Kyunghyun Cho
· Associate Professor of Computer Science and Data ScienceNew York University · Computer Science and Engineering
Active 2011–2024
Academic metrics are sourced from OpenAlex and public funding records; values may differ from Google Scholar.
About
Kyunghyun Cho is a professor who co-leads the Computational Intelligence, Learning, Vision and Robotics (CILVR) research group at NYU. He is involved in multiple research initiatives including Machine Learning for Language (ML²), which he co-leads with He He, Tal Linzen, Eunsol Choi, and Greg Durrett. Additionally, he was part of the B-Team at NYU Radiology led by Krzysztof Geras. His work extends to industry where he leads Frontier Research within Prescient Design at Genentech under the Computational Science Center of Excellence (CS CoE). His research focuses on advancing machine learning, particularly in language, vision, and robotics, and he has mentored a diverse group of postdoctoral researchers, PhD students, MSc/BSc students, visiting researchers, and alumni, contributing significantly to the field through both academic and industry collaborations.
Research topics
- Computer science
- Artificial intelligence
- Natural language processing
- Machine learning
- Algorithm
Frequent coauthors
- 133 shared
Yoshua Bengio
- 66 shared
Richard Bonneau
- 52 shared
Krzysztof J. Geras
- 42 shared
Linda Moy
- 42 shared
James Glass
- 42 shared
Tianxing He
- 37 shared
Sachin Kumar
South Ural State University
- 37 shared
Tianle Wang
Taizhou University
Education
- 2014
Ph.D.
Aalto University
- 2011
M.S., Machine Learning and Data Mining (MACADAMIA)
Aalto University
- 2009
B.S., Computer Science
Korea Advanced Institute of Science and Technology
Awards & honors
- CIFAR Fellow of Learning in Machines & Brains
- Samsung Ho-Am Prize in Engineering (2021)
Similar researchers at New York University
- Resume-aware match score
- Save to shortlist
- AI-drafted outreach
See your match with Kyunghyun Cho
PhdFit ranks faculty by your research interests, methods, and publications — grounded in their actual work, not templates.
- Free to start
- No credit card
- 30-second signup