Bio
I obtained my B.A. from Harvard with a concentration in applied mathematics and a minor in philosophy, and my Ph.D. from UC Berkeley in statistics. Before joining MIT, I held a postdoctoral position in the machine learning and statistics group at Microsoft Research.
Affiliations
- MIT Department of Electrical Engineering and Computer Science (EECS)
- MIT Lab for Information and Decision Systems (LIDS)
- MIT Statistics and Data Science Center (SDSC)
Recent Publications & Working Papers
Aligning Evaluation with Clinical Priorities: Calibration, Label Shift, and Error Costs
Joint with Gerardo Flores, Alyssa Smith, and Julia Fukuyama
The Gaussian Mixing Mechanism: Renyi Differential Privacy via Gaussian Sketches
Joint with Omri Lev, Vishwak Srinivasan, Moshe Shenfeld, Katrina Ligett, and Ayush Sekhari
Homogeneous Algorithms Can Reduce Competition in Personalized Pricing
Joint with Nathan Jo, Kathleen Creel, and Manish Raghavan
Adaptive Backtracking Line Search
Joint with Laurent Lessard and Joao Cavalcanti
High-accuracy sampling from constrained spaces with the Metropolis-adjusted Preconditioned Langevin Algorithm
Joint with Vishwak Srinivasan and Andre Wibisono
Allocation Multiplicity: Evaluating the Promises of the Rashomon Set
Joint with Shomik Jain, Margaret Wang, and Kathleen Creel
Algorithmic Pluralism: A Structural Approach To Equal Opportunity 🏆 Best Paper
Joint with Shomik Jain, Vinith Suriyakumar, and Kathleen Creel
Scarce Resource Allocations That Rely On Machine Learning Should Be Randomized
Joint with Shomik Jain and Kathleen Creel
Adaptive kernel selection for Stein Variational Gradient Descent
Joint with Moritz Melcher, Simon Weissmann, and Jakob Zech
Interaction Context Often Increases Sycophancy in LLMs
Joint with Shomik Jain, Charlotte Park, Matheus Vianna, and Dana Calacci
A Consequentialist Critique of Binary Classification Evaluation: Theory, Practice, and Tools
Joint with G Flores, A Schiff, AH Smith, JA Fukuyama
Unstable Unlearning: The Hidden Risk of Concept Resurgence in Diffusion Models
Joint with Vinith Suriyakumar, Rohan Alur, Ayush Sekhari and Manish Raghavan
UCD: Unlearning in LLMs via Contrastive Decoding
Joint with Vinith M. Suriyakumar and Ayush Sekhari
What Does Your Benchmark Really Measure? A Framework for Robust Inference of AI Capabilities
Joint with Nathan Jo
LLM Output Homogenization is Task Dependent
Joint with Shomik Jain, Jack Lanchantin, Maximilian Nickel, Karen Ullrich and Jamelle Watson-Daniels
Teaching
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6.401
Introduction to Data Science and Statistics
Spring 2021
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6.036
Introduction to Machine Learning
Spring 2022, Spring 2023
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6.3950
AI, Decision Making and Society
Fall 2022, Fall 2023, Fall 2024, Fall 2025
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6.S964
Topics in Data Science for Society
Spring 2025
Contact
Contact Information
- Email: ashia07@mit.edu
- Office: Stata Center