UW ECE is proud to welcome renowned computer scientist Yann LeCun, who will deliver the Department’s 2024 Lytle Lecture on Wednesday, January 24, in the HUB Lyceum.
Data Sciences are fundamentally transforming nearly every area of engineering, science, and society. The University of Washington’s Electrical & Computer Engineering faculty are making fundamental contributions to many different areas of data sciences, including machine learning, AI, optimization, information theory, computer vision, and speech and natural language processing. Many of our data sciences faculty hold secondary appointments in applied mathematics, computer science and engineering, bioengineering, and other departments, and are active participants in cross-disciplinary institutes such as UW’s eScience Institute, the Allen Institute of Artificial Intelligence and the Bloedel Hearing Research Center.
Artificial intelligence (AI), mathematical optimization and information theory.
Faculty: Lillian Ratliff, Katrin Kirchhoff, Jeffrey A. Bilmes, Les Atlas, Maryam Fazel, Sreeram Kannan, Mari Ostendorf, Ming-Ting Sun, Eli Shlizerman, Jenq-Neng Hwang, Linda Shapiro, Hannaneh Hajishirzi, Shwetak Patel, Radha Poovendran
Statistical Signal Processing
Theory, algorithms, signal processing systems and signal processing applications (i.e. biomedical, geophysical signals and synthetic signals).
Speech and Natural Language Processing
Speech recognition, natural language understanding, computational linguistics and web-based language techniques.
Computer Vision and Image Processing
Video analysis, surveillance, object recognition, activity recognition, medical image analysis and video compression
Quantum information systems, quantum algorithms for complex systems, quantum hardware
Faculty: Rahul Trivedi
Read the latest issue of The Integrator, UW ECE’s flagship, annual publication intended for alumni and friends of the Department. The magazine highlights the UW ECE community and covers stories about extraordinary students and their achievements, faculty research and discoveries, alumni news, events and more!
Graduate students in UW ECE Professor Radha Poovendran’s TinyML course are learning how to squeeze cloud-based, machine learning networks into small, resource-constrained devices.
A UW research team led by UW ECE and Physics Associate Professor Arka Majumdar has moved quantum technology development a significant step ahead, demonstrating a new kind of silicon photonic chip that could work as a solid foundation for building a quantum simulator, one with useful applications in the real world.
UW ECE Associate Professor Payman Arabshahi was recently named site director and principal investigator at the UW for this new, multi-institutional, NSF-funded Center.
Poovendran will be the UW lead for a new, multi-university institute, which is developing approaches that leverage AI to defend against cyberthreats that target the security and privacy of computer networks and their users.
- Mahmood Hameed
- Gang Hua
- Karthik Mohan
- Rahul Trivedi
- Rania Hussein
- Sreeram Kannan
- Lillian Ratliff
- Eli Shlizerman
- Shwetak N. Patel
- Radha Poovendran
- C. J. Richard Shi
- Jose Nathan Kutz
- Ming-Ting Sun
- Linda G. Shapiro
- Eve A. Riskin
- Mari Ostendorf
- Brian A. Nelson
- Katrin Kirchhoff
- Jenq-Neng Hwang
- Hannaneh Hajishirzi
- Maryam Fazel
- Jeffrey A. Bilmes
- Les Atlas
- MachinE Learning, Optimization, and Data Interpretation (MELODI) Laboratory
- Transformation, Interpretation and Analysis of Language (TIAL)
- Intelligent Systems Lab
- Graphics and Imaging Lab
- Data-Driven Dynamical Systems
- Signal, Speech and Language Interpretation Lab
- Silicon System Research Lab
- Ubicomp (Ubiquitous Computing) Research Lab
- Design, Test and Reliability Research Laboratory
- Information Processing Lab
- Information Theory Lab
- Interactive System Design Laboratory
- Digital Pathology: Accuracy, Viewing Behavior and Image Characterization (with PI: Joann Elmore at Harborview and others)
- 3D Head Reconstruction from Images or Videos (with Ira Kemmelmacher-Shlizerman in CSE)
- Expression Recognition with Deep Neural Nets (with Barbara Mones in CSE)
- Automatic Recognition of Power Line in Millimeter Wave Radar Video
- Surface Light Field Compression Using a Point Cloud Codec
- A Data-driven Point Cloud Simplification Framework for City-scale Image-based Localization
- Full-Capacity Unitary Recurrent Neural Networks
- Deep Submodular Functions: Definitions and Learning
- Exploiting Tradeoffs for Exact Recovery in Heterogeneous Stochastic Block Models
- Y-Net: Joint Segmentation and Classification Diagnosis of Breast Biopsy Images