutting-edge research at the intersection of control theory, machine learning, optimization, and sustainable energy systems.”
Yu received her bachelor’s degree in mechanical engineering from the Georgia Institute of Technology. She went on to earn her doctoral degree in control and dynamical systems from the California Institute of Technology, also known as Caltech.
Yu’s research interests include the interplay between control theory and machine learning, with a focus on online decision-making and distributed algorithms for large-scale sustainable energy systems. She was named an Amazon AI4Science fellow in 2023. She was also the recipient of several awards, including the Best Paper Finalist award in the Association for Computing Machinery, or ACM, e-Energy Conference in 2022 and the Caltech Amori Doctoral Prize in 2024.
Banghua Zhu
Banghua Zhu will also become a tenure-track assistant professor in the Department in September 2025. Zhu is currently a UW ECE affiliate assistant professor, and he works at a startup he co-founded, Nexusflow, which leverages cutting-edge research to create generative AI agents for business enterprises.
“I’m excited to join UW ECE and contribute to its world-class research and educational programs,” Zhu said. “The Department’s strong foundation in machine learning, combined with Seattle’s vibrant tech industry, creates an ideal environment for advancing research in language model training, evaluation, and serving. I look forward to collaborating with talented colleagues and students to push the boundaries of AI and large language models, while leveraging the unique opportunities that the UW and the Seattle area offer in bridging academic research with real-world applications.”
Zhu received his bachelor’s degree in electrical and electronics engineering from Tsinghua University and his doctoral degree in electrical engineering and computer science from the University of California, Berkeley.
His research focuses on improving the efficiency and safety of foundation models, specifically large language models. He is dedicated to creating open-source datasets and tools for public access. His research interests include training and evaluation of language models, game theory, reinforcement learning, human-AI interactions, and machine learning systems. He is a recipient of the 2023 David Sakrison Memorial Prize for outstanding research at the UC Berkeley Department of Electrical Engineering and Computer Sciences.
UW ECE would like to thank the faculty search committee, which was chaired in 2023–24 by UW ECE and Allen School Professor Georg Seelig and in 2024–25 by UW ECE and Physics Professor Kai-Mei Fu. The Department appreciates the committee members’ careful reviews, engaged participation, and generous welcome toward the candidates.
[post_title] => UW ECE welcomes six new faculty members
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[post_content] => By Wayne Gillam / UW ECE News
[caption id="attachment_35061" align="alignright" width="550"] After almost a decade in a successful career developing products built on artificial intelligence, data science, and machine learning, UW ECE alumna Arpita Ghosh Dacy (BSEE '10) was introduced by a friend to beauty pageants, which led her down an unexpected road that culminated in being crowned Mrs. Universe America 2023–24. Photo by Jasmeet K Photography[/caption]
UW ECE alumna Arpita Ghosh Dacy (BSEE ‘10) is a person who doesn’t limit herself. She is enthusiastic about trying new things and has learned first-hand the value of stepping outside her comfort zone. This was demonstrated early in her career, when she worked with cutting-edge technologies that were considered risky and unproven in the marketplace but later became widely adopted. Her openness to new experiences in both her business and personal life continues today.
Three years ago, after almost a decade in a successful career developing products built on artificial intelligence, data science, and machine learning, Dacy was introduced by a friend to beauty pageants, which led her down an unexpected road that culminated in being crowned Mrs. Universe America 2023–24. Now, in addition to taking on this new role while continuing to work in a leadership position at Amazon, Dacy gives back to a wide range of charitable organizations by volunteering her time as a workshop and program leader, mentor, and motivational speaker.
“When I first started to work in artificial intelligence 10 years ago, it was a very new field, and working primarily in machine learning and AI was thought by many to be a risk. But just look at how these areas are booming now! So, taking that chance, that calculated risk led by curiosity, paid off,” Dacy said. “I think it’s never too late to learn something new about yourself and explore new things. When I first entered beauty pageants, I stepped way outside of my comfort zone. But it was amazing. It broadened my point of view, and I grew as a person.”
Technical leader at Amazon
[caption id="attachment_35065" align="alignright" width="450"] In the Alexa Kids Experience team at Amazon, Dacy leads development of a wide range of products from concept to delivery that are designed to help children play, learn, and grow. Shown above, Alexa Echo Dot devices that look and talk like owls and dragons. Photo courtesy of Amazon.[/caption]
At Amazon, Dacy is a senior technical program manager in the Alexa Kids Experience team. There, she leads development of a wide range of products from concept to delivery that are designed to help children play, learn, and grow. Most recently, her team has been launching pioneering Alexa features, such as the “Hey Disney!” voice assistant, kid-friendly character voices for Alexa, and Explore with Alexa — Amazon’s very first conversational feature for kids that leverages Alexa’s large language model technology to present fun facts and trivia questions.
Dacy said that products such as these are designed to inspire a child’s creativity, curiosity, and imagination. For example, Alexa applications, such as Amazon Math, are designed to help kids build basic math skills, interactive books encourage creative thinking and reading, and Morning Routines help children foster independence by building their own routine for starting the day.
“Alexa Kids aims to provide an engaging learning experience for kids,” Dacy said. “My daughter loves the kid-friendly Alexa features, and I love what a safe and engaging educational resource they have been for our family.”
As a technical program manager and a mother of a seven-year-old daughter who uses Alexa and Echo devices, Dacy said that safety was paramount. She also said that she enjoys the transparency Alexa Kids provides in monitoring her own child’s activity and is proud to help bring that vision of greater transparency to her everyday work.
Mrs. Universe America
[caption id="attachment_35068" align="alignright" width="360"] On December 10, 2023, Dacy was crowned Mrs. Universe America 2023–24 at the 11th annual Global Women Festival hosted by AmPowering in Seattle, Washington. In October, she will compete for the Mrs. Universe 2024 worldwide title in Incheon, South Korea. Photo by Jasmeet K Photography.[/caption]
In fact, it was Dacy’s daughter, Aishani, who was instrumental in bringing her into beauty pageants. Dacy was first introduced to this world in 2021 by a friend who invited her to attend a pageant sponsored by AmPowering, a non-profit organization founded by Menka Soni, which is committed to empowering women and youth, enriching families, and transforming communities. At the event, Dacy noticed that there were opportunities for children to participate in fashion shows and pageants. After talking with Aishani and learning that she was excited about getting involved, Dacy took her to get a headshot done for a Macy’s Kids segment in the North America Fashion Week show. As they were leaving the photoshoot, a modeling coach noticed Dacy and insisted she have her photo taken as well. From there, Dacy was discovered by the modeling industry, and designers reached out, encouraging her to participate in modeling and beauty pageants. So, Dacy took the plunge and ended up achieving a whirlwind string of successes. On December 10, 2023, she won the national title and was crowned Mrs. Universe America 2023–24 at the 11th annual Global Women Festival hosted by AmPowering in Seattle, Washington. In October, Dacy will compete for the Mrs. Universe 2024 worldwide title in Incheon, South Korea.
The experience of participating in beauty pageants pushed Dacy far outside her comfort zone.
“I have no modeling or pageantry background. I come from engineering, a tech background,” Dacy said. “A good thing about AmPowering’s pageant process is that it has a lot of mentors and training. My coach, Shivani Singh (co-founder of Coachnista), taught me everything I know about pageant presentations. There’s so much that goes into this, and I’m still her student, prepping for Mrs. Universe worldwide.”
During her reign as Mrs. Universe America, Dacy discovered that success in this venue opened doors and created experiences that otherwise would not have been possible for her. Since earning her title, she’s been invited to more events to talk about her life in engineering and balancing roles as a tech leader, mother, and mentor. She also has been able to promote her Mrs. Universe America platform, which is focused on empowering women, and in particular, women in STEM fields.
A mentor who gives back to the community
In keeping with her Mrs. Universe America platform, Dacy is passionate about supporting women and providing them with the tools they need to succeed. In addition to AmPowering, she is involved in several other charitable organizations that help women, including Helen’s Place women’s shelter, the New Bethlehem Project for families, and API Chaya. In 2023, she spoke at the Grace Hopper Conference for Women in Technology and mentored many individuals involved with the organization. She also is a mentor and speaker for women at Amazon and provides learning and discussion sessions focused on achieving better work-life balance.
At the UW, Dacy has been involved with Women Engineers Rise, or WE Rise, in the UW College of Engineering since she was an undergraduate student. Today, she is a professional advisory board member in the organization, mentors students, and recently spoke at the WE Rise annual conference as well as the We Rise 2024 Graduation Celebration and Thank You Celebration Tea. She is also a professional alumni member in the UW chapter of the Sigma Lambda Gamma National Sorority, which she has been actively involved with since her undergraduate years. Other organizations Dacy was affiliated with while attending the UW include the Society of Women Engineers and the National Society of Collegiate Scholars.
“Being a woman of color and in the STEM field, sometimes imposter syndrome looms large. But when you get these opportunities to meet others who have crossed these barriers and are making it, that is huge.” — UW ECE alumna Arpita Ghosh Dacy (BSEE '10)
As an undergraduate student at UW ECE, Dacy performed electrical and biomedical engineering research, tutored pre-engineering students in math and science, and graduated on the Dean’s List. She said that Cathryne Jordan, from the CoE’s Office of Inclusive Excellence, was her academic adviser and an influential mentor during this time. Since then, Jordan has remained a mentor and friend to Dacy for over 18 years.
“Being a woman of color and in the STEM field, sometimes imposter syndrome looms large. But when you get these opportunities to meet others who have crossed these barriers and are making it, that is huge,” Dacy said. “I will forever be grateful to Cathryne for providing me with guidance and opportunities when I was an undergrad and then inviting me to come back and talk to students as an alumna and industry executive.”
Looking ahead, Dacy said she would like to continue the trajectory she is on, working with products built on AI and new technologies. She is aiming to develop and innovate products that can improve and enhance people’s lives and leverage AI’s capabilities for good. She is particularly interested in large language models and how that technology could be applied in the marketplace. She is also looking forward to representing America this fall at the Mrs. Universe 2024 worldwide pageant.
When asked what advice she might give to students in engineering and STEM, Dacy was forthright and emphasized the importance of courage.
“Do not be afraid, and don’t let imposter syndrome get in the way of your success. Try to find mentors and join groups and organizations that uplift you,” she said. “Step out of your comfort zone. Don’t be afraid to take a risk. Don't let negativity stop you. Stretch your potential.”
More information about Arpita Ghosh Dacy can be found on her personal website and at her LinkedIn profile.
[post_title] => Arpita Ghosh Dacy — tech leader, mentor, and Mrs. Universe America
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[post_content] => By Wayne Gillam / UW ECE News
[caption id="attachment_34944" align="alignright" width="550"] UW ECE's Certificate Program in GPU-Accelerated Computing & Visualization is designed for working professionals and graduate students. This three-quarter, online program takes students on a deep dive into the graphics processing unit, or GPU, a critical piece of modern computer architecture.[/caption]
Starting autumn quarter 2024, UW ECE will again be providing the Certificate Program in GPU-Accelerated Computing & Visualization for working professionals and graduate students. This three-quarter, online program is affiliated with the Professional Master’s Program, and it takes students on a deep dive into the graphics processing unit, or GPU, which is a critical piece of modern computer architecture. Besides enabling the graphics seen on desktop computers, laptops, and mobile devices, GPUs also provide computing power for a wide range of other data-intensive applications, such as gaming, cloud computing, scientific computing, machine learning and artificial intelligence, robotics, and much more.
The Certificate Program is taught by UW ECE Affiliate Assistant Professor Colin Reinhardt, who is a UW alumnus (BSEE ‘05, BS Physics ‘05, Ph.D. ‘10) and an engineer in the U.S. Navy, where he leads a team of software engineers and scientists that specialize in GPU computing for physics-based modeling and simulation. Reinhardt is an expert on GPU application programming interfaces, or APIs, such as CUDA, OpenCL, Vulkan, and OpenGL. He also has expertise in a wide range of GPU applications, including scientific computing and visualization, physically based rendering, 3D-modeling and simulation, predictive rendering, machine/deep learning, and neural networks. Below are questions and answers with Reinhardt about GPUs and the Certificate Program that explain more details about this exciting course of study.
What is a graphics processing unit, or GPU?
[caption id="attachment_34951" align="alignright" width="450"] UW ECE Affiliate Assistant Professor Colin Reinhardt[/caption]
A graphics processing unit, which is commonly called “GPU” for short, is a specialized microprocessor subsystem that most computers today have, whether it’s a desktop workstation, laptop, or a mobile smartphone. All these devices have GPUs inside of them, and they work alongside the computer's central processing unit, or CPU (which is the main “brain” of your computer). You can think of the GPU as the workhorse of your computer for many compute-intensive tasks.
Fundamentally, the GPU is about massively parallel multiprocessing capability. It allows you to do a lot of computation, faster. But there are challenges in how you write the code and how you structure your algorithms to use this power effectively. For example, there are certain conditions that must be met for an algorithm to be parallelizable. And then, if you want your algorithm to be parallelized, how do you do that efficiently for a given GPU architecture? That’s a major focus in this Program, particularly in the GPU computing course.
What sorts of things do GPUs make possible?
The original, driving purpose for GPUs was to accelerate the production of 3D graphics. They are optimized for this and are still used heavily for that purpose. Another place that GPUs are critical is in image processing. So, in scientific fields, for example, GPUs are used for doing physically based algorithms to process video. Anytime there are large numbers of pixels and large images being processed, such as for additional post-processing, special effects, or image analysis — GPUs are well suited for all those problems.
Biomedical applications are another big area. GPUs are used for biomedical image analysis, image fusion, and 3D-computed tomography. And as GPU capabilities progress, the ability to deliver solutions progresses as well. We’re now seeing real-time 3D visualization of fused biomedical images that include positron emission tomography, computed tomography, and magnetic resonance imagery. All these different modalities that are imaging into the human body and producing critical diagnostic and therapeutic imagery are fundamentally driven and accelerated by GPUs.
One of the biggest applications of GPUs today is for machine learning and artificial intelligence. Deep learning models, natural language processing models, and large language models, such as ChatGPT, DALL-E, and Microsoft CoPilot all critically depend on GPUs for training. GPUs also help engineers and scientists deal with massive amounts of data, known as “big data,” because GPUs enable us to compute faster. Furthermore, one step removed, they allow us to train these deep learning models and other machine learning tools at massive scale, which can then help to process more data even faster, and even in real time. So, overall, I think GPUs are a critical tool that are only going to continue to become more important and powerful as the technology continues to progress.
Could you tell me more about your background as it relates to GPUs and this Certificate Program?
I’m an alumnus of the Department. I received a double bachelor’s degree in physics and electrical engineering from the UW in 2005, and then I went on to earn my doctoral degree from UW ECE in 2010. As a graduate student, I did research in an area related to GPUs, free space optical communication, which is a very compute-intensive field.
After completing my doctoral degree, I went to work for the U.S. Navy, where I continued to work in free space optical communications and related areas involving LiDAR, laser systems, and a lot of computational and numerical modeling of the atmosphere. These are places where computational demands are extremely high. So, use of the GPU in my work became very important, and I started to explore using these tools for the work I did with the Navy. That led me to become familiar with GPU capabilities early on. I also had a desire to teach, give back, and support the UW. So, in 2017, I became an affiliate assistant professor in the Department. Today, in addition to my teaching duties at UW ECE, I still work as a Navy engineer, where I lead a distributed team of software engineers and scientists that do GPU computing and hardware-accelerated algorithm development.
Teaching in the Professional Master’s Program is very inspiring for me because of the quality of the students that I’ve had a chance to work with. I’ve been very impressed with the creativity, skill, and the diligence of the students that I’ve worked with over the years in this Program. I’ve seen a lot of impressive projects done by students in these classes that are applicable to many different fields ranging from mechanical engineering to biomedical and scientific applications.
There’s a huge industry demand for students who have this knowledge and can put it into practice. So, in my curriculum, I focus on the practical skills you will need to use these tools and frameworks, as opposed to just learning a bunch of theory, where there could be a gap between that theory and how you apply it to real world tasks. All the classes that I teach have a major project-based element to them, which gives students a chance to work through the whole design-development-testing life cycle in a practical way and apply the GPU theory and methods we’ve learned.
What will students learn in this Certificate Program?
The Certificate Program is all online and consists of three courses, one each quarter. Typically, we offer these in autumn, winter, and spring, consecutively. The first quarter course is titled “Applied High-Performance GPU Computing.” It is focused on the fundamentals of how GPUs work, GPU hardware architecture as well as software, algorithm analysis and requirements, and analytical methods to determine when an algorithm is parallelizable. I also teach techniques to map your algorithm to the GPU hardware. We do this using primarily CUDA, which is a Nvidia-specific GPU language.
The second quarter course is called “GPU-Accelerated Interactive Scientific Visualization Techniques.” This title emphasizes the fact that we make use of GPU capabilities to accelerate graphics visualization at interactive rates. The course starts off with the basics of 3D-computer graphics because you need to understand the structures and the methods for a traditional 3D-computer graphics pipeline. Then, we talk about how those different steps in the 3D-computer graphics pipeline map to the GPU hardware. We look at OpenGL and Vulkan, which are the two major open-source industry standard APIs for using the GPU to do 3D-computer graphics. The focus in this course is not just on game graphics, but on more general scientific visualization, in particular, biomedical image visualization. But this is also applicable to just about any kind of general engineering visualization, or even more generally, data visualization, which moves into this important new domain of visualizing and understanding deep learning and machine learning models. So, there’s some interesting methods that utilize 3D and multi-dimensional visualization techniques to look inside deep learning networks and try to understand what they’re doing. We will look at some of those methods as well as more traditional, scientific visualization with fluid dynamics and computational electromagnetics.
The third quarter is what I call “Advanced GPU Computing and Visualization.” In this course, we bring together both scientific visualization and GPU computing. This is the culmination of the curriculum, and it integrates what you’ve learned in the first two quarters. We discuss how to develop a system that might be doing both visualization and heavy computing simultaneously. Most production-scale systems need to do this kind of thing. But there are additional challenges, such as tying together your algorithms between, say, Vulkan and CUDA or Vulkan and OpenCL. Furthermore, we cover some advanced techniques leveraging new, specialized GPU hardware features. For instance, we look at programming tensor cores, which offer even more speedup for particular computation types, and we’ll also look at the programming of the new Nvidia ray-tracing cores. This is hardware-accelerated ray tracing inside the latest Nvidia RTX GPUs. This is an exciting new area that’s just starting to be leveraged.
I also teach what I call “black art techniques.” These are programming skills that are generally not taught in schools or in theoretical textbooks. They are not well documented. Manufacturers are extremely careful with their hardware architecture information. They don’t publish it. They protect it and don’t disclose it. So, it’s difficult to learn. This is something that I wrestle with as an engineer myself: How do you know what’s happening in this black box that your code is running on? And so, there are reverse engineering and micro-benchmarking techniques that can be used to tease out particulars that could be critical in optimizing your code. We get into some of those things as well as how you can infer or learn particulars that could be very useful in writing highly performant code on the device when the vendors are not going to tell you that information.
Who is a good fit for this Program?
This Program is a good fit for any student who is interested in increasing their marketability in machine learning, 3D graphics, image processing, or computer vision. All these areas are well suited to having a strong foundation in low-level GPUs and scientific visualization. This Program is also for professionals who are wrestling with compute-intensive problems, where either their current code or systems are not fast enough (maybe they’re not processing as much data as they want to or need to, maybe their accuracy is limited). All these areas can be enhanced and accelerated by using GPUs. So, anybody who is a professional wrestling with those kinds of problems and wants to learn techniques to improve their system is another good candidate.
How could skills gained in this Program benefit an individual’s career?
I think that the skills learned in this program can benefit an individual’s career by providing them with a low-level understanding of GPU architecture as well as how to write tuned code for GPUs and think in parallel software development framework, which is not something that is traditionally taught in software engineering. All these things will help an individual become a valuable contributor to software or system development teams or potentially continue their education to do further research in the field.
What sorts of tools and technologies will students have access to?
We use a lot of tools and technologies in the Program. First, we use Amazon Web Services, or AWS, as a framework for the whole curriculum development. We also use it to provide GPUs that the students will use in doing their exercises and doing their programming. So, you don’t need to have a device with an Nvidia GPU to do this course. You will get access to a real GPU on the AWS cloud, and students have dedicated use of Nvidia GPU time on their cloud instances. So, that’s nice. And because it’s through AWS, you can log in remotely. You could do this from a variety of places and access the system from many types of client devices.
Then, for the actual curriculum content, students will obviously be studying GPU architecture. In particular, we will be looking at the Nvidia GPUs, but I will also talk about the other key players in the GPU market space, which are AMD and Intel. We’ll look at their GPU architectures and the similarities and differences between what they are doing compared to Nvidia.
We will look primarily at CUDA, the latest generation of the CUDA toolbox, and we’ll be using that to program the Nvidia GPUs. We’ll also talk about OpenCL, which is an open industry Khronos standard analogous to CUDA but device agnostic. So, it’s not tied to any one vendor, although I will say Intel and AMD are strong proponents of OpenCL.
Then, when it comes to scientific visualization, we’ll be focusing on two other Khronos standards, which are OpenGL, which was the traditional, dominant API for 3D-graphics programming, but in the last few years has been replaced and superseded by Vulkan, which is the new, modern GPU-centric graphics API. So, we will be using Vulkan.
And then we’ll be using several other Nvidia tools that come along with the CUDA toolkit to do analysis and profiling. We’ll learn the CUDA compiler tool, some of the CUDA extensions, and some of the other CUDA libraries that are included that have pre-written, GPU capabilities. There are also other profilers and analysis tools that we’ll be using.
Is there anything else students might want to know?
They might be curious about prerequisites. The official set of required and recommended prerequisites for the track is provided on the website. However, I just want to comment that there is a margin of flexibility, where, if you are coming in slightly underprepared, it is possible to compensate by doing a bit of extra work alongside the regular curriculum to supplement and enrich your understanding of the background knowledge areas. But it does take a serious commitment to doing the extra work and not falling behind in your assignments!
For example, having an intermediate to advanced skill level in C and C++ programming is strongly recommended. It is highly beneficial and will make your life easier if you have that level of experience, but it is not necessarily a showstopper. I have had students who didn’t know C and C++ very well coming in. They had a little bit more of a learning curve to surmount, but they were able to do it. I certainly will do what I can to assist. So, if you’re motivated and willing to put in the extra work, you can still complete the Program.
The same thing applies for the stated recommended prerequisite about having computer architecture background experience. We do get into topics such as microprocessor architecture, memory hierarchies, and cache architectures, which are important on these devices to make them run most efficiently. But again, it’s certainly something that a student could pick up on their own while they do the coursework. So, in the spirit of parallel programming, if you’re willing to learn and work at the same time, you can do it. But it will require more biological neural flops! Sorry, I had to squeeze in a computer/AI nerd joke!
For more information, visit the UW ECE Certificate Program in GPU-Accelerated Computing & Visualization webpage and the UW ECE Professional Master’s Program webpage. Learn more about UW ECE Affiliate Assistant Professor Colin Reinhardt on his bio page.
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[post_date] => 2024-08-02 08:30:43
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[post_content] => By Wayne Gillam / UW ECE News
[caption id="attachment_34887" align="alignright" width="575"] This fall, a new textbook by UW ECE Professor Daniel Kirschen (above) will be introduced into the UW ECE power and energy systems undergraduate curriculum. “Power Systems: Fundamental Concepts and the Transition to Sustainability” helps students learn the ins and outs of how power systems work as well as the fundamental constraints that guide design and operation of these complex technologies. Photo by Ryan Hoover / UW ECE[/caption]
This fall, a new textbook providing students with an up-to-date overview of modern power systems will be introduced into the UW ECE power and energy systems undergraduate curriculum. “Power Systems: Fundamental Concepts and the Transition to Sustainability” helps students learn the ins and outs of how power systems work as well as the fundamental constraints that guide design and operation of these complex technologies. The textbook will also help to prepare students to engineer power systems capable of incorporating large amounts of renewable energy into electrical grids, which supports efforts across the globe aimed at protecting the environment and addressing climate change. This textbook is on-track to become an integral part of the UW ECE power and energy systems research and education program, which is viewed by academics and professionals alike to be one of the best of its kind in the nation and in the world.
The textbook was written by Daniel Kirschen, who is the Donald W. and Ruth Mary Close Endowed Professor in Electrical Engineering at UW ECE. Kirschen is a member of the Clean Energy Institute at the UW; is an Institute of Electrical and Electronics Engineers (IEEE) Fellow; is the editor in chief of the journal IEEE Transactions on Energy Markets, Policy and Regulation; and he is known internationally for his power and energy systems research at the Renewable Energy Analysis Lab. He was recently elected to the Washington State Academy of Sciences in recognition of his work on the integration of renewable energy sources into electrical grids. Kirschen is also well known for co-authoring “Fundamentals of Power System Economics,” a textbook that is considered to be essential reading for graduate students and practicing engineers working with power systems.
Over the last few years, Kirschen noticed that power systems textbooks for undergraduate students were becoming outdated.
“The existing textbooks for undergraduate students did not cover material that students need to know to be prepared to support the transition to sustainable power systems,” Kirschen said. “My new textbook provides a more recent, modern perspective on power systems. It also acknowledges that things are changing and will continue to change for several years.”
An undergraduate textbook based on UW ECE curriculum
[caption id="attachment_34891" align="alignright" width="250"] Kirschen’s textbook will help to prepare students to engineer power systems capable of incorporating large amounts of renewable energy into electrical grids, which supports efforts across the globe aimed at protecting the environment and addressing climate change.[/caption]
This new textbook is based on courses Kirschen teaches at UW ECE. He said that the book also encapsulates the way power and energy systems are taught in the Department by a wide range of outstanding instructors. Other professors that teach about power and energy systems at UW ECE include Jungwon Choi, Scott Dunham, June Lukuyu, Alex Mamishev, Joshua Smith, and Baosen Zhang. Both Lukuyu and Zhang contributed to the textbook.
Kirschen’s textbook covers important topics that are essential to understanding power systems, such as the modeling of power system components, power flow, fault calculations, and maintaining power system stability. In addition, the textbook includes a detailed discussion of the demand for electricity and how that affects the operation of power systems, an overview of the various forms of conventional and renewable energy conversion, a primer on electronic power conversion, a careful analysis of the technical and economic issues involved in load generation balancing, and an introduction to electricity markets.
Kirschen said that he wrote the textbook with the intent of explaining not only the “what” and the “how” about power systems but also the “why.” This approach helps the reader better understand standard processes and procedures used in power systems and provides a knowledge base for developing solutions to modern problems resulting from rapid change. He aimed to keep the topics and the language he used accessible to undergraduate students.
“I’ve written a textbook in a very student-friendly manner, trying to keep the explanations very clear,” Kirschen said. “I focused first on providing students with an intuitive understanding of the material and then related it to the more rigorous matters later, after they have acquired this more intuitive understanding.”
On the horizon — an updated textbook for graduate students
[caption id="attachment_34896" align="alignright" width="250"] Kirschen is also working on the third edition of his popular textbook for graduate students, “Fundamentals of Power System Economics.”[/caption]
Now that he has completed this undergraduate-level textbook, and it is making its way into UW ECE curriculum, Kirschen has begun working on the third edition of his textbook for graduate students (mentioned above). He anticipates that this updated version will be published within the next couple of years. He noted that power systems economics has been very much affected by the increasing reliance on renewable energy sources, and the landscape has changed greatly since the last edition of his graduate-level textbook, which was published in 2019.
“The world of power systems is changing rapidly, and so there is a tremendous demand from industry, government, and nonprofit organizations for people who understand our systems and could help drive these changes. Our responsibility as educators is to provide students with an education that provides them with the basics and the ability to understand and solve new problems,” Kirschen said. “The basic principles remain the same, but the applications keep changing so fast. Really being on top of the new research and new ideas and being able to incorporate those in your teaching is essential.”
Learn more about UW ECE Professor Daniel Kirschen on his bio page. More information about the Department’s power and energy systems research, graduate program, and undergraduate curriculum is located on our website.
[post_title] => New textbook provides a fresh perspective on modern power systems
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[post_modified] => 2024-08-02 08:31:42
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