Dec 17: Accepted to AAMAS! Work extending Restless Bandits past the paradigm of "to act or not to act" by allowing for multiple action choices per arm. Relevant for planning in domains where multiple intervention options are available to one resource-constrained planner (e.g., community health care). Paper forthcoming!
Sept 25: Accepted to NeurIPS! Co-first author work with Aditya Mate developing theory for Collapsing Bandits, a new subclass of Restless Bandits. Simulation evaluations on a real-world-derived public health challenge. Extensions to follow [preprint]
Sept 24: Accepted to PNAS! Our COVID-19 modeling work of between-population variation of disease dynamics by accounting for country-specific demographics, contact patterns, comorbidities, and household structures [publication] [code]
April 30: Live interview on ABC-7 WJLA about our work modeling COVID-19 [video]
April 28: (COVID-19) See our collaborative work with The Daily Beast to evaluate Georgia's proposed reopening policies. Great experience working the journalists on The Daily Beast team! [article] [preprint]
I am a PhD student in Computer Science at Harvard University. Advised by Prof. Milind Tambe, I study how AI techniques can solve challenges in public health, with a technical focus in machine learning and sequential decision making. Using these approaches, I have developed predictive models and sequential planning tools for community health workers in India combatting tuberculosis. Part of this work I conducted from Banglore while on a research internship with Microsoft Research India, where I was grateful to be advised by Dr. Amit Sharma. Currently, I am very proud and fortunate to be supported by a 2019-'22 National Science Foundation Graduate Research Fellowship.
Previously, I have worked on building agent-based models for simulating non-pharmacological interventions for preventing the spread of COVID-19 and designed machine learning models for detecting sobriety using mobile health data (check out the dataset!) During my undergraduate degree at The Ohio State Univeristy, I studied computational genetics as a Pelotonia fellow.
Outside of research, I co-direct the Harvard AI in Healthcare Group, a cross-sectional organization that brings together students, researchers and entrepreneurs from across disciplines to explore opportunities and hear from leading experts in this exciting space. I also co-organize the Harvard CRCS Rising Stars Workshop which seeks to highlight and provide networking and mentorship opportunities to budding junior researchers dedicated to studying AI for Social Impact.