About me

Hey! My name is Aaron—I'm an undergraduate student studying computer science and mathematics at UMass Amherst. I am broadly interested in theoretical aspects of artificial intelligence, privacy, and algorithm design. In the past, I have researched applications of machine learning in drug discovery and quantum chemistry.

Links

• Personal Webpage
• GitHub
• LinkedIn
• Google Scholar

Coursework

A list of courses that I've taken at UMass.

Spring 2025

• CS 596C: Complexity Theory Seminar
• CS 611: Advanced Algorithms
• Math 612: Algebra II (Modules, Fields, Galois Theory, Commutative Algebra)
• Math 621: Complex Analysis

Fall 2024

• CS 514: Algorithms for Data Science
• CS 666: Theory and Practice of Cryptography
• Math 370: Writing in Mathematics
• Math 611: Algebra I (Groups, Rings, Modules)

Spring 2024

• CS 220: Programming Methodology
• CS 311: Intro Algorithms
• CS 501: Formal Language Theory
• CS 589: Machine Learning

Fall 2023

• CS 230: Computer Systems Principles
• CS 240: Reasoning Under Uncertainty
• Math 411: Intro Abstract Algebra I
• Math 523H: Intro Real Analysis I

Resume/CV

News

• [01/2025] A brief summary of my work is available here.
• [12/2024] I will be a Head UCA for CS 311: Introduction to Algorithms starting Spring 2024.
• [08/2024] I am a lecturer for the UMass Machine Learning Club starting Fall 2024.
• [05/2024] I am selected to be an Undergraduate Course Assistant for CS 311: Introduction to Algorithms starting Fall 2024.
• [04/2024] I am selected to participate in the UMass Math/Stats REU program in Summer 2024! I will be working with Prof. Siman Wong on a project involving lattice packings of hyperspheres. More details to follow.
• [03/2024] Cheng-Wei Ju's paper "Accurate Electronic and Optical Properties of Organic Doublet Radicals Using Machine Learned Range-Separated Functionals" (on which I am a co-author) is accepted by The Journal of Physical Chemistry A and selected as the front cover paper of the latest issue. Congratulations to Cheng-Wei, Prof. Lin, and the rest of the team!
• [08/2023] I am continuing to work at AbbVie as an analyst/intern through the 2023-24 school year! I will be working with the Computational Toxicology department on developing a deep learning model to generate synthetic animal study data. The project aims to reduce the need for animal studies in the drug discovery pipeline. Our research is conducted in collaboration with the U.S. Food and Drug Administration (see: AnimalGAN Initiative).