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UW and UW ECE spinout WiBotic part of $5.8M contract to study wireless charging on moon

A team of multiple organizations, including the UW and UW ECE spinout Wibotic, plans to develop a line of lightweight, ultrafast wireless chargers that could help both humans and robots live and work on the moon.

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UW and UW ECE spinout WiBotic part of $5.8M contract to study wireless charging on moon Banner

UW ECE doctoral student Vikram Iyer featured in AAAS for murder hornet tracking; finding ways to meld nature and science

Iyer's impressive work in radio device miniaturization and insect tagging was recently highlighted by the American Association for the Advancement of Science (AAAS).

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UW ECE doctoral student Vikram Iyer featured in AAAS for murder hornet tracking; finding ways to meld nature and science Banner

UW ECE seeks outstanding faculty candidates in quantum information science & technology

UW ECE invites applicants for 2 tenure track assistant professors with expertise in quantum information science & technology (QIST). Join a vibrant, diverse and world-class entrepreneurial community of researchers and students who are pioneering the development of groundbreaking quantum-enabled technologies at UW.

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UW ECE seeks outstanding faculty candidates in quantum information science & technology Banner

Engineers design a tiny, implantable chip to deepen understanding of the brain and enable better treatments for neurological disorders

A UW ECE research team has designed a new chip for neural interfaces that will help increase knowledge about the brain and enable better treatments for a wide range of medical conditions such as Parkinson’s disease and epilepsy.

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Engineers design a tiny, implantable chip to deepen understanding of the brain and enable better treatments for neurological disorders Banner

UW ECE team receives $800K award from the National Science Foundation to help increase capacity of quantum computing systems

A new $800,000 National Science Foundation (NSF) Convergence Accelerator Award will help dramatically increase the capacity of quantum computing and simulation systems to retain and process information.

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UW ECE team receives $800K award from the National Science Foundation to help increase capacity of quantum computing systems Banner

AI model uses smartphone location data to predict power grid usage

Researchers at Microsoft and the University of Washington, including UW ECE professor Baosen Zhang, propose an AI system that uses smartphone location data to forecast electrical load.

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AI model uses smartphone location data to predict power grid usage Banner

News + Events

https://www.ece.uw.edu/spotlight/mooncharging/
https://www.ece.uw.edu/spotlight/iyer-murderhornets/
https://www.ece.uw.edu/spotlight/qist-faculty-search/
https://www.ece.uw.edu/spotlight/tinychip/
https://www.ece.uw.edu/spotlight/nsf2020-quantum/
https://www.ece.uw.edu/spotlight/ai-powergrid/
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                    [post_content] => [caption id="attachment_20442" align="alignright" width="315"] UW ECE alum Ben Waters is co-founder and CEO of WiBotic — a UW ECE spinout and key organization involved in the contract to study wireless charging on the moon. (University of Washington)[/caption]

One challenge to life in space is power: how to keep humans cozy and robots working when there are no built-in power outlets and when solar power is not always an option.

Now a team of organizations — led by the space technology company Astrobotic and including the University of Washington and the UW Department of Electrical & Computer Engineering (UW ECE) spinout WiBotic — has received a $5.8 million contract to develop a line of lightweight, ultrafast wireless chargers that could help both humans and robots live and work on the moon. This contract is part of the NASA Tipping Point call for proposals.

Though prototypes for wireless charging have existed since 2011, this new magnetic resonance-based power supply system would be the first of its kind in space.

Wireless charging in space comes with its own set of issues, such as how to keep the metallic iron in moon dust — or lunar regolith — from interfering with charging connections. The UW has received $440,000 from this contract to study how lunar regolith affects wireless power transfer.

“Moon dust is very fine and tends to stick to surfaces because it gets electrically charged. The UW team is tackling the fundamental research question of how dust particle size and composition affects power transfer efficiency,” said UW lead researcher Joshua Smith, a professor in both the Paul G. Allen School of Computer Science & Engineering and UW ECE. “We plan to take an approach that is a hybrid of science and engineering: We will develop a synthetic moon dust that is consistent with known relevant properties, but that represents the worst case for our wireless power transfer system.

[caption id="attachment_20448" align="alignright" width="315"] Joshua R. Smith, a UW professor in both ECE and CSE, will be UW's lead researcher for understanding how moon dust particle size and composition affect power transfer efficiency. (photo by Tara Gimmer)[/caption]

“Our work will be the basis of the engineering requirements for the rest of the team. It will help us answer questions such as: how much extra power should be transferred to overcome the expected losses to heat? Or how much cooling capacity needs to be built into the system to get rid of that heat produced in the moon dust?”

Astrobotic’s CubeRover, which was developed in collaboration with the NASA Kennedy Space Center, is the first space technology that will be integrated with the wireless charging system. Part of NASA’s Tipping Point contract will fund the development of CubeRover’s intelligent autonomous navigation system, which will enable precise navigation where GPS is not an option. This will equip the CubeRover — and other planetary roving technologies — to find charging docks to power up again and again, and survive the 14-day lunar night.

Astrobotic will space-qualify the entire system, test engineering and flight models, and lead integration of CubeRover and the multi-kilowatt, ultrafast wireless charging system, designed by WiBotic. WiBotic will also provide engineering, mechanical and electrical design support.

[caption id="attachment_20443" align="alignleft" width="347"] A team of multiple organizations, including the UW and UW ECE spinout Wibotic, plans to develop a line of lightweight, ultrafast wireless chargers that could help both humans and robots live and work on the moon. (Sarah McQuate/University of Washington)[/caption]

“These rovers need easy and reliable access to power in an environment that includes extremely abrasive dust and severe temperatures, making this a perfect application for WiBotic’s innovative non-contact proximity charging solutions,” says Ben Waters, UW ECE alum and WiBotic CEO. “We’re looking forward to working with Astrobotic and the team to deliver flexible and durable charging stations that provide power to a range of manned and unmanned lunar vehicles.”

This wireless charging technology could have considerable utility not only on the moon, but also in critical space applications on Mars, in orbit and beyond. Future teams will be able to scale the wireless technology to diverse assets like lunar vehicles, power tools, flying systems and more. The base station, power receiver and CubeRover flight units will be delivered to NASA for inclusion into an upcoming lunar mission via the Commercial Lunar Payload Services program in 2023.

Adapted from a release by Astrobotic.
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[caption id="" align="alignright" width="311"]Vikram Iyer. Photo by Mark Stone/University of Washington. Vikram Iyer working with bees at the University of Washington. Photo by Mark Stone/UW Photo[/caption]
If tracking “murder hornets” sounds more like a job for an entomologist/detective, you might be surprised by this member of the hornet-tracking team: a Ph.D. candidate at the University of Washington's Department of Electrical and Computer Engineering (UW ECE) named Vikram Iyer. One of his most recent endeavors was collaborating with entomologists to track Asian hornets (also called “murder hornets”), which have been spotted in Washington state. According to Washington State Department of Agriculture (WSDA), these hornets, which are originally from certain parts of Asia including Japan, South Korea, and China, are dangerous and efficient killers of bees. In a mere few hours, just a few Asian hornets can attack and slaughter an entire colony by decapitating the bees and taking over their hives. The WSDA warns that these hornets pose an immeasurable threat, and if they are not held in check and eradicated, they have the potential to damage the environment, economy, and public health. “We heard about this issue with the murder hornets and thought, ‘We have the technology that could potentially be helpful with this problem,’” Iyer says. He contacted WSDA and explained that they have little wireless transmitters that could be used to tag a hornet and then track it back to its nest. “The past few years, I’ve done a series of projects where we’ve been developing small electronics, things like little wireless sensors that are small enough to ride on the back of live insects,” says Iyer. His portfolio includes putting a sensor on a live bumblebee, a camera on the back of a live beetle (which was published in a July 2020 study in ScienceRobotics), and mounting sensors on moths that can be dropped at specific targets. Iyer notes that this experience was handy as the Asian hornet species nests underground, which makes it that much harder to locate them. Efforts in other countries to track them are often unsuccessful. “We started thinking about how we can use a small radio tag to actually follow the insect,” Iyer says. Their device has a battery, radio chip, antenna, and temperature sensor, and it sends out a Bluetooth signal about two times per second.
“We heard about this issue with the murder hornets and thought, ‘We have the technology that could potentially be helpful with this problem,’” Iyer says.
So far, WSDA has been able to identify two hotspots of activity near the Canadian border using a network of traps they set up. Then, when they caught a live hornet, Iyer went to where the WSDA entomologists were and helped them put the tracking devices on the insect. While Iyer has put devices on other insects such as bees and beetles himself for his previous projects, he left this one up to the insect experts: These murder hornets are not just dangerous for bees — they have extra-long stingers that they can use repeatedly and can squirt a caustic venom. Using a little noose made from dental floss and glue, the lead WSDA entomologist attached Iyer’s device onto the hornet after putting the hornet on ice to sedate it. Then they let it go. “We were able to follow it for about a quarter of a mile on our first attempt,” says Iyer. After flying for some time up in the trees, the hornet came down closer toward the ground and stopped for a while in a big patch of blackberries, where the team thought the nest might be. Unfortunately, it flew away at some point and they ended up losing the signal as it went further into the woods. [caption id="attachment_20400" align="alignleft" width="468"]Vikram Iyer Vikram Iyer investigates how a bumblebee (inside the container) performs with the sensor package attached to its back. Photo by Mark Stone/UW Photo[/caption] As of now, there are more hornets still at large, but with Iyer’s tech in the field, scientists have a much better shot at finding the nests. “This confirms that our tracking devices work, that this general approach works,” Iyer says. “It also points us in the same direction as a number of other sightings that are all kind of clustered around the same patch of woods pointing in one direction.” A 2020 recipient of The Marconi Society Paul Baran Young Scholars award, Iyer was recognized for his research focusing on different kinds of wireless technologies, including bio-inspired and bio-integrative wireless sensor systems, for communication, wireless power delivery, data collection, and more. Iyer has also been working on a project where a live insect or a small drone can carry some sort of sensor and then drop it at a location that is hard-to-reach or dangerous, like a volcano or for forest fire monitoring. In addition to his UW projects and applying for faculty positions, Iyer is also working with researchers at Microsoft on an air quality monitoring platform for cities that uses gas sensors to monitor air quality on a more granular scale. “I’m inspired by natural systems to design things, and my most recent works have been trying to augment them and leverage the capabilities of live animals to complement what we can engineer,” says Iyer. “That’s something that I’m interested in exploring.”
Story by Katherine Lee |  AAAS [post_title] => UW ECE doctoral student Vikram Iyer featured in AAAS for murder hornet tracking; finding ways to meld nature and science [post_excerpt] => [post_status] => publish [comment_status] => closed [ping_status] => closed [post_password] => [post_name] => iyer-murderhornets [to_ping] => [pinged] => [post_modified] => 2020-11-09 10:02:18 [post_modified_gmt] => 2020-11-09 18:02:18 [post_content_filtered] => [post_parent] => 0 [guid] => https://www.ece.uw.edu/?post_type=spotlight&p=20378 [menu_order] => 2 [post_type] => spotlight [post_mime_type] => [comment_count] => 0 [filter] => raw ) [2] => WP_Post Object ( [ID] => 20340 [post_author] => 26 [post_date] => 2020-11-03 13:15:24 [post_date_gmt] => 2020-11-03 21:15:24 [post_content] => Quantum Information Science & Technology Now accepting applications for two tenure track faculty positions   The University of Washington Department of Electrical & Computer Engineering (UW ECE) invites applications for two full-time, tenure-track faculty positions at the rank of assistant professor. Candidates making connections between QIST and data science, circuits, devices, controls, computer engineering, information theory and other existing efforts in the ECE department are particularly encouraged to apply, but all areas of QIST will be considered. The positions are multi-year appointments with 9-month service periods with an anticipated start date of September 1, 2021. Applications must be submitted by December 1, 2020 to receive full consideration. UW ECE offers an innovative, collaborative and inclusive environment in which our faculty and students succeed at finding impactful solutions to today’s challenges. The Seattle area is particularly attractive given the presence of significant industrial research laboratories, top technology companies, as well as a vibrant technology-driven entrepreneurial community that further enhances the intellectual atmosphere. We look forward to learning how the applicant's experience or future plans for teaching, research and service would support our commitment to diversity and inclusion. Qualifications Applicants for tenure-track and tenure-eligible positions must have earned a doctorate (or foreign equivalent) in electrical engineering, computer engineering, applied physics or related field by the date of appointment. View UW ECE QIST flyerLearn more and apply via Interfolio >
The new UW ECE positions are supported by a UW College of Engineering (COE) cluster hiring initiative in QIST, which also includes a new faculty hire in the UW Department of Mechanical Engineering (ME), while new Paul G. Allen School of Computer Science and Engineering (CSE) hires in QIST will be closely aligned with UW’s community of QIST researchers. “Our vision is for UW to have expertise across the full quantum stack,” said Kai-Mei Fu, UW associate professor of electrical and computer engineering (ECE) and physics and co-chair of UW’s interdisciplinary QuantumX Initiative. “Our future colleagues in ECE, ME, and CSE will help UW address the key QIST engineering challenges of performance and scalability. We want to help develop a Quantum Silicon Valley in the Pacific Northwest, and we want UW to be the #1 place in the world for students to come and build their skills in QIST.” [post_title] => UW ECE seeks outstanding faculty candidates in quantum information science & technology [post_excerpt] => [post_status] => publish [comment_status] => closed [ping_status] => closed [post_password] => [post_name] => qist-faculty-search [to_ping] => [pinged] => [post_modified] => 2020-11-03 13:23:35 [post_modified_gmt] => 2020-11-03 21:23:35 [post_content_filtered] => [post_parent] => 0 [guid] => https://www.ece.uw.edu/?post_type=spotlight&p=20340 [menu_order] => 3 [post_type] => spotlight [post_mime_type] => [comment_count] => 0 [filter] => raw ) [3] => WP_Post Object ( [ID] => 20271 [post_author] => 27 [post_date] => 2020-10-16 15:14:40 [post_date_gmt] => 2020-10-16 22:14:40 [post_content] => Story by Wayne Gillam | UW ECE News [caption id="attachment_20273" align="alignright" width="625"]Headshots of Chris Rudell and Visvesh Sathe UW ECE associate professors Chris Rudell (left) and Visvesh Sathe (right) led the research team that developed this implantable chip, which will help neuroscientists deepen our understanding of the brain and enable better treatments for a wide range of medical conditions and disorders. Photo illustration by Ryan Hoover[/caption] Chris Rudell and Vivesh Sathe have vision. Together, with graduate students in their labs at the University of Washington Department of Electrical & Computer Engineering (UW ECE), they have designed a sophisticated neural interface in the form of a small, implantable chip. This chip is designed to help neuroscientists deepen their understanding of the brain and promises to take engineers one step closer to developing more effective devices to treat neurological disorders and conditions such as Parkinson’s disease, epilepsy, depression and obsessive-compulsive disorder. Looking ahead, they developed the chip to be scalable and translatable into future technologies for decades to come. “This chip is tiny. It is two by two millimeters, and it has pure, unrefined electrical engineering at its core,” said Rudell, a UW ECE associate professor and member of the Center for Neurotechnology (CNT). “That’s what Visvesh and I are working toward, developing techniques that are more broadly applicable, that are geared toward translation into high-volume production by our industry partners. In addition, the circuits in this chip could be used in future generations of semiconductor technology, eventually becoming smaller and smaller as these silicon technologies begin to feature sub-nanometer dimensions.” “This work represents the promise of realizing a technology that will improve our understanding of how circuits in the brain are connected, furthering neuroscience’s understanding of neural plasticity [the brain’s ability to adapt and change over time],” added Sathe, who is a UW ECE associate professor and also a CNT member.

Big steps forward

[caption id="attachment_20277" align="alignright" width="525"]Two young men working on an electronic device UW ECE alumnus John Uehlin (left) in a 2016 photo taken in Rudell’s lab with Joshua Chen, a CNT Research Experience for Undergraduates summer program participant. Uehlin worked on an early version of the chip prototype when he was a graduate student. He is also lead author of the most recent paper from Rudell and Sathe’s labs that describes the current version of the chip. Chen is now a Ph.D. candidate at Rice University.[/caption] Rudell and Sathe are senior authors of a new paper in the IEEE Journal of Solid-State Circuits, written by Rudell’s graduate student John Uehlin. The paper describes research that is the culmination of several years of work and contributions by UW ECE graduate students such as William Anthony Smith, Venkata Rajesh Pamula, Eric Pepin and Daniel Michelliti, as well as CNT member Steve Perlmutter. The article describes in detail the chip’s functions as they apply to a neural interface, allowing electrical signals to pass back and forth between the brain and the device. A key step forward in this design is the effectiveness of the chip at performing signal-noise cancellation, which allows neurons in the brain to be electrically stimulated while simultaneously recording their response. This noise, or “artifact” cancellation becomes increasingly difficult to accomplish the smaller the chip size. Neural stimulation generally requires high voltage levels that are much too high for tiny, semiconductor technologies conducive to digital circuits. Rudell and Sathe addressed this problem by stacking circuits in a way that delivers the desired electrical stimulation current without damaging the chip. “That was what we worked on in our group for about five years, figuring out techniques to practically achieve high voltage output without hurting the transistors and substantially improving long-term reliability, which is key for devices planted in the body,” Rudell said. “We are trying to focus on semiconductor technologies at least a decade in the future, when we can make a chip similar to this one, so small that it becomes comparable in size to a grain of rice.” [caption id="attachment_20282" align="alignleft" width="300"]web_Micrograph of the fabricated 65-nm test chip Rudell and Sathe’s research team has developed a chip for neural interfaces that integrates neural recording, stimulation and signal processing for artifact cancellation all on a single device, using a 65-nanometer (nm) silicon technology. Next steps for the team includes integrating wireless power and data transfer on the same, tiny chip. Pictured above is a micrograph of the fabricated 65-nm test chip.[/caption] This, along with work by Sathe to improve artifact cancellation capabilities, allows for “low-latency neural circuit analysis” — the ability to identify and monitor short connections between neurons. This new capability will allow neuroscientists to read signals from the brain that they previously weren’t able to before because of the amount of signal interference caused by neural stimulation artifacts. “Analyzing low-latency neural connectivity has traditionally been difficult because of stimulation artifacts. These large, spurious signals can corrupt and even disable neural recording altogether for a brief period of time, leading to a sort of blind-spot,” Sathe explained. “This chip enables uninterrupted neural recording, regardless of concurrent stimulation activity. Realizing continuous recording has been a long-standing problem in the neural engineering community that scientists and engineers have struggled with.” Sathe and Rudell are among the first to come up with a single-chip solution to this problem. Through several years of research and experimentation, they have developed a system that integrates neural recording, stimulation and signal processing for artifact cancellation all on a single chip. Their research effort remains pursuant to fully realizing a bidirectional brain-computer interface (robust, two-way communication between the brain and a neural device) that is fully integrated on a single chip. “A major advantage associated with developing prototype neural interface chips at the UW relates to the fact that we have an outstanding research environment, with the opportunity to collaborate with many world-class neuroscientists, neural engineers and clinical surgeons right here on campus. This allows us to exercise our chip in many neural interface applications,” Rudell said. “The integration of such diverse research efforts inside the CNT provides a huge advantage for our work.”

Working together to achieve a milestone

[caption id="attachment_20279" align="alignright" width="525"]A young man works on an electronic device. When he was a graduate student in Rudell’s lab, UW ECE alumnus Eric Pepin designed and developed the original on-chip neural stimulator that allows high-voltage output without damaging digital-friendly transistors. Pepin, who now works designing millimeter-wave integrated circuits at SpaceX, is also a co-author of this most recent paper from Rudell and Sathe’s labs.[/caption] Complex research and achievements such as this one are usually the result of teams of people working tirelessly together over years. This accomplishment is no exception. Key to Rudell and Sathe’s success were the graduate students who worked alongside them and collaboration with Perlmutter’s lab. Also important to their success was feedback from CNT industry affiliate Medtronic, as well as CNT members Eberhard Fetz, Chet Moritz, Amy Orsborn and Azadeh Yazdan. Their input was crucial to guiding development of the chip and keeping the research team aware of considerations that would come up when translating this research from the lab to experiments in living tissue, to patients in the real world. “Medtronic’s contribution was critical and went well beyond providing funding support to the project,” Sathe said. “They provided valuable guidance by helping us appreciate a number of system requirements that implantable interfaces must meet before they can be used beyond a research lab setting. They were flexible in their approach, allowing the scope and direction of the work to be determined primarily by the research findings during the course of the project.” Next steps for Sathe and Rudell involve further addressing the problems involved with bringing this technology into the real world, such as integrating wireless power and data transfer on the same tiny chip with neural recording and stimulation. They also plan to scale down the chip size to make it more than 10 times smaller than the current version. Their prototype chip is currently at Medtronic, undergoing rigorous testing to help ensure that the technology will be safe and reliable when it is someday implanted in a patient for clinical trials. And they are working methodically toward that end goal. “This paper, like the ones preceding it, is part of a longer-term effort within our groups to address key barriers to implantable closed-loop neural interfaces one at a time, building upon our prior work each step of the way,” Sathe said. “Evaluating the practical applicability of the technology with our neuroscience and industry collaborators is central to realizing interfaces that are robust, scalable and ultimately useful.” For more information about this research work, contact Chris Rudell or Visvesh Sathe. [post_title] => Engineers design a tiny, implantable chip to deepen understanding of the brain and enable better treatments for neurological disorders [post_excerpt] => [post_status] => publish [comment_status] => closed [ping_status] => closed [post_password] => [post_name] => tinychip [to_ping] => [pinged] => [post_modified] => 2020-10-16 15:14:40 [post_modified_gmt] => 2020-10-16 22:14:40 [post_content_filtered] => [post_parent] => 0 [guid] => https://www.ece.uw.edu/?post_type=spotlight&p=20271 [menu_order] => 4 [post_type] => spotlight [post_mime_type] => [comment_count] => 0 [filter] => raw ) [4] => WP_Post Object ( [ID] => 20171 [post_author] => 27 [post_date] => 2020-09-30 15:45:13 [post_date_gmt] => 2020-09-30 22:45:13 [post_content] => Story by Wayne Gillam | UW ECE News [caption id="attachment_20190" align="alignright" width="600"]Headshots in a graphic illustration of Mo Li, Arka Majumdar and Karl Böhringer UW ECE professors Mo Li, Arka Majumdar and Karl Böhringer are leading a multidisciplinary, multi-institutional research team that is working toward dramatically increasing the capacity of quantum computing systems to retain and process information. Quantum computing holds the potential to spur significant breakthroughs in science and engineering, as well as improve many aspects of modern life. Scaling-up the technology for practical applications is one of the field’s greatest challenges, and the UW ECE-led team stands to make a significant contribution toward addressing this issue. Photo illustration by Ryan Hoover[/caption] Quantum computing is creating new ways to approach complex, data-intensive problems, and it holds the potential to spur significant breakthroughs in science and engineering. Improvements to drug development, online security, financial modeling, battery technology, traffic optimization, and even better weather forecasting could all be made possible by quantum computing systems. However, scaling-up the computing capacity of quantum systems to a level that would be useful across a wide range of applications is one of the field’s greatest challenges. A multidisciplinary research team at the University of Washington Department of Electrical & Computer Engineering (UW ECE) is collaborating with a Bay Area startup, Atom Computing, and the University of Illinois to help solve this problem and to enhance the quantum workforce. The team, led by UW ECE professors Mo Li, Arka Majumdar and Karl Böhringer, recently received a new $800,000 National Science Foundation (NSF) Convergence Accelerator grant to greatly increase the capacity of quantum computing systems to retain and process information. To achieve this goal, the UW ECE-led team will develop a chip-scale, acousto-optic multi-beam steering system that will enable a dramatic scale-up of cold-atom quantum computing systems to greater than 1,000 qubits. It will be quite an accomplishment when fully realized, given that the world’s largest quantum computer is still well under 100 qubits. Launched in 2019, the NSF Convergence Accelerator program was created to accelerate basic research and discovery aligning with the NSF’s 10 “Big Ideas.” The program’s main focus is to make timely investments to solve high-risk societal challenges through use-inspired convergence research (multidisciplinary research driven by its intended application), ultimately delivering tangible solutions to improve the lives of millions of people. In 2020, the NSF continues to invest in two transformative research areas of national importance — quantum technology and artificial intelligence (AI) — to ensure that technological advancements in these areas have a positive impact on society. “The quantum technology and AI-driven data and model sharing topics were chosen based on community input and identified federal research and development priorities,” said Douglas Maughan, head of the NSF Convergence Accelerator program. “This is the program’s second cohort, and we are excited for these teams to use convergence research and innovation-centric fundamentals to accelerate solutions that have a positive societal impact.” The research team has the interdisciplinary expertise needed in integrated photonics, miniature diffractive optics, and microelectromechanical systems (MEMS) to realize a promising scheme of quantum computing. Li is confident that his team will achieve a high level of impact. Beyond quantum computing, the beam steering technology that the team is developing may also find revolutionary applications in remote sensing, autonomous navigation and virtual reality. “Quantum technology has entered the 2.0 stage,” Li said. “A critical effort is to employ a hybrid of technologies to increase the number of qubits and realize a scheme of system-level integration for quantum computing and simulation.” Böhringer added, “I am excited to work with this team to apply MEMS technology toward miniaturized, scalable quantum computing systems. The long-term investments that the NSF has made in the National Nanotechnology Coordinated Infrastructure and its predecessor programs are an invaluable resource for this project.” Over the next nine months, the UW ECE-led team will work to build a proof-of-concept for their solution by leveraging multidisciplinary expertise; NSF Convergence Accelerator innovation processes such as human-centered design, team science, pitch preparation and presentation coaching; and crosscutting partnerships between academia, non-profits, government and industry. The UW ECE team is among a cohort of 29 teams who will participate in a pitch competition and proposal evaluation to move into phase two of the program. If successful, the team will be eligible for additional funding — up to $5 million for a period of 24 months to further develop prototyping and build a sustainability model to continue impact beyond NSF support. After completing the entire program, the team plans to distribute its new optical beam steering technology by manufacturing devices at scale in an industrial foundry and delivering them to a broad user base nationwide. Learn more about this UW ECE-led research project and the NSF Convergence Accelerator program on the NSF website. [post_title] => UW ECE team receives $800K award from the National Science Foundation to help increase capacity of quantum computing systems [post_excerpt] => [post_status] => publish [comment_status] => closed [ping_status] => closed [post_password] => [post_name] => nsf2020-quantum [to_ping] => [pinged] => [post_modified] => 2020-10-16 15:50:54 [post_modified_gmt] => 2020-10-16 22:50:54 [post_content_filtered] => [post_parent] => 0 [guid] => https://www.ece.uw.edu/?post_type=spotlight&p=20171 [menu_order] => 5 [post_type] => spotlight [post_mime_type] => [comment_count] => 0 [filter] => raw ) [5] => WP_Post Object ( [ID] => 20093 [post_author] => 25 [post_date] => 2020-09-23 17:16:18 [post_date_gmt] => 2020-09-24 00:16:18 [post_content] => [caption id="attachment_20110" align="alignright" width="590"] UW ECE Keith and Nancy Rattie Endowed Career Development Professor
Baosen Zhang. Photo illustration by Ryan Hoover[/caption] In a paper published on the preprint server Arxiv.org, researchers at Microsoft and the University of Washington, including Keith and Nancy Rattie Endowed Career Development Professor Baosen Zhang, propose an AI system that uses smartphone location data to forecast electrical load. They say their architecture, which takes into account data from geographical regions both within the U.S. and Europe, can outperform conventional forecasting methods by more than three times. The pandemic shows no sign of abating, and it’s made a striking impact on the global electrical grid. Stay-at-home orders and social distancing meant to slow the outbreak of COVID-19 have resulted in major shifts in load patterns and peak demands. Italy saw a 25% reduction in demand during its country-wide lockdown, and in the U.S., overall power consumption has fallen to a 16-year low. Typical power forecasting algorithms consider weather, timing information, and previous consumption levels in their predictions, but the paper’s coauthors claim those techniques can’t capture the large and sudden shifts caused by the pandemic. That’s because they take for granted that similar days at similar times of the year observe similar load patterns, an assumption the crisis fundamentally changes — there aren’t any historically similar events. [caption id="attachment_20094" align="alignleft" width="582"] Above: Load forecast results on Seattle City Light data set. Mobi_MTL is the best-performing of the researchers’ AI models.[/caption] In the proposed model, mobility data serves as a proxy for economic activities. (The researchers assert that population-level mobility data — for instance, transit and shopping trends — can show how people change their behaviors once distancing mandates are implemented.) A transfer learning scheme enables knowledge-sharing among regions to reflect the phases at which countries around the world (and cities in the U.S.) return to work. The AI model performs day-ahead forecasts given smartphone mobility data, weather data and other variables. To address the challenges of limited data availability (since the start of the pandemic) and robustness to changes like relaxed self-quarantine measures, the researchers employed a multi-task learning framework comprising models co-trained for a set of prediction tasks with corresponding data sets. Together, these models learned the regional differences in electricity consumption and the effects of COVID-19 mitigation efforts, and they enabled knowledge transfer so that forecasts remained accurate even in the presence of unseen data for a particular location. [caption id="attachment_20095" align="alignleft" width="1125"] Above: Simulation results for day-ahead load forecasts.[/caption] To train the system, the researchers collected mobility information from Google’s and Apple’s anonymized COVID-19 community reports, in addition to publicly available hourly country-, zonal-, and metropolitan-level electricity consumption data. They combined them to create a corpus covering February 15 to May 15, which spanned pre- and post-lockdown periods in all areas of interest. The researchers report that in simulation experiments, their best model improved over baselines that didn’t incorporate mobility data, particularly for U.S. metropolitan areas. For instance, in the Seattle City Light service region for the two weeks between May 2 to May 15, the baseline model had a day-ahead forecast error rate of 15.01% (much larger than the typical 2% to 4% before the pandemic) compared with the proposed model’s error rate of 2.28%. Indeed, the proposed model was 3.98 times more performant than the baselines across all benchmarks. [caption id="attachment_20096" align="alignleft" width="407"] Above: Load projections for January 2021 and July 2020 based on Seattle weather profiles from the previous year, considering scenarios of mobility patterns.[/caption] In a separate experiment, the team used their model to plot out load curves far in advance of the start of the pandemic. After concatenating estimated mobility features along with weather data from weeks in July 2019 and January 2020, they calculated possible load scenarios in the Seattle area during July 2020 and January 2021 and found that the model’s output showed a relationship between reduced mobility and load. “We can see the decreases of mobility indexes poses more reductions of winter load, with a peak load reduction of over 300MW if current mobility patterns persist,” the coauthors wrote. “By explicitly incorporating mobility patterns, our approach can greatly reduce the error between forecasts and actual loads … As the global pandemic may still pose impacts to the power grids in the future, we think techniques developed in the paper could inform grid operators possible future load patterns.” The team's paper is currently under review at Nature Energy.
Story Adapted from |   VentureBeat [post_title] => AI model uses smartphone location data to predict power grid usage [post_excerpt] => [post_status] => publish [comment_status] => closed [ping_status] => closed [post_password] => [post_name] => ai-powergrid [to_ping] => [pinged] => [post_modified] => 2020-10-16 15:49:37 [post_modified_gmt] => 2020-10-16 22:49:37 [post_content_filtered] => [post_parent] => 0 [guid] => https://www.ece.uw.edu/?post_type=spotlight&p=20093 [menu_order] => 6 [post_type] => spotlight [post_mime_type] => [comment_count] => 0 [filter] => raw ) ) [_numposts:protected] => 6 [_rendered:protected] => 1 [_classes:protected] => Array ( [0] => view-block [1] => block--spotlight-robust-news ) [_finalHTML:protected] =>
https://www.ece.uw.edu/spotlight/mooncharging/
https://www.ece.uw.edu/spotlight/iyer-murderhornets/
https://www.ece.uw.edu/spotlight/qist-faculty-search/
https://www.ece.uw.edu/spotlight/tinychip/
https://www.ece.uw.edu/spotlight/nsf2020-quantum/
https://www.ece.uw.edu/spotlight/ai-powergrid/
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(University of Washington)[/caption] One challenge to life in space is power: how to keep humans cozy and robots working when there are no built-in power outlets and when solar power is not always an option. Now a team of organizations — led by the space technology company Astrobotic and including the University of Washington and the UW Department of Electrical & Computer Engineering (UW ECE) spinout WiBotic — has received a $5.8 million contract to develop a line of lightweight, ultrafast wireless chargers that could help both humans and robots live and work on the moon. This contract is part of the NASA Tipping Point call for proposals. Though prototypes for wireless charging have existed since 2011, this new magnetic resonance-based power supply system would be the first of its kind in space. Wireless charging in space comes with its own set of issues, such as how to keep the metallic iron in moon dust — or lunar regolith — from interfering with charging connections. The UW has received $440,000 from this contract to study how lunar regolith affects wireless power transfer. “Moon dust is very fine and tends to stick to surfaces because it gets electrically charged. The UW team is tackling the fundamental research question of how dust particle size and composition affects power transfer efficiency,” said UW lead researcher Joshua Smith, a professor in both the Paul G. Allen School of Computer Science & Engineering and UW ECE. “We plan to take an approach that is a hybrid of science and engineering: We will develop a synthetic moon dust that is consistent with known relevant properties, but that represents the worst case for our wireless power transfer system. [caption id="attachment_20448" align="alignright" width="315"] Joshua R. Smith, a UW professor in both ECE and CSE, will be UW's lead researcher for understanding how moon dust particle size and composition affect power transfer efficiency. (photo by Tara Gimmer)[/caption] “Our work will be the basis of the engineering requirements for the rest of the team. It will help us answer questions such as: how much extra power should be transferred to overcome the expected losses to heat? Or how much cooling capacity needs to be built into the system to get rid of that heat produced in the moon dust?” Astrobotic’s CubeRover, which was developed in collaboration with the NASA Kennedy Space Center, is the first space technology that will be integrated with the wireless charging system. Part of NASA’s Tipping Point contract will fund the development of CubeRover’s intelligent autonomous navigation system, which will enable precise navigation where GPS is not an option. This will equip the CubeRover — and other planetary roving technologies — to find charging docks to power up again and again, and survive the 14-day lunar night. Astrobotic will space-qualify the entire system, test engineering and flight models, and lead integration of CubeRover and the multi-kilowatt, ultrafast wireless charging system, designed by WiBotic. WiBotic will also provide engineering, mechanical and electrical design support. [caption id="attachment_20443" align="alignleft" width="347"] A team of multiple organizations, including the UW and UW ECE spinout Wibotic, plans to develop a line of lightweight, ultrafast wireless chargers that could help both humans and robots live and work on the moon. (Sarah McQuate/University of Washington)[/caption] “These rovers need easy and reliable access to power in an environment that includes extremely abrasive dust and severe temperatures, making this a perfect application for WiBotic’s innovative non-contact proximity charging solutions,” says Ben Waters, UW ECE alum and WiBotic CEO. “We’re looking forward to working with Astrobotic and the team to deliver flexible and durable charging stations that provide power to a range of manned and unmanned lunar vehicles.” This wireless charging technology could have considerable utility not only on the moon, but also in critical space applications on Mars, in orbit and beyond. Future teams will be able to scale the wireless technology to diverse assets like lunar vehicles, power tools, flying systems and more. The base station, power receiver and CubeRover flight units will be delivered to NASA for inclusion into an upcoming lunar mission via the Commercial Lunar Payload Services program in 2023. 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[caption id="" align="alignright" width="311"]Vikram Iyer. Photo by Mark Stone/University of Washington. Vikram Iyer working with bees at the University of Washington. Photo by Mark Stone/UW Photo[/caption]
If tracking “murder hornets” sounds more like a job for an entomologist/detective, you might be surprised by this member of the hornet-tracking team: a Ph.D. candidate at the University of Washington's Department of Electrical and Computer Engineering (UW ECE) named Vikram Iyer. One of his most recent endeavors was collaborating with entomologists to track Asian hornets (also called “murder hornets”), which have been spotted in Washington state. According to Washington State Department of Agriculture (WSDA), these hornets, which are originally from certain parts of Asia including Japan, South Korea, and China, are dangerous and efficient killers of bees. In a mere few hours, just a few Asian hornets can attack and slaughter an entire colony by decapitating the bees and taking over their hives. The WSDA warns that these hornets pose an immeasurable threat, and if they are not held in check and eradicated, they have the potential to damage the environment, economy, and public health. “We heard about this issue with the murder hornets and thought, ‘We have the technology that could potentially be helpful with this problem,’” Iyer says. He contacted WSDA and explained that they have little wireless transmitters that could be used to tag a hornet and then track it back to its nest. “The past few years, I’ve done a series of projects where we’ve been developing small electronics, things like little wireless sensors that are small enough to ride on the back of live insects,” says Iyer. His portfolio includes putting a sensor on a live bumblebee, a camera on the back of a live beetle (which was published in a July 2020 study in ScienceRobotics), and mounting sensors on moths that can be dropped at specific targets. Iyer notes that this experience was handy as the Asian hornet species nests underground, which makes it that much harder to locate them. Efforts in other countries to track them are often unsuccessful. “We started thinking about how we can use a small radio tag to actually follow the insect,” Iyer says. Their device has a battery, radio chip, antenna, and temperature sensor, and it sends out a Bluetooth signal about two times per second.
“We heard about this issue with the murder hornets and thought, ‘We have the technology that could potentially be helpful with this problem,’” Iyer says.
So far, WSDA has been able to identify two hotspots of activity near the Canadian border using a network of traps they set up. Then, when they caught a live hornet, Iyer went to where the WSDA entomologists were and helped them put the tracking devices on the insect. While Iyer has put devices on other insects such as bees and beetles himself for his previous projects, he left this one up to the insect experts: These murder hornets are not just dangerous for bees — they have extra-long stingers that they can use repeatedly and can squirt a caustic venom. Using a little noose made from dental floss and glue, the lead WSDA entomologist attached Iyer’s device onto the hornet after putting the hornet on ice to sedate it. Then they let it go. “We were able to follow it for about a quarter of a mile on our first attempt,” says Iyer. After flying for some time up in the trees, the hornet came down closer toward the ground and stopped for a while in a big patch of blackberries, where the team thought the nest might be. Unfortunately, it flew away at some point and they ended up losing the signal as it went further into the woods. [caption id="attachment_20400" align="alignleft" width="468"]Vikram Iyer Vikram Iyer investigates how a bumblebee (inside the container) performs with the sensor package attached to its back. Photo by Mark Stone/UW Photo[/caption] As of now, there are more hornets still at large, but with Iyer’s tech in the field, scientists have a much better shot at finding the nests. “This confirms that our tracking devices work, that this general approach works,” Iyer says. “It also points us in the same direction as a number of other sightings that are all kind of clustered around the same patch of woods pointing in one direction.” A 2020 recipient of The Marconi Society Paul Baran Young Scholars award, Iyer was recognized for his research focusing on different kinds of wireless technologies, including bio-inspired and bio-integrative wireless sensor systems, for communication, wireless power delivery, data collection, and more. Iyer has also been working on a project where a live insect or a small drone can carry some sort of sensor and then drop it at a location that is hard-to-reach or dangerous, like a volcano or for forest fire monitoring. In addition to his UW projects and applying for faculty positions, Iyer is also working with researchers at Microsoft on an air quality monitoring platform for cities that uses gas sensors to monitor air quality on a more granular scale. “I’m inspired by natural systems to design things, and my most recent works have been trying to augment them and leverage the capabilities of live animals to complement what we can engineer,” says Iyer. “That’s something that I’m interested in exploring.”
Story by Katherine Lee |  AAAS [post_title] => UW ECE doctoral student Vikram Iyer featured in AAAS for murder hornet tracking; finding ways to meld nature and science [post_excerpt] => [post_status] => publish [comment_status] => closed [ping_status] => closed [post_password] => [post_name] => iyer-murderhornets [to_ping] => [pinged] => [post_modified] => 2020-11-09 10:02:18 [post_modified_gmt] => 2020-11-09 18:02:18 [post_content_filtered] => [post_parent] => 0 [guid] => https://www.ece.uw.edu/?post_type=spotlight&p=20378 [menu_order] => 2 [post_type] => spotlight [post_mime_type] => [comment_count] => 0 [filter] => raw ) [2] => WP_Post Object ( [ID] => 20340 [post_author] => 26 [post_date] => 2020-11-03 13:15:24 [post_date_gmt] => 2020-11-03 21:15:24 [post_content] => Quantum Information Science & Technology Now accepting applications for two tenure track faculty positions   The University of Washington Department of Electrical & Computer Engineering (UW ECE) invites applications for two full-time, tenure-track faculty positions at the rank of assistant professor. Candidates making connections between QIST and data science, circuits, devices, controls, computer engineering, information theory and other existing efforts in the ECE department are particularly encouraged to apply, but all areas of QIST will be considered. The positions are multi-year appointments with 9-month service periods with an anticipated start date of September 1, 2021. Applications must be submitted by December 1, 2020 to receive full consideration. UW ECE offers an innovative, collaborative and inclusive environment in which our faculty and students succeed at finding impactful solutions to today’s challenges. The Seattle area is particularly attractive given the presence of significant industrial research laboratories, top technology companies, as well as a vibrant technology-driven entrepreneurial community that further enhances the intellectual atmosphere. We look forward to learning how the applicant's experience or future plans for teaching, research and service would support our commitment to diversity and inclusion. Qualifications Applicants for tenure-track and tenure-eligible positions must have earned a doctorate (or foreign equivalent) in electrical engineering, computer engineering, applied physics or related field by the date of appointment. View UW ECE QIST flyerLearn more and apply via Interfolio >
The new UW ECE positions are supported by a UW College of Engineering (COE) cluster hiring initiative in QIST, which also includes a new faculty hire in the UW Department of Mechanical Engineering (ME), while new Paul G. Allen School of Computer Science and Engineering (CSE) hires in QIST will be closely aligned with UW’s community of QIST researchers. “Our vision is for UW to have expertise across the full quantum stack,” said Kai-Mei Fu, UW associate professor of electrical and computer engineering (ECE) and physics and co-chair of UW’s interdisciplinary QuantumX Initiative. “Our future colleagues in ECE, ME, and CSE will help UW address the key QIST engineering challenges of performance and scalability. We want to help develop a Quantum Silicon Valley in the Pacific Northwest, and we want UW to be the #1 place in the world for students to come and build their skills in QIST.” [post_title] => UW ECE seeks outstanding faculty candidates in quantum information science & technology [post_excerpt] => [post_status] => publish [comment_status] => closed [ping_status] => closed [post_password] => [post_name] => qist-faculty-search [to_ping] => [pinged] => [post_modified] => 2020-11-03 13:23:35 [post_modified_gmt] => 2020-11-03 21:23:35 [post_content_filtered] => [post_parent] => 0 [guid] => https://www.ece.uw.edu/?post_type=spotlight&p=20340 [menu_order] => 3 [post_type] => spotlight [post_mime_type] => [comment_count] => 0 [filter] => raw ) [3] => WP_Post Object ( [ID] => 20271 [post_author] => 27 [post_date] => 2020-10-16 15:14:40 [post_date_gmt] => 2020-10-16 22:14:40 [post_content] => Story by Wayne Gillam | UW ECE News [caption id="attachment_20273" align="alignright" width="625"]Headshots of Chris Rudell and Visvesh Sathe UW ECE associate professors Chris Rudell (left) and Visvesh Sathe (right) led the research team that developed this implantable chip, which will help neuroscientists deepen our understanding of the brain and enable better treatments for a wide range of medical conditions and disorders. Photo illustration by Ryan Hoover[/caption] Chris Rudell and Vivesh Sathe have vision. Together, with graduate students in their labs at the University of Washington Department of Electrical & Computer Engineering (UW ECE), they have designed a sophisticated neural interface in the form of a small, implantable chip. This chip is designed to help neuroscientists deepen their understanding of the brain and promises to take engineers one step closer to developing more effective devices to treat neurological disorders and conditions such as Parkinson’s disease, epilepsy, depression and obsessive-compulsive disorder. Looking ahead, they developed the chip to be scalable and translatable into future technologies for decades to come. “This chip is tiny. It is two by two millimeters, and it has pure, unrefined electrical engineering at its core,” said Rudell, a UW ECE associate professor and member of the Center for Neurotechnology (CNT). “That’s what Visvesh and I are working toward, developing techniques that are more broadly applicable, that are geared toward translation into high-volume production by our industry partners. In addition, the circuits in this chip could be used in future generations of semiconductor technology, eventually becoming smaller and smaller as these silicon technologies begin to feature sub-nanometer dimensions.” “This work represents the promise of realizing a technology that will improve our understanding of how circuits in the brain are connected, furthering neuroscience’s understanding of neural plasticity [the brain’s ability to adapt and change over time],” added Sathe, who is a UW ECE associate professor and also a CNT member.

Big steps forward

[caption id="attachment_20277" align="alignright" width="525"]Two young men working on an electronic device UW ECE alumnus John Uehlin (left) in a 2016 photo taken in Rudell’s lab with Joshua Chen, a CNT Research Experience for Undergraduates summer program participant. Uehlin worked on an early version of the chip prototype when he was a graduate student. He is also lead author of the most recent paper from Rudell and Sathe’s labs that describes the current version of the chip. Chen is now a Ph.D. candidate at Rice University.[/caption] Rudell and Sathe are senior authors of a new paper in the IEEE Journal of Solid-State Circuits, written by Rudell’s graduate student John Uehlin. The paper describes research that is the culmination of several years of work and contributions by UW ECE graduate students such as William Anthony Smith, Venkata Rajesh Pamula, Eric Pepin and Daniel Michelliti, as well as CNT member Steve Perlmutter. The article describes in detail the chip’s functions as they apply to a neural interface, allowing electrical signals to pass back and forth between the brain and the device. A key step forward in this design is the effectiveness of the chip at performing signal-noise cancellation, which allows neurons in the brain to be electrically stimulated while simultaneously recording their response. This noise, or “artifact” cancellation becomes increasingly difficult to accomplish the smaller the chip size. Neural stimulation generally requires high voltage levels that are much too high for tiny, semiconductor technologies conducive to digital circuits. Rudell and Sathe addressed this problem by stacking circuits in a way that delivers the desired electrical stimulation current without damaging the chip. “That was what we worked on in our group for about five years, figuring out techniques to practically achieve high voltage output without hurting the transistors and substantially improving long-term reliability, which is key for devices planted in the body,” Rudell said. “We are trying to focus on semiconductor technologies at least a decade in the future, when we can make a chip similar to this one, so small that it becomes comparable in size to a grain of rice.” [caption id="attachment_20282" align="alignleft" width="300"]web_Micrograph of the fabricated 65-nm test chip Rudell and Sathe’s research team has developed a chip for neural interfaces that integrates neural recording, stimulation and signal processing for artifact cancellation all on a single device, using a 65-nanometer (nm) silicon technology. Next steps for the team includes integrating wireless power and data transfer on the same, tiny chip. Pictured above is a micrograph of the fabricated 65-nm test chip.[/caption] This, along with work by Sathe to improve artifact cancellation capabilities, allows for “low-latency neural circuit analysis” — the ability to identify and monitor short connections between neurons. This new capability will allow neuroscientists to read signals from the brain that they previously weren’t able to before because of the amount of signal interference caused by neural stimulation artifacts. “Analyzing low-latency neural connectivity has traditionally been difficult because of stimulation artifacts. These large, spurious signals can corrupt and even disable neural recording altogether for a brief period of time, leading to a sort of blind-spot,” Sathe explained. “This chip enables uninterrupted neural recording, regardless of concurrent stimulation activity. Realizing continuous recording has been a long-standing problem in the neural engineering community that scientists and engineers have struggled with.” Sathe and Rudell are among the first to come up with a single-chip solution to this problem. Through several years of research and experimentation, they have developed a system that integrates neural recording, stimulation and signal processing for artifact cancellation all on a single chip. Their research effort remains pursuant to fully realizing a bidirectional brain-computer interface (robust, two-way communication between the brain and a neural device) that is fully integrated on a single chip. “A major advantage associated with developing prototype neural interface chips at the UW relates to the fact that we have an outstanding research environment, with the opportunity to collaborate with many world-class neuroscientists, neural engineers and clinical surgeons right here on campus. This allows us to exercise our chip in many neural interface applications,” Rudell said. “The integration of such diverse research efforts inside the CNT provides a huge advantage for our work.”

Working together to achieve a milestone

[caption id="attachment_20279" align="alignright" width="525"]A young man works on an electronic device. When he was a graduate student in Rudell’s lab, UW ECE alumnus Eric Pepin designed and developed the original on-chip neural stimulator that allows high-voltage output without damaging digital-friendly transistors. Pepin, who now works designing millimeter-wave integrated circuits at SpaceX, is also a co-author of this most recent paper from Rudell and Sathe’s labs.[/caption] Complex research and achievements such as this one are usually the result of teams of people working tirelessly together over years. This accomplishment is no exception. Key to Rudell and Sathe’s success were the graduate students who worked alongside them and collaboration with Perlmutter’s lab. Also important to their success was feedback from CNT industry affiliate Medtronic, as well as CNT members Eberhard Fetz, Chet Moritz, Amy Orsborn and Azadeh Yazdan. Their input was crucial to guiding development of the chip and keeping the research team aware of considerations that would come up when translating this research from the lab to experiments in living tissue, to patients in the real world. “Medtronic’s contribution was critical and went well beyond providing funding support to the project,” Sathe said. “They provided valuable guidance by helping us appreciate a number of system requirements that implantable interfaces must meet before they can be used beyond a research lab setting. They were flexible in their approach, allowing the scope and direction of the work to be determined primarily by the research findings during the course of the project.” Next steps for Sathe and Rudell involve further addressing the problems involved with bringing this technology into the real world, such as integrating wireless power and data transfer on the same tiny chip with neural recording and stimulation. They also plan to scale down the chip size to make it more than 10 times smaller than the current version. Their prototype chip is currently at Medtronic, undergoing rigorous testing to help ensure that the technology will be safe and reliable when it is someday implanted in a patient for clinical trials. And they are working methodically toward that end goal. “This paper, like the ones preceding it, is part of a longer-term effort within our groups to address key barriers to implantable closed-loop neural interfaces one at a time, building upon our prior work each step of the way,” Sathe said. “Evaluating the practical applicability of the technology with our neuroscience and industry collaborators is central to realizing interfaces that are robust, scalable and ultimately useful.” For more information about this research work, contact Chris Rudell or Visvesh Sathe. [post_title] => Engineers design a tiny, implantable chip to deepen understanding of the brain and enable better treatments for neurological disorders [post_excerpt] => [post_status] => publish [comment_status] => closed [ping_status] => closed [post_password] => [post_name] => tinychip [to_ping] => [pinged] => [post_modified] => 2020-10-16 15:14:40 [post_modified_gmt] => 2020-10-16 22:14:40 [post_content_filtered] => [post_parent] => 0 [guid] => https://www.ece.uw.edu/?post_type=spotlight&p=20271 [menu_order] => 4 [post_type] => spotlight [post_mime_type] => [comment_count] => 0 [filter] => raw ) [4] => WP_Post Object ( [ID] => 20171 [post_author] => 27 [post_date] => 2020-09-30 15:45:13 [post_date_gmt] => 2020-09-30 22:45:13 [post_content] => Story by Wayne Gillam | UW ECE News [caption id="attachment_20190" align="alignright" width="600"]Headshots in a graphic illustration of Mo Li, Arka Majumdar and Karl Böhringer UW ECE professors Mo Li, Arka Majumdar and Karl Böhringer are leading a multidisciplinary, multi-institutional research team that is working toward dramatically increasing the capacity of quantum computing systems to retain and process information. Quantum computing holds the potential to spur significant breakthroughs in science and engineering, as well as improve many aspects of modern life. Scaling-up the technology for practical applications is one of the field’s greatest challenges, and the UW ECE-led team stands to make a significant contribution toward addressing this issue. Photo illustration by Ryan Hoover[/caption] Quantum computing is creating new ways to approach complex, data-intensive problems, and it holds the potential to spur significant breakthroughs in science and engineering. Improvements to drug development, online security, financial modeling, battery technology, traffic optimization, and even better weather forecasting could all be made possible by quantum computing systems. However, scaling-up the computing capacity of quantum systems to a level that would be useful across a wide range of applications is one of the field’s greatest challenges. A multidisciplinary research team at the University of Washington Department of Electrical & Computer Engineering (UW ECE) is collaborating with a Bay Area startup, Atom Computing, and the University of Illinois to help solve this problem and to enhance the quantum workforce. The team, led by UW ECE professors Mo Li, Arka Majumdar and Karl Böhringer, recently received a new $800,000 National Science Foundation (NSF) Convergence Accelerator grant to greatly increase the capacity of quantum computing systems to retain and process information. To achieve this goal, the UW ECE-led team will develop a chip-scale, acousto-optic multi-beam steering system that will enable a dramatic scale-up of cold-atom quantum computing systems to greater than 1,000 qubits. It will be quite an accomplishment when fully realized, given that the world’s largest quantum computer is still well under 100 qubits. Launched in 2019, the NSF Convergence Accelerator program was created to accelerate basic research and discovery aligning with the NSF’s 10 “Big Ideas.” The program’s main focus is to make timely investments to solve high-risk societal challenges through use-inspired convergence research (multidisciplinary research driven by its intended application), ultimately delivering tangible solutions to improve the lives of millions of people. In 2020, the NSF continues to invest in two transformative research areas of national importance — quantum technology and artificial intelligence (AI) — to ensure that technological advancements in these areas have a positive impact on society. “The quantum technology and AI-driven data and model sharing topics were chosen based on community input and identified federal research and development priorities,” said Douglas Maughan, head of the NSF Convergence Accelerator program. “This is the program’s second cohort, and we are excited for these teams to use convergence research and innovation-centric fundamentals to accelerate solutions that have a positive societal impact.” The research team has the interdisciplinary expertise needed in integrated photonics, miniature diffractive optics, and microelectromechanical systems (MEMS) to realize a promising scheme of quantum computing. Li is confident that his team will achieve a high level of impact. Beyond quantum computing, the beam steering technology that the team is developing may also find revolutionary applications in remote sensing, autonomous navigation and virtual reality. “Quantum technology has entered the 2.0 stage,” Li said. “A critical effort is to employ a hybrid of technologies to increase the number of qubits and realize a scheme of system-level integration for quantum computing and simulation.” Böhringer added, “I am excited to work with this team to apply MEMS technology toward miniaturized, scalable quantum computing systems. The long-term investments that the NSF has made in the National Nanotechnology Coordinated Infrastructure and its predecessor programs are an invaluable resource for this project.” Over the next nine months, the UW ECE-led team will work to build a proof-of-concept for their solution by leveraging multidisciplinary expertise; NSF Convergence Accelerator innovation processes such as human-centered design, team science, pitch preparation and presentation coaching; and crosscutting partnerships between academia, non-profits, government and industry. The UW ECE team is among a cohort of 29 teams who will participate in a pitch competition and proposal evaluation to move into phase two of the program. If successful, the team will be eligible for additional funding — up to $5 million for a period of 24 months to further develop prototyping and build a sustainability model to continue impact beyond NSF support. After completing the entire program, the team plans to distribute its new optical beam steering technology by manufacturing devices at scale in an industrial foundry and delivering them to a broad user base nationwide. Learn more about this UW ECE-led research project and the NSF Convergence Accelerator program on the NSF website. [post_title] => UW ECE team receives $800K award from the National Science Foundation to help increase capacity of quantum computing systems [post_excerpt] => [post_status] => publish [comment_status] => closed [ping_status] => closed [post_password] => [post_name] => nsf2020-quantum [to_ping] => [pinged] => [post_modified] => 2020-10-16 15:50:54 [post_modified_gmt] => 2020-10-16 22:50:54 [post_content_filtered] => [post_parent] => 0 [guid] => https://www.ece.uw.edu/?post_type=spotlight&p=20171 [menu_order] => 5 [post_type] => spotlight [post_mime_type] => [comment_count] => 0 [filter] => raw ) [5] => WP_Post Object ( [ID] => 20093 [post_author] => 25 [post_date] => 2020-09-23 17:16:18 [post_date_gmt] => 2020-09-24 00:16:18 [post_content] => [caption id="attachment_20110" align="alignright" width="590"] UW ECE Keith and Nancy Rattie Endowed Career Development Professor
Baosen Zhang. Photo illustration by Ryan Hoover[/caption] In a paper published on the preprint server Arxiv.org, researchers at Microsoft and the University of Washington, including Keith and Nancy Rattie Endowed Career Development Professor Baosen Zhang, propose an AI system that uses smartphone location data to forecast electrical load. They say their architecture, which takes into account data from geographical regions both within the U.S. and Europe, can outperform conventional forecasting methods by more than three times. The pandemic shows no sign of abating, and it’s made a striking impact on the global electrical grid. Stay-at-home orders and social distancing meant to slow the outbreak of COVID-19 have resulted in major shifts in load patterns and peak demands. Italy saw a 25% reduction in demand during its country-wide lockdown, and in the U.S., overall power consumption has fallen to a 16-year low. Typical power forecasting algorithms consider weather, timing information, and previous consumption levels in their predictions, but the paper’s coauthors claim those techniques can’t capture the large and sudden shifts caused by the pandemic. That’s because they take for granted that similar days at similar times of the year observe similar load patterns, an assumption the crisis fundamentally changes — there aren’t any historically similar events. [caption id="attachment_20094" align="alignleft" width="582"] Above: Load forecast results on Seattle City Light data set. Mobi_MTL is the best-performing of the researchers’ AI models.[/caption] In the proposed model, mobility data serves as a proxy for economic activities. (The researchers assert that population-level mobility data — for instance, transit and shopping trends — can show how people change their behaviors once distancing mandates are implemented.) A transfer learning scheme enables knowledge-sharing among regions to reflect the phases at which countries around the world (and cities in the U.S.) return to work. The AI model performs day-ahead forecasts given smartphone mobility data, weather data and other variables. To address the challenges of limited data availability (since the start of the pandemic) and robustness to changes like relaxed self-quarantine measures, the researchers employed a multi-task learning framework comprising models co-trained for a set of prediction tasks with corresponding data sets. Together, these models learned the regional differences in electricity consumption and the effects of COVID-19 mitigation efforts, and they enabled knowledge transfer so that forecasts remained accurate even in the presence of unseen data for a particular location. [caption id="attachment_20095" align="alignleft" width="1125"] Above: Simulation results for day-ahead load forecasts.[/caption] To train the system, the researchers collected mobility information from Google’s and Apple’s anonymized COVID-19 community reports, in addition to publicly available hourly country-, zonal-, and metropolitan-level electricity consumption data. They combined them to create a corpus covering February 15 to May 15, which spanned pre- and post-lockdown periods in all areas of interest. The researchers report that in simulation experiments, their best model improved over baselines that didn’t incorporate mobility data, particularly for U.S. metropolitan areas. For instance, in the Seattle City Light service region for the two weeks between May 2 to May 15, the baseline model had a day-ahead forecast error rate of 15.01% (much larger than the typical 2% to 4% before the pandemic) compared with the proposed model’s error rate of 2.28%. Indeed, the proposed model was 3.98 times more performant than the baselines across all benchmarks. [caption id="attachment_20096" align="alignleft" width="407"] Above: Load projections for January 2021 and July 2020 based on Seattle weather profiles from the previous year, considering scenarios of mobility patterns.[/caption] In a separate experiment, the team used their model to plot out load curves far in advance of the start of the pandemic. After concatenating estimated mobility features along with weather data from weeks in July 2019 and January 2020, they calculated possible load scenarios in the Seattle area during July 2020 and January 2021 and found that the model’s output showed a relationship between reduced mobility and load. “We can see the decreases of mobility indexes poses more reductions of winter load, with a peak load reduction of over 300MW if current mobility patterns persist,” the coauthors wrote. “By explicitly incorporating mobility patterns, our approach can greatly reduce the error between forecasts and actual loads … As the global pandemic may still pose impacts to the power grids in the future, we think techniques developed in the paper could inform grid operators possible future load patterns.” The team's paper is currently under review at Nature Energy.
Story Adapted from |   VentureBeat [post_title] => AI model uses smartphone location data to predict power grid usage [post_excerpt] => [post_status] => publish [comment_status] => closed [ping_status] => closed [post_password] => [post_name] => ai-powergrid [to_ping] => [pinged] => [post_modified] => 2020-10-16 15:49:37 [post_modified_gmt] => 2020-10-16 22:49:37 [post_content_filtered] => [post_parent] => 0 [guid] => https://www.ece.uw.edu/?post_type=spotlight&p=20093 [menu_order] => 6 [post_type] => spotlight [post_mime_type] => [comment_count] => 0 [filter] => raw ) ) [post_count] => 6 [current_post] => -1 [in_the_loop] => [post] => WP_Post Object ( [ID] => 20441 [post_author] => 25 [post_date] => 2020-11-18 11:26:38 [post_date_gmt] => 2020-11-18 19:26:38 [post_content] => [caption id="attachment_20442" align="alignright" width="315"] UW ECE alum Ben Waters is co-founder and CEO of WiBotic — a UW ECE spinout and key organization involved in the contract to study wireless charging on the moon. (University of Washington)[/caption] One challenge to life in space is power: how to keep humans cozy and robots working when there are no built-in power outlets and when solar power is not always an option. Now a team of organizations — led by the space technology company Astrobotic and including the University of Washington and the UW Department of Electrical & Computer Engineering (UW ECE) spinout WiBotic — has received a $5.8 million contract to develop a line of lightweight, ultrafast wireless chargers that could help both humans and robots live and work on the moon. This contract is part of the NASA Tipping Point call for proposals. Though prototypes for wireless charging have existed since 2011, this new magnetic resonance-based power supply system would be the first of its kind in space. Wireless charging in space comes with its own set of issues, such as how to keep the metallic iron in moon dust — or lunar regolith — from interfering with charging connections. The UW has received $440,000 from this contract to study how lunar regolith affects wireless power transfer. “Moon dust is very fine and tends to stick to surfaces because it gets electrically charged. The UW team is tackling the fundamental research question of how dust particle size and composition affects power transfer efficiency,” said UW lead researcher Joshua Smith, a professor in both the Paul G. Allen School of Computer Science & Engineering and UW ECE. “We plan to take an approach that is a hybrid of science and engineering: We will develop a synthetic moon dust that is consistent with known relevant properties, but that represents the worst case for our wireless power transfer system. [caption id="attachment_20448" align="alignright" width="315"] Joshua R. Smith, a UW professor in both ECE and CSE, will be UW's lead researcher for understanding how moon dust particle size and composition affect power transfer efficiency. (photo by Tara Gimmer)[/caption] “Our work will be the basis of the engineering requirements for the rest of the team. It will help us answer questions such as: how much extra power should be transferred to overcome the expected losses to heat? Or how much cooling capacity needs to be built into the system to get rid of that heat produced in the moon dust?” Astrobotic’s CubeRover, which was developed in collaboration with the NASA Kennedy Space Center, is the first space technology that will be integrated with the wireless charging system. Part of NASA’s Tipping Point contract will fund the development of CubeRover’s intelligent autonomous navigation system, which will enable precise navigation where GPS is not an option. This will equip the CubeRover — and other planetary roving technologies — to find charging docks to power up again and again, and survive the 14-day lunar night. Astrobotic will space-qualify the entire system, test engineering and flight models, and lead integration of CubeRover and the multi-kilowatt, ultrafast wireless charging system, designed by WiBotic. WiBotic will also provide engineering, mechanical and electrical design support. [caption id="attachment_20443" align="alignleft" width="347"] A team of multiple organizations, including the UW and UW ECE spinout Wibotic, plans to develop a line of lightweight, ultrafast wireless chargers that could help both humans and robots live and work on the moon. (Sarah McQuate/University of Washington)[/caption] “These rovers need easy and reliable access to power in an environment that includes extremely abrasive dust and severe temperatures, making this a perfect application for WiBotic’s innovative non-contact proximity charging solutions,” says Ben Waters, UW ECE alum and WiBotic CEO. “We’re looking forward to working with Astrobotic and the team to deliver flexible and durable charging stations that provide power to a range of manned and unmanned lunar vehicles.” This wireless charging technology could have considerable utility not only on the moon, but also in critical space applications on Mars, in orbit and beyond. Future teams will be able to scale the wireless technology to diverse assets like lunar vehicles, power tools, flying systems and more. The base station, power receiver and CubeRover flight units will be delivered to NASA for inclusion into an upcoming lunar mission via the Commercial Lunar Payload Services program in 2023. Adapted from a release by Astrobotic. 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