Overview
Theoretical computer science and machine learning.
Current Appointments & Affiliations
Cue Family Associate Professor of Computer Science
·
2023 - Present
Computer Science,
Trinity College of Arts & Sciences
Associate Professor of Computer Science
·
2021 - Present
Computer Science,
Trinity College of Arts & Sciences
Director of Graduate Studies PhD Program in the Department of Computer Science
·
2023 - Present
Computer Science,
Trinity College of Arts & Sciences
Associate Professor of Mathematics
·
2024 - Present
Mathematics,
Trinity College of Arts & Sciences
Recent Publications
ON THE LIMITATIONS OF TEMPERATURE SCALING FOR DISTRIBUTIONS WITH OVERLAPS
Conference 12th International Conference on Learning Representations, ICLR 2024 · January 1, 2024 Despite the impressive generalization capabilities of deep neural networks, they have been repeatedly shown to be overconfident when they are wrong. Fixing this issue is known as model calibration, and has consequently received much attention in the form o ... CiteRECALL: Membership Inference via Relative Conditional Log-Likelihoods
Conference EMNLP 2024 - 2024 Conference on Empirical Methods in Natural Language Processing, Proceedings of the Conference · January 1, 2024 The rapid scaling of large language models (LLMs) has raised concerns about the transparency and fair use of the data used in their pretraining. Detecting such content is challenging due to the scale of the data and limited exposure of each instance during ... CiteProvably Learning Diverse Features in Multi-View Data with Midpoint Mixup
Conference Proceedings of Machine Learning Research · January 1, 2023 Mixup is a data augmentation technique that relies on training using random convex combinations of data points and their labels. In recent years, Mixup has become a standard primitive used in the training of state-of-the-art image classification models due ... CiteRecent Grants
Collaborative Reseach: Transferable, Hierarchical, Expressive, Optimal, Robust, Interpretable NETworks (THEORINET)
ResearchPrincipal Investigator · Awarded by National Science Foundation · 2020 - 2025Collaborative Reseach: Transferable, Hierarchical, Expressive, Optimal, Robust, Interpretable NETworks (THEORINET)
ResearchPrincipal Investigator · Awarded by Simons Foundation · 2020 - 2025CAREER: Optimization Landscape for Non-convex Functions - Towards Provable Algorithms for Neural Networks
ResearchPrincipal Investigator · Awarded by National Science Foundation · 2019 - 2024View All Grants
Education, Training & Certifications
Princeton University ·
2013
Ph.D.