Engineering students gathered to receive exclusive access to the Sonos API and smart speakers. These students are the first to receive this level of professional developer access. Three teams were recognized with the best projects.
Data sciences are fundamentally transforming nearly every area of engineering, science, and society. The University of Washington’s Electrical 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
UW EE hosted its first annual Research Review Day. Industry partners joined University of Washington faculty and students to discuss top research in the field of electrical engineering.
UW EE Ph.D. student Thomas Powers and UW EE alum Scott Wisdom (Ph.D. '17) received the Best Student Paper Award at the IEEE Workshop on Applications of Signal Processing to Audio and Acoustics.
The team, made up of UW electrical engineers and computer science engineers, is one of three in the world to make it to the finals. Their challenge is to build a “socialbot” that can have intelligent conversations with Amazon's Alexa.
Professors Sham Kakade and Maryam Fazel are co-directors on the three-year $1.5 million award from the NSF.
A team of graduate students and researchers, led by UW Electrical Engineering Professor Jenq-Neng Hwang, won the Track 2 challenge in the IEEE Smart World NVIDIA AI City Challenge.
- 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
- Graphics and Imaging Lab
- Data-Driven Dynamical Systems
- AI/ML/NLP Lab
- Signal, Speech and Language Interpretation Lab
- Silicon System Research Lab
- Ubicomp (Ubiquitous Computing) Research Lab
- Data Compression 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
- Full-Capacity Unitary Recurrent Neural Networks
- Deep Submodular Functions: Definitions and Learning
- Exploiting Tradeoffs for Exact Recovery in Heterogeneous Stochastic Block Models
- Modeling Stylized Character Expressions via Deep Learning
- Lagrangian Multiplier Adaptation for Rate-Distortion Optimization with Inter-frame Dependency
- A Data-driven Point Cloud Simplification Framework for City-scale Image-based Localization