Malvern Madondo

I am a Research Scientist in the department of Radiation & Cellular Oncology at the University of Chicago, working with Dr. Zhen Tian on developing automatic treatment algorithms for various radiotherapy modalities.

Changelog

07/2024 — Starting as a Research Scientist at the University of Chicago in the Department of Radiation & Cellular Oncology!
04/2024 — Defended my PhD dissertation on "Applications of Closed-loop Control in Biomedical Interventions: From Neural Modulation to Diabetes Management" at Emory University!
03/2024 — Giving a lightning talk on "Learning Control Policies of Hodgkin-Huxley Neuronal Dynamics", at MCBIOS24
03/2024 — Poster presentation on "A Neural ODE Approach to Glycemic Control" (based on my Lilly internship) at MCBIOS24
11/2023 — Presented our work, "Learning Control Policies of Hodgkin-Huxley Neuronal Dynamics", at Machine Learning for Health (ML4H 2023)
08/2023 — Completed my research internship with the Advanced Analytics and Data Sciences (AADS) team at Eli Lilly.
09/2022 — Giving a talk on "Closed-loop Deep Brain Stimulation via Optimal Control" at the SIAM Mathematics of Data Science 2022 conference! [poster]
08/2022 — Completed my research internship with the Responsible Tech team at IBM Research in Yorktown Heights, NY.
03/2022 — In San Diego, CA, for the CRA Grad Cohort Workshop for Inclusion, Diversity, Equity, Accessibility, and Leadership Skills (IDEALS)
08/2021 — Thrilled to be one of the recipients of the 2021 Google PhD Fellowship
05/2021 — Started my research internship with the Tech for Justice team at IBM Research where I'm collaborating with researchers in the Center for Computational Health.

Research

My research focuses on machine learning and mathematical optimization, particularly reinforcement learning and optimal control in critical domains like healthcare. I develop closed-loop control solutions for neuromodulatory interventions, such as deep brain stimulation, and glycemic control systems for Type 1 Diabetes management.

Some representative projects include:

Closed-loop Control for Deep Brain Stimulation
[Emory University '24]
Interdisciplinary collaboration with Dr. Lars Ruthotto and Dr. Nicholas Au Yong on developing adaptive control algorithms for optimizing deep brain stimulation via Reinforcement Learning and Optimal Control.

Glycemic Control for Type 1 Diabetes Management
[IBM Research '21 | Eli Lilly '23]
Implemented various control strategies for managing blood glucose levels in simulated Type 1 Diabetes patients. Leveraged RL and OC theory to model the glucoregulatory system and develop algorithms for real-time insulin delivery, reducing the risk of hyperglycemia and hypoglycemia across various meal scenarios.

Reinforcement Learning for Sustainable Agriculture
[IBM Research '22]
Developed SWATGym, a reinforcement learning environment for crop management based on the Texas A&M Soil & Water Assessment Tool(SWAT). SWATgym enables evaluation of various crop management strategies on a full growing season. It includes standard and RL-based agents for decision-making, and a reward function that captures the trade-offs between crop yield and environmental impact.

Fair Reinforcement Learning
[IBM Research '21]
Exploring bias in patient representation in healthcare and developing a fair treatment strategy by leveraging representation learning and reinforcement learning. Work done during internship with IBM Research in collaboration with the talented team at the Center for Computational Health: Mohamed Ghalwash, Zach Shahn, and Pablo Meyer Rojas.

Reinforcement Learning and Graph Generation
[Emory University]
Applying model-based Reinforcement Learning strategies in the field of graph generation, in particular, to generative models that can learn to create novel graphs efficiently.

Malvern Madondo

Research Scientist | UChicago