<Angela Lin>

Welcome to my website! I am a fifth year PhD candidate at the Operations Research Center at MIT, advised by Professor Georgia Perakis. Prior to graduate school, I completed my undergraduate studies at Rice University, majoring in Computational and Applied Mathematics and minoring in Mathematics.

I am broadly interested in applying data-driven decision-making frameworks that combine optimization and machine learning to support clinical and managerial decisions in healthcare operations. My current research aims to leverage data and mathematical models to address the unique challenges in clinical decision-making. In particular, my research focuses on settings where clinicians must make real-time sequential treatment or allocation decisions while operating under limited resources.

I am grateful to be supported by the MIT Health and Life Sciences (HEALS) Collaborative Graduate Fellowship.

Papers

A Data-Driven, Interpretable, Risk-Aware Framework for Clinical Decision-Making Under Limited Resources
Co-authors: Lien Le (MD), Dessislava Pachamanova, Georgia Perakis, Omar Skali Lami
Under review at Operations Research.

Dynamic Resource Allocation for Healthcare Service Design: An Application to Geographic Cohorting
Co-authors: Dessislava Pachamanova, Georgia Perakis
Major revision at Service Science.

Reinforcement Learning for Clinical Decision Support for Sepsis Treatment (Case study on Reinforcement Learning)
Co-authors: Dessislava Pachamanova, Georgia Perakis
Minor revision at INFORMS Transactions on Education.

Holistically Robust Markov Decision Processes for Clinical Decision-Making
Co-authors: Gavin Findlay, Dessislava Pachamanova, Georgia Perakis
Working paper. To be submitted to European Journal of Operations Research.

Data-Driven Decision Support for Sepsis Treatment: IV Fluid and Vasopressor Strategies
Co-authors: Lien Le (MD), Douglas McConnell (MD), Dessislava Pachamanova, Georgia Perakis, Adam Schwartz (MD)
Working paper. To be submitted to Journal of American Medical Association.

Talks

Interpretable, Data-Driven Framework for Sepsis Treatment Decision Support
2025 and 2024 Data, Models and Decisions Executive MBA course at MIT Sloan
2025 MIT Sloan Visiting Committee
2024 Society of Hospital Medicine Converge Conference
2023 MSOM Conference
2023 INFORMS Healthcare Conference
2023 INFORMS Annual Meeting
2022 MIT MGB AI Cures Conference

Online Optimization of Patient-Physician Assignments for Geographic Cohorting
2025 INFORMS Annual Meeting
2025 MSOM Conference
2025 Society of Hospital Medicine Converge Conference

Holistically Robust Markov Decision Processes for Clinical Treatment Decisions
2024 INFORMS Annual Meeting

Teaching

MIT 15.730: Data, Models, and Decisions for Executive MBAs
Teaching Assistant, Spring 2024 and 2025, Rating: 6.67/7 and 6.73/7

Rice University CAAM 378: Introduction to Operations Research and Optimization for Undergraduates
Grader, Fall 2019

Rice University BIOC 210: Introductory Biology for Undergraduates
Teaching Assistant, Fall 2018

Awards

INFORMS Case Competition Finalist 2025

MIT Health and Life Sciences (HEALS) Collaborative Graduate Fellowship 2025-2026

National Science Foundation Graduate Research Fellowship Program (NSF GRFP) Honorable Mention 2023

MIT-Google Innovation in Computing Schwarzman College Fellowship 2022-2023

Service and Outreach

MIT Resources for Easing Friction and Stress (REFS) volunteer 2022-Present

MIT Highschool Summer Program (HSP) volunteer teacher 2022

Rice Kinder Institute Community Bridges Fellow 2021

Rice University Academic Mentor 2020-2021

Rice University Alternative Spring Break Participant 2020

Rice University Eco Committee Member 2019-2020

Partners for Advancement of Immersion of Refugees volunteer 2017-2019