I am an associate professor in EECS at MIT studying computer vision, machine learning, and AI.
Previously, I spent a year as a visiting research scientist at OpenAI, and before that I was a postdoctoral scholar with Alyosha Efros in the EECS department at UC Berkeley. I completed my Ph.D. in Brain & Cognitive Sciences at MIT, under the supervision of Ted Adelson, where I also frequently worked with Aude Oliva. I received my undergraduate degree in Computer Science from Yale, where I got my start on research working with Brian Scholl. A longer bio is here.
▸ Science of deep learning: Why do large models find solutions that generalize? What structures improve generalization? And when might these methods still fail?
Representative projects: Low-rank bias, Quasimetric learning, What makes for good views for contrastive learning
▸ Emergent intelligence: How can intelligence emerge from data and tasks, and how can it emerge without imitating another intelligence's cultural artifacts?
▸ Embodied intelligence: To what extent is physical embodiment, in interactive environments, useful or necessary for intelligence?
▸ Synthetic data and environments: What kinds of training data / environments are most instructive toward achieving robust, aligned, and general intelligence?
▸ Controllable AI: How can we make AI systems that can be steered, edited, and controlled by human users?
Minyoung (Jacob) Huh
Former Members and Visitors
Yen-Chen Lin (PhD), Lucy Chai (PhD), Swami Sankaranarayanan (Postdoc), Stephanie Fu (UROP, MEng), Kevin Frans (UROP, MEng), Yonglong Tian (PhD), Jerry Ngo (Visiting student), Taqiya Ehsan (Visiting student), Ali Jahanian (Research Scientist), Dillon Dupont (UROP), Kate Xu (UROP), Maxwell Jiang (UROP), Toru Lin (MEng), Kenny Derek (MEng), Yilun Du (UROP), Zhongxia Yan (Rotation)
|Interested in joining the group? Please see info about applying here.|
|Distilled Feature Fields Enable Few-Shot Language-Guided Manipulation|
William Shen*, Ge Yang*, Alan Yu, Jansen Wong, Leslie Kaelbling, Phillip Isola
CoRL 2023 (oral).
|Learning New Dimensions of Human Visual Similarity using Synthetic Data|
Stephanie Fu*, Netanel Tamir*, Shobhita Sundaram*, Lucy Chai, Richard Zhang, Tali Dekel, Phillip Isola
NeurIPS 2023 (spotlight).
|StableRep: Synthetic Images from Text-to-Image Models Make Strong Visual Representation Learners|
Yonglong Tian, Lijie Fan, Phillip Isola, Huiwen Chang, Dilip Krishnan
|Improving CLIP Training with Language Rewrites|
Lijie Fan, Dilip Krishnan, Phillip Isola, Dina Katabi, Yonglong Tian
|Straightening Out the Straight-Through Estimator: |
Overcoming Optimization Challenges in Vector Quantized Networks
Minyoung Huh, Brian Cheung, Pulkit Agrawal, Phillip Isola
|Optimal Goal-Reaching Reinforcement Learning via Quasimetric Learning|
Tongzhou Wang, Antonio Torralba, Phillip Isola, Amy Zhang
|Persistent Nature: A Generative Model of Unbounded 3D Worlds|
Lucy Chai, Richard Tucker, Zhengqi Li, Phillip Isola, Noah Snavely
|Powderworld: A Platform for Understanding Generalization via Rich Task Distributions|
Kevin Frans, Phillip Isola
[Paper][Blog + Demo][Code]