Judy Hoffman

About

Dr. Judy Hoffman is an Associate Professor in the School of Interactive Computing at Georgia Tech, where she is also a member of the Machine Learning Center and a Diversity and Inclusion Fellow. Her research focuses on the intersection of computer vision and machine learning, with specialization in domain adaptation, transfer learning, adversarial robustness, and algorithmic fairness. She has received numerous awards, including NSF CAREER, Google Research Scholar Award, Samsung AI Researcher of the Year Award, NVIDIA female leader in computer vision award, AIMiner top 100 most influential scholars in Machine Learning, MIT EECS Rising Star, and multiple best paper awards. In addition to her research, she co-founded and continues to advise Women in Computer Vision, an organization that provides mentorship and travel support for early-career women in the computer vision community. Prior to joining Georgia Tech, she was a Research Scientist at Facebook AI Research. She earned her PhD in Electrical Engineering and Computer Science from UC Berkeley, followed by Postdoctoral research at Stanford University and UC Berkeley.

Research topics

• Computer science
• Artificial intelligence
• Machine learning
• Computer vision
• Data mining

Selected publications

• Masked reconstruction based self-supervision for human activity recognition

  2020-09-04 · 133 citations

  article

  The ubiquitous availability of wearable sensing devices has rendered large scale collection of movement data a straightforward endeavor. Yet, annotation of these data remains a challenge and as such, publicly available datasets for human activity recognition (HAR) are typically limited in size as well as in variability, which constrains HAR model training and effectiveness. We introduce masked reconstruction as a viable self-supervised pre-training objective for human activity recognition and ex…

  PublisherDOI

• Ego-Exo4D: Understanding Skilled Human Activity from First- and Third-Person Perspectives

  2024-06-16 · 82 citations

  article

  We present Ego-Exo4D, a diverse, large-scale multi-modal multiview video dataset and benchmark challenge. Ego-Exo4D centers around simultaneously-captured ego-centric and exocentric video of skilled human activities (e.g., sports, music, dance, bike repair). 740 participants from 13 cities worldwide performed these activities in 123 different natural scene contexts, yielding long-form captures from 1 to 42 minutes each and 1,286 hours of video combined. The multimodal nature of the dataset is un…

  PublisherDOI

• Gaze-LLE: Gaze Target Estimation via Large-Scale Learned Encoders

  2025-06-10 · 14 citations

  article

  We address the problem of gaze target estimation, which aims to predict where a person is looking in a scene. Predicting a person’s gaze target requires reasoning both about the person’s appearance and the contents of the scene. Prior works have developed increasingly complex, handcrafted pipelines for gaze target estimation that carefully fuse features from separate scene encoders, head encoders, and auxiliary models for signals like depth and pose. Motivated by the success of general-purpose f…

  PublisherDOI

• EgoMimic: Scaling Imitation Learning via Egocentric Video

  2025-05-19 · 9 citations

  article

  The scale and diversity of demonstration data required for imitation learning is a significant challenge. We present EgoMimic, a full-stack framework which scales manipulation via human embodiment data, specifically egocentric human videos paired with 3D hand tracking. EgoMimic achieves this through: (1) a system to capture human embodiment data using the ergonomic Project Aria glasses, (2) a low-cost bimanual manipulator that minimizes the kinematic gap to human data, (3) cross-domain data alig…

  PublisherDOI

• SKYSCENES: A Synthetic Dataset for Aerial Scene Understanding

  Lecture notes in computer science · 2024-11-01 · 4 citations

  book-chapter
  PublisherDOI

Frequent coauthors

• Trevor Darrell

  88 shared

• Kate Saenko

  65 shared

• Eric Tzeng

  37 shared

• Jeff Donahue

  27 shared

• Viraj Prabhu

  R.M.D. Engineering College

  22 shared

• Daniel Bolya

  20 shared

• Prithvijit Chattopadhyay

  Georgia Institute of Technology

  19 shared

• Dhruv Batra

  14 shared

Awards & honors

• NSF CAREER
• Google Research Scholar Award
• Samsung AI Researcher of the Year Award
• NVIDIA female leader in computer vision award
• AIMiner top 100 most influential scholars in Machine Learnin…

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