Read this year's issue of The Integrator — UW ECE's flagship, annual magazine highlighting the Department's extraordinary faculty research, student achievements, alumni stories, special events and more!
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: 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
What causes a research publication to become highly cited and stand the test of time? We asked UW ECE faculty to help shed some light on this intriguing question.
Professor Eve Riskin is returning to UW ECE after 15 years as an associate dean in the UW College of Engineering. And as co-founder and faculty director of STARS, she has plans to share this successful program model with colleges and universities across the country.
UW ECE and CSE professor Shwetak Patel was recently honored by Georgia Tech and Business Insider for his contributions to low-power sensing and mobile health innovation.
Eight UW graduate students received this year’s Distinguished Dissertation and Thesis Awards. Schwock won in the category of Mathematics, Physical Sciences & Engineering for his work on analyzing and predicting ocean ambient noise.
The new three-course, graduate-level evening program is for students wanting to enhance their skills and knowledge in these exciting, cutting-edge areas.
- Karthik Mohan
- Rania Hussein
- Sreeram Kannan
- Eli Shlizerman
- Shwetak N. Patel
- Radha Poovendran
- 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