I teach machines to see like people and interact with people. As modern machines struggle to fully conceptualize the visual world, my research bootstraps machine learning using frameworks from behavioral and social sciences.
Ranjay Krishna is an Assistant Professor at the Paul G. Allen School of Computer Science & Engineering. His research lies at the intersection of computer vision and human computer interaction. This research has received best paper, outstanding paper, and orals at CVPR, ACL, CSCW, NeurIPS, UIST, and ECCV, and has been reported by Science, Forbes, the Wall Street Journal, and PBS NOVA. His research has been supported by Google, Amazon, Cisco, Toyota Research Institute, NSF, ONR, and Yahoo. He holds a bachelor's degree in Electrical & Computer Engineering and in Computer Science from Cornell University, a master's degree in Computer Science from Stanford University and a Ph.D. in Computer Science from Stanford University.
Ranjay Krishna, Principal Investigator
My students and I are part of the RAIVN and GRAIL research groups at UW. We also closely collaborate with the DUB, NLP, and DB groups.
Masters and undergraduate students
Long term collaborating PhD students
Pre-prints & working papers
Ph.D. @ Stanford University, 2021
Co-advised by Fei-Fei Li
and Michael Bernstein.
Research statement 
Teaching statement 
Diversity statement 
ranjay [at] cs [dot] washington [dot] edu
Bill & Melinda Gates Center
3800 E Stevens Way NE,
Seattle, WA 98195
University of Washington:
CSE 599H: AI vs IA 
CSE 493G1: Deep learning 
CSE 455: Computer Vision 
CSE 576: Advanced Computer Vision 
CS231N: Convolutional Neural Networks for Visual Recognition 
CS131 Computer Vision: Foundations and Applications   
- [Link to all assignments]
- [Link to the crowdsourced class notes book]
[Jul 2023] We are organizing a workshop on Artificial Intelligence and Human-Computer Interaction at ICML 2023
[Jun 2023] I will be giving one of the keynote talks at the New Frontiers in Vision and Language Reasoning workshop at CVPR 2023.
[Mar 2023] Our CVPR 2023 paper was recognized as a CVPR Highlight awarded to top 2.5% of submissions.
[Nov 2022] Our work won the Madrona Prize for the most commercializable research project.
[Nov 2022] Our work at PNAS 2022 has been covered by the press at Science and TechXplore.
[Oct 2022] I am co-organizing the Compositionality in Computer Vision workshop at ECCV 2022.
[Sep 2022] Our large scale AI deployment interacting and learning from real human interactions online appears at PNAS 2022.
[Oct 2021] I am speaking at the Compositionality in Computer Vision workshop at ICCV 2021.
[Oct 2021] Our ACL 2021 paper will receive an outstanding paper award (top 6 papers at the conference).
[Oct 2021] I am co-organizing the Compositionality in Computer Vision workshop at ICCV 2021.
[Jul 2021] I am speaking at the workshop on Humans in the learning loop at ICML 2021.
[Apr 2021] I am successfully defended my Ph.D. at Stanford University and graduated with a distinction in teaching for instructing 5 courses.
[Mar 2021] I have accepted an invitation to serve as an Area Chair for at UIST 2021.
[Mar 2021] I am co-instructing CS 231N Convolutional Neural Networks course during the spring 2021 quarter at Stanford.
[Nov 2020] Our EMNLP W-NUT 2020 paper will appear as an oral presentation (top 10% of all EMNLP W-NUT submissions)
[Oct 2020] Our CSCW 2020 paper will receive a best paper honorable mention award (top 2% of all CSCW submissions)
[Aug 2020] I am co-organizing the International Challenge on Compositional and Multimodal Perception workshop at ECCV 2020.
[Jun 2020] I am co-organizing the Compositionality in Computer Vision workshop at CVPR 2020.
[Jun 2020] I am organizing the ActivityNet Challenge on Dense Captioning Events in Videos at CVPR 2020.
[Jun 2020] I am one of the keynote speakers at the DIRA workshop at CVPR 2020.
[Apr 2020] I am co-instructing CS 231N Convolutional Neural Networks course during the spring 2020 quarter at Stanford.
[Dec 2019] Our NeurIPS 2019 paper will appear as an oral presentation (top 0.5% of all NeurIPS submissions).
[Oct 2019] I am organizing an ICCV workshop on Scene Graph Representation and Learning.
[Oct 2019] I am a co-organizer and a guest editor for an IEEE TPAMI special issue on Graphs in Vision and Pattern Analysis.
[Sep 2019] I am instructing CS 131 Computer Vision: Foundations and Applications during the fall 2019 quarter at Stanford.
Trailer for a documentary
Venue: PBS NOVA
Title: Can we build a brain?
Venue: PBS NOVA
Title: Can we build a brain?