Faculty
EEB-418
bilmes
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cs.washington.edu
Adjunct, Electrical & Computer Engineering
Machine learning, speech/language/bioinformatics/music, submodularity & discrete optimization
CSE2 210
bboots
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cs.washington.edu
Fundamental and applied research at the intersection of artificial intelligence, machine learning, and robotics
leobix
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uw.edu
Adjunct, Foster School of Business
Artificial intelligence, machine learning, operations research, information systems, large language models and generative AI, multimodality, healthcare, environmental sustainability, predictive and prescriptive analytics, AI for social good, AI and the future of work
CSE2 236
mcakmak
![](/images/bw_ampersand.png)
cs.washington.edu
Human-robot interaction, programming by demonstration, robot teleoperation
aylin
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uw.edu
Adjunct, Information School
Artificial intelligence, AI ethics, algorithmic bias, computational social science, computer vision, data science, machine learning, natural language processing
rcalo
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uw.edu
Adjunct, School of Law
Law and emerging technology, especially robotics, artificial intelligence, augmented and virtual reality, disinformation, security, and privacy
CSE 578
yejin
![](/images/bw_ampersand.png)
cs.washington.edu
Natural language processing
anind
![](/images/bw_ampersand.png)
uw.edu
Adjunct, Information School
ssdu
![](/images/bw_ampersand.png)
cs.washington.edu
Deep learning, representation learning, reinforcement learning, non-convex optimization
CSE2 203
ali
![](/images/bw_ampersand.png)
cs.washington.edu
Computer vision, machine learning
mfazel
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ee.washington.edu
Adjunct, Electrical & Computer Engineering
Convex optimization; systems and control theory
CSE2 204
fox
![](/images/bw_ampersand.png)
cs.washington.edu
Robotics, artificial intelligence, activity recognition
CSE 528
mgolub
![](/images/bw_ampersand.png)
cs.washington.edu
Machine learning and data science for neuroengineering and basic systems neuroscience; deep learning techniques for understanding neural computations in the brain; brain-computer interfaces
abhgupta
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cs.washington.edu
Deep reinforcement learning algorithms for robotic systems, with a focus on reward specification, continual real-world data collection and learning, offline reinforcement learning, and multi-task learning and dexterous manipulation
CSE 470
hannaneh
![](/images/bw_ampersand.png)
cs.washington.edu
Natural Language Processing, Artificial Intelligence, Machine Learning
lalitj
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uw.edu
Adjunct, Foster School of Business
Machine learning, online experiments, human preference learning
CSE2 340
jamieson
![](/images/bw_ampersand.png)
cs.washington.edu
Machine learning, active learning, reinforcement learning
nj
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cs.washington.edu
Social reinforcement learning: developing algorithms that combine insights from social learning, deep learning, and multi-agent training to improve AI agents' learning, generalization, coordination, and human-AI interaction.
pangwei
![](/images/bw_ampersand.png)
cs.washington.edu
Techniques and theory for building reliable and interactive machine learning systems
ranjay
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cs.washington.edu
Development of new representations, models, and training paradigms for machine learning and computer vision, drawing on insights from human-computer interaction, social, and behavioral sciences
CSE 536
suinlee
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cs.washington.edu
Computational biology - precision medicine, network biology, genetics of complex traits; Machine learning - interpretability, feature selection, structure learning
CSE346
mmp
![](/images/bw_ampersand.png)
stat.washington.edu
Adjunct, Statistics
Statistical learning algorithms
saramos
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cs.washington.edu
Development and application of machine learning and statistical methods to study health and disease
Genome Sciences
william-noble
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uw.edu
Adjunct, Genome Sciences
Development of machine learning techniques for molecular biology
CSE2 207
sewoong
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cs.washington.edu
Theory and practice of machine learning, including generative adversarial networks, differential privacy, anonymous messaging, crowdsourcing, and ranking
CSE 590
zoran
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cs.washington.edu
Scientific-discovery games, games for learning, computer graphics, animation, optimal control, natural locomotion, optimization
rao
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cs.washington.edu
Computational neuroscience, artificial intelligence, brain-computer interfaces
ratliffl
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uw.edu
Adjunct, Electrical & Computer Engineering
Machine learning, game theory, decision-making, optimization, artificial intelligence
CSE2 342
seitz
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cs.washington.edu
Computer vision, computer graphics
chirags
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uw.edu
Adjunct, Information School
Artificial intelligence, machine learning, data science, information retrieval
rbs
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cs.washington.edu
Allen School Associate Director for Diversity, Equity, Inclusion and Access and Professor of Computer Science & Engineering
Computing education research and learning technologies to help people explore their curiosities and create things to improve the world around themselves
CSE 634
shapiro
![](/images/bw_ampersand.png)
cs.washington.edu
Computer vision, multimedia retrieval, biomedical informatics
nasmith
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cs.washington.edu
Natural language processing
CSE2 242
siddh
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cs.washington.edu
Robotic manipulation, motion planning, human-robot interaction, assistive robotics
CSE 638
tanimoto
![](/images/bw_ampersand.png)
cs.washington.edu
Liveness in programming environments, programming for virtual reality, educational technology, collaborative problem-solving environments
CSE 566
yuliats
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cs.washington.edu
Natural language processing
swang
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cs.washington.edu
Computational biology — learning in the open-world setting, biomedical natural language processing, network biology
CSE 534
lsz
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cs.washington.edu
Faculty (non-CSE)
thomasr
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u.washington.edu
Statistics
Affiliate Faculty
CSE446
lfb
![](/images/bw_ampersand.png)
cs.washington.edu
Machine Learning, Computer Vision, Robotics
guestrin
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stanford.edu
Machine learning
halevy
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google.com
Google
Data management, artificial intelligence
horvitz
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microsoft.com
Microsoft Research
Adaptive systems and interaction
kautz
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cs.rochester.edu
University of Rochester
Knowledge representation and reasoning systems.
Yoky Matsuoka
CSE650
yoky
![](/images/bw_ampersand.png)
cs.washington.edu
Nest
Robotics, brain-machine interface
CSE436
matthai
![](/images/bw_ampersand.png)
microsoft.com
Microsoft Research
Human activity recognition, sensor-based reasoning
desney
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microsoft.com
Microsoft Research
Human-Computer Interaction and Brain-Computer Interfaces
CSE 434
todorov
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cs.washington.edu
Intelligent control in biology and engineering
Postdocs
mgord
![](/images/bw_ampersand.png)
cs.washington.edu
Mitchell Gordon is a postdoc working with professors Jeff Heer and Yejin Choi. He designs interactive systems and evaluation approaches that bridge principles of human-computer interaction with the realities of machine learning. He recently completed his Ph.D. in computer science at Stanford, advised by Michael Bernstein and James Landay. He will join MIT EECS/CSAIL as an assistant professor starting fall 2024.
grotz
![](/images/bw_ampersand.png)
cs.washington.edu
Markus Grotz currently works with Dieter Fox in the UW Robotics and State Estimation Lab and Tamim Asfour in the High Performance Humanoid Technologies Lab (H2T). His research focuses on visual perception for robotic manipulation tasks.
Graduate Students (CSE)
CSE382
bansalg
![](/images/bw_ampersand.png)
cs.washington.edu
CSE410
jbare
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cs.washington.edu
Computational cognitive/neuro science
CSE 510
antoineb
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cs.washington.edu
Arunkumar Byravan
barun
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cs.washington.edu
CSE 503
safiye
![](/images/bw_ampersand.png)
cs.washington.edu
Machine Learning, Computational Biology
CSE 402
tqchen
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cs.washington.edu
eunsol
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cs.washington.edu
CSE482
mjyc
![](/images/bw_ampersand.png)
cs.washington.edu
human-robot interaction, machine learning, brain-computer interface
nfitz
![](/images/bw_ampersand.png)
cs.washington.edu
CSE 374
mbforbes
![](/images/bw_ampersand.png)
cs.washington.edu
Natural language processing: learning commonsense knowledge, NLP + {robotics, vision}
luheng
![](/images/bw_ampersand.png)
cs.washington.edu
CSE491 (lab)
peter
![](/images/bw_ampersand.png)
cs.washington.edu
3D reconstruction and mapping with RGB-D (Kinect-style) cameras.
Justin Huang
jstn
![](/images/bw_ampersand.png)
cs.washington.edu
mandar90
![](/images/bw_ampersand.png)
cs.washington.edu
natural language processing, machine learning
CSE374
mkoch
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cs.washington.edu
Machine learning, artificial intelligence, natural language processing, information extraction
CSE 386
kentonl
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cs.washington.edu
natural language processing; artificial intelligence
Lillian Li
CSE 306
yli2244
![](/images/bw_ampersand.png)
cs.washington.edu
CSE414
anglil
![](/images/bw_ampersand.png)
cs.washington.edu
Julian Michael
julianjm
![](/images/bw_ampersand.png)
cs.washington.edu
Natural language processing, artificial intelligence, natural language semantics
George Mulcaire
CSE 394
gmulc
![](/images/bw_ampersand.png)
cs.washington.edu
Natural language processing, artificial intelligence
Eric Rombokas
eric.rombokas
![](/images/bw_ampersand.png)
gmail.com
msap
![](/images/bw_ampersand.png)
cs.washington.edu
Natural Language Processing, Computational Social Science
CSE 390
samt
![](/images/bw_ampersand.png)
cs.washington.edu
I'm interested in natural language understanding. My research is aimed at learning to automatically map natural language sentences to graph representations of their meaning, ideally in a way that works well for a broad variety of domains and languages.
W Austin Webb
CSE524
webb
![](/images/bw_ampersand.png)
cs.washington.edu
clzhang
![](/images/bw_ampersand.png)
cs.washington.edu
Congle Zhang
clzhang
![](/images/bw_ampersand.png)
cs.washington.edu
Non-CSE Grad Students
karna
![](/images/bw_ampersand.png)
uw.edu
(EE)
Collaborators
sumitb
![](/images/bw_ampersand.png)
microsoft.com
Microsoft Research
peterc
![](/images/bw_ampersand.png)
vulcan.com
Vulcan
sdumais
![](/images/bw_ampersand.png)
microsoft.com
Microsoft Research
benjamin.grosof
![](/images/bw_ampersand.png)
gmail.com
Vulcan
me
![](/images/bw_ampersand.png)
patrickpantel.com
Microsoft Research
teevan
![](/images/bw_ampersand.png)
microsoft.com
Microsoft Research
Undergraduate Researchers
Matthew Bryan
CSE 286
mmattb
![](/images/bw_ampersand.png)
cs.washington.edu
Brain-Computer Interfaces, Neural Engineering
Application of machine learning techniques to the brain-computer interface (BCI) domain. This includes hierarchical task modelling (HBCIs), and the use of POMDPs for optimal data collection.
Maxwell Forbes
mbforbes
![](/images/bw_ampersand.png)
cs.washington.edu
Stefan Martin
CSE 286
stefan7
![](/images/bw_ampersand.png)
uw.edu
Spatial filtering for the brain-computer interface (BCI) domain.
Alumni
CSE446
lfb
![](/images/bw_ampersand.png)
cs.washington.edu
Intel Labs
Machine Learning, Computer Vision, Robotics
jbragg
![](/images/bw_ampersand.png)
cs.washington.edu
Marc Deisenroth
CSE480
marc
![](/images/bw_ampersand.png)
cs.washington.edu
CSE394
bdferris
![](/images/bw_ampersand.png)
cs.washington.edu
CSE506
tlin
![](/images/bw_ampersand.png)
cs.washington.edu
CSE414
cynthia
![](/images/bw_ampersand.png)
cs.washington.edu
Human-Robot Interaction, Robots and Language, Robot Learning
CSE444
xm
![](/images/bw_ampersand.png)
cs.washington.edu
CSE490
nath
![](/images/bw_ampersand.png)
cs.washington.edu
xiaofeng.ren
![](/images/bw_ampersand.png)
Amazon