Sotabase

Career

· Co-Founder & Head of AI, Virtue AI2024–
· Assistant Professor, Stanford University2022–
· Adjunct Associate Professor, University of Illinois Urbana-Champaign2021–
· Research Scientist, Google2018–2024
· Assistant Professor, University of Illinois Urbana-Champaign2016–2021
· Postdoctoral Researcher, Stanford University2014–2016
· Postdoctoral Researcher, University of Texas at Austin2013–2014
· M.S. / Ph.D. Electrical Engineering, University of Texas at Austin2008–2013
· B.S. Electrical Engineering, New Jersey Institute of Technology2000–2005

Publications (184)

Representation Engineering: A Top-Down Approach to AI Transparency
arXiv.org · 2023
739
cited
DecodingTrust: A Comprehensive Assessment of Trustworthiness in GPT Models
Neural Information Processing Systems · 2023
568
cited
A Field Guide to Federated Optimization
arXiv.org · 2021
465
cited
Testing and Evaluation of Health Care Applications of Large Language Models: A Systematic Review.
Journal of the American Medical Association (JAMA) · 2024
275
cited
Rethinking machine unlearning for large language models
Nature Machine Intelligence · 2024
219
cited
Investigating Data Contamination for Pre-training Language Models
arXiv.org · 2024
93
cited
Toward fairness in artificial intelligence for medical image analysis: identification and mitigation of potential biases in the roadmap from data collection to model deployment
Journal of Medical Imaging · 2023
89
cited
One-Minute Video Generation with Test-Time Training
Computer Vision and Pattern Recognition · 2025
67
cited
Open Problems in Technical AI Governance
arXiv.org · 2024
55
cited
Scaling Laws for Downstream Task Performance of Large Language Models
arXiv.org · 2024
49
cited
MedHELM: Holistic Evaluation of Large Language Models for Medical Tasks
arXiv.org · 2025
47
cited
Opportunistic detection of type 2 diabetes using deep learning from frontal chest radiographs
Nature Communications · 2023
38
cited
A Systematic Review of Testing and Evaluation of Healthcare Applications of Large Language Models (LLMs)
medRxiv · 2024
36
cited
Machine Unlearning Doesn't Do What You Think: Lessons for Generative AI Policy, Research, and Practice
arXiv.org · 2024
36
cited
Putnam-AXIOM: A Functional and Static Benchmark for Measuring Higher Level Mathematical Reasoning
36
cited
Self-Supervised Learning of Representations for Space Generates Multi-Modular Grid Cells
Neural Information Processing Systems · 2023
34
cited
Why Has Predicting Downstream Capabilities of Frontier AI Models with Scale Remained Elusive?
arXiv.org · 2024
34
cited
The Leaderboard Illusion
arXiv.org · 2025
32
cited
Toward an Evaluation Science for Generative AI Systems
arXiv.org · 2025
30
cited
Lottery Ticket Adaptation: Mitigating Destructive Interference in LLMs
arXiv.org · 2024
29
cited
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