About
Hello! I am a PhD student at MIT, co-advised by Professors Collin Stultz and Marzyeh Ghassemi. Prior to my PhD, I received my B.S.E. from Princeton University in 2023, where my senior thesis was supervised by the incredible Professor Christiane Fellbaum.
My research focuses on reliable and controllable machine learning with the goal of building models that behave predictably across diverse conditions. In particular, I find value in working on high-stakes domains like healthcare.
Outside of research, I love reading and birding!
You can reach me at abinitha@mit.edu. I'd love to hear from you!
Publications
2026
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Rank-Constrained Adaptation for Reliable Real-World Performance
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Sense and Sensitivity: Benchmarking LLM Clinical Triage Recommendations with Physician Experts
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Answering the Wrong Question: Reasoning Trace Inversion for Abstention in LLMs
2025
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The Medium is the Message: How Non-Clinical Information Shapes Clinical Decisions in LLMs
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2026
Rank-Constrained Adaptation for Reliable Real-World Performance
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Poison-then-Hide: Finetuning-Activated Backdoor Attack on Pretrained Vision Encoders
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Sense and Sensitivity: Benchmarking LLM Clinical Triage Recommendations with Physician Experts
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Answering the Wrong Question: Reasoning Trace Inversion for Abstention in LLMs
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2025
The MedPerturb Dataset: What Non-Content Perturbations Reveal About Human and Clinical LLM Decision Making
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The Medium is the Message: How Non-Clinical Information Shapes Clinical Decisions in LLMs
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2023
PanDa Game: Optimized Privacy-Preserving Publishing of Individual-Level Pandemic Data Based on a Game Theoretic Model
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What seems to be the problem? Stigmatizing language in patient medical notes
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2022
PanDa Game: Optimized Privacy-Preserving Publishing of Individual-Level Pandemic Data Based on a Game Theoretic Model