Sotabase

Career

· Faculty Associate at Berkman Klein Center for Internet and Society, Harvard University2025–
· Junior Research Fellow of Trinity College, University of Cambridge2025–
· Assistant Professor of Statistical Sciences, University of Toronto2025–
· Master's Degree in Statistics, University of Oxford2016–2017
· Undergraduate Degree in Mathematics and Economics, Yale University2012–2016
· AI Fellow at Center for Security and Emerging Technology, Georgetown University
· Assistant Professor and Faculty Fellow, New York University
· Associate Member of the Department of Computer Science, University of Oxford
· DPhil Candidate in Computer Science, University of Oxford
· PhD in Computer Science, University of Oxford

Publications (61)

The StarCraft Multi-Agent Challenge
Adaptive Agents and Multi-Agent Systems · 2019
1,138
cited
Protein Design with Guided Discrete Diffusion
Neural Information Processing Systems · 2023
185
cited
Plex: Towards Reliability using Pretrained Large Model Extensions
arXiv.org · 2022
141
cited
A Systematic Comparison of Bayesian Deep Learning Robustness in Diabetic Retinopathy Tasks
arXiv.org · 2019
121
cited
Multi3Net: Segmenting Flooded Buildings via Fusion of Multiresolution, Multisensor, and Multitemporal Satellite Imagery
AAAI Conference on Artificial Intelligence · 2018
115
cited
Uncertainty Baselines: Benchmarks for Uncertainty & Robustness in Deep Learning
arXiv.org · 2021
107
cited
Benchmarking Bayesian Deep Learning on Diabetic Retinopathy Detection Tasks
NeurIPS Datasets and Benchmarks · 2022
66
cited
Challenges and Opportunities in Offline Reinforcement Learning from Visual Observations
Trans. Mach. Learn. Res. · 2022
63
cited
Position: Bayesian Deep Learning is Needed in the Age of Large-Scale AI
International Conference on Machine Learning · 2024
58
cited
VIREL: A Variational Inference Framework for Reinforcement Learning
Neural Information Processing Systems · 2018
58
cited
Tractable Function-Space Variational Inference in Bayesian Neural Networks
Neural Information Processing Systems · 2023
55
cited
A Study of Bayesian Neural Network Surrogates for Bayesian Optimization
International Conference on Learning Representations · 2023
53
cited
Continual Learning via Sequential Function-Space Variational Inference
International Conference on Machine Learning · 2023
52
cited
Non-Vacuous Generalization Bounds for Large Language Models
International Conference on Machine Learning · 2023
40
cited
Visual Explanations of Image-Text Representations via Multi-Modal Information Bottleneck Attribution
Neural Information Processing Systems · 2023
35
cited
An Information-Theoretic Perspective on Variance-Invariance-Covariance Regularization
arXiv.org · 2023
29
cited
Benchmarking Bayesian Deep Learning with Diabetic Retinopathy Diagnosis
2019
28
cited
On Pathologies in KL-Regularized Reinforcement Learning from Expert Demonstrations
Neural Information Processing Systems · 2022
28
cited
Outcome-Driven Reinforcement Learning via Variational Inference
Neural Information Processing Systems · 2021
22
cited
Learning from Reward-Free Offline Data: A Case for Planning with Latent Dynamics Models
arXiv.org · 2025
20
cited
Sotabase