About Me
Hello! I am a final-year Ph.D. Candidate in the Computer Science Department at Harvard University advised by Professor Finale Doshi-Velez and Professor Susan Murphy. I am currently on the job market for research scientist and AI engineer positions. My primary research focus is designing and deploying online reinforcement learning (RL) algorithms for real-world systems.
Before coming to Harvard, I was a Technical Lead at Amazon, developing on backend, desktop, mobile web, and mobile app (native and react native) platforms for the configurable, contextual and personalized navigation experience for Wholefoods Market, Prime Now, & Amazon Fresh.
News
February 2025 - Our Oralytics deployment paper has been accepted and awarded a full-length presentation at IAAI-25 / AAAI-25. This paper conducts post-trial re-sampling analyses to evaluate the algorithm. Results indicate that the Oralytics algorithm did indeed learn the advantage of one action over the other in certain states.
November 2024 - I was invited to give a talk at SLDS 2024 in the ``Statistical learning in clinical trials” session. I presented our recent Oralytics deployment paper.
July 2024 - The Oralytics clinical trial has completed!
May 2024 - I presented our Monitoring fidelity paper at the Society for Clinical Trials Annual Meeting.
February 2024 - Our Oralytics protocol paper has been accepted and published in the Contemporary Clinical Trials journal!
November 2023 - I received a scholarship from the Global Symposium on AI in Dentistry hosted by Harvard School of Dental Medicine.
September 2023 - The RL Algorithm (design details here) we developed is officially running in the Oralytics clinical trial!
June 2023 - I am extremely grateful to be back at Amazon as an Applied Scientist Intern on the Alexa AI team. I worked on improving personalization for LLMs using supervised and RL-based methods.
June 2023 - I was invited to Two Sigma’s Soho HQ for the PhD Symposium to present our work on reward design.
February 2023 - I gave a full-length oral presentation at AAAI 2023 in the Innovative Applications of Artificial Intelligence (IAAI-23) Medical session.
November 2022 - I gave a mDOT webinar on Designing Reinforcement Learning Algorithms for Mobile Health (video here).
November 2022 - Our paper Reward Design For An Online Reinforcement Learning Algorithm Supporting Oral Self-Care (arxiv version here) has been accepted to IAAI 2023!
October 2022 - I am grateful for the opportunity to represent Harvard Engineering at the Ivy Collective Symposium hosted by University of Pennsylvania.
July 2022 - Designing Reinforcement Learning Algorithms for Digital Interventions: Pre-implementation Guidelines (paper here) has been accepted and published to the Algorithms journal!
July 2022 - I am grateful to have received the Derek Bok Certificate of Distinction in Teaching Award from Harvard University.
June 2022 - I presented our work Designing Reinforcement Learning Algorithms for Digital Interventions: Pre-implementation Guidelines in a full-length oral presentation at the RLMD 2022 Conference
May 2022 - I am grateful to have received the RLDM 2022 Student Travel Fellowship!
February 2022 - The patent on Item identification based on receipt image filed while I was a Software Developement Engineer at Amazon was issued!