MIT ’28 · Computer Science, Economics & Data Science + Mathematics
Currently in Cambridge, MA ·
I’m drawn to the human side of computational systems, especially how people use data and technology to navigate markets and make decisions. At the MIT Media Lab, I explored this through randomized experiments and field studies on how AI influences human behavior. At the California ISO, I approached it from a different angle, building test automation for the systems that power California’s wholesale electricity market.
Cambridge, MA
B.S. in Computer Science, Economics & Data Science (6-14); B.S. in Mathematics (18) · GPA 4.7/5.0
Coursework: Game Theory, Microeconomic Theory & Public Policy, Machine Learning, Probability & Random Variables, Optimization Methods for Business Analytics, Algorithms, Linear Algebra & Optimization
Jun–Sep 2026
Sacramento, CA
Jun 2025–Aug 2026
Cambridge, MA
Dec 2025–Apr 2026
Computational Perception & Cognition Lab, advised by Prof. Aude Oliva
Mar–Sep 2025
Oct 2024–Apr 2025
Michelle Kim, Daniel Low, David Lafond, Eugene Shim, Michelle Han, Mohanad Kandil, Chenyu Zhang, Theo Kitsberg, Chelsea Boccagno, Paul Pu Liang, Pattie Maes. ACM CHI 2026.
Abhinav Jain, Ehan Masud, Michelle Han, Rohan Dhillon, Sumukh Rao, Arya Joshi, Salar Cheema, Saurav Kumar. International Conference on Informatics (ICI), 2023.
Aug 2026–present
MIT Sports Lab, advised by Prof. Anette Hosoi
2025
Apple Swift Student Challenge winner
Tennis and figure skating, poker, secondhand fashion and fine jewelry, Broadway, film, and making coffee and matcha.
Cambridge, Massachusetts ·
Computer Science, Economics & Data Science + Mathematics
I study computation, economics and math at MIT. I’m drawn to the human side of computational systems, particularly how people use data and technology to navigate markets and make decisions.
Pick a charm
The short version
Hi, I’m Michelle! I grew up in Sacramento, and at MIT you’ll find me in the lab, volunteering with SWE and Women in EECS, on the tennis court or behind the Latte Lab counter.
I’m studying Computer Science, Economics and Data Science (Course 6-14) and Mathematics (Course 18) at MIT.
At the MIT Media Lab I study how AI-supported systems influence the way people reflect, make decisions and change their behavior, using randomized experiments and field studies. That work led to a paper at ACM SIGCHI 2026. This summer I was a software engineering intern at the California ISO, which runs most of California’s power grid and its wholesale electricity market.
On campus I’m VP of Technology for the Society of Women Engineers and VP of Development for Women in EECS. I’m also on the Undergraduate Advisory Group for the Schwarzman College of Computing, in Sigma Kappa, and on the club tennis team. Off campus I’m usually at a poker table or browsing secondhand designer listings.
MIT Media Lab and MIT CSAIL
At the MIT Media Lab, working with Paul Pu Liang and Pattie Maes, I helped build a voice journaling system that turns spoken entries into counterfactual reflections and personalized action plans. We tested it in a 15-day field study, and that work became our CHI 2026 paper.
I also ran a randomized study (N = 128) asking whether human ratings and LLM-as-judge ratings of AI-generated suggestions predict whether people actually use them. Each one picks up a different signal about behavior.
Before that, in Aude Oliva’s Computational Perception & Cognition Lab at CSAIL, I built an open-source pipeline for eye-tracking data and ran pilot studies on how people judge AI-generated versus real visual content.
Research interests
Things I’ve made
MIT Sports Lab, advised by Prof. Anette Hosoi · Aug 2026 to now
A Python Markov-chain engine that computes live match-win probabilities from point-level serve and return rates, using exact dynamic programming over every possible score.
Serve and return ratings train across 102,077 ATP and WTA matches, replayed in date order so no future data leaks into a prediction. The model’s fair values are then benchmarked against bookmaker closing prices, with the margin removed, on about 98,000 matches.
Apple Swift Student Challenge winner, 2025
A journaling app with seven formats: text, audio, video, sketching, uploads, quizzes and more. It uses AI to detect mood, read handwriting and analyze images so people can spot patterns in their reflections. It has more than 100 users on the App Store.
MIT Media Lab · ACM CHI 2026
A full-stack voice journaling system. It transcribes spoken entries, generates counterfactual reflections with an LLM, and turns them into personalized action plans. We evaluated it in a 15-day study with people using it in their everyday lives.
MIT Women in EECS
An opportunities board for MIT’s Women in EECS community, collecting openings in one place.
Personal portfolio
An earlier portfolio site that you navigate by turning a Rubik’s cube.
Work, research and leadership
Software Engineering Intern
Built Python and Selenium regression suites, run in CI/CD, that validate California’s wholesale energy market systems: real-time bids, dispatch, transactions and grid-reliability constraints. Tracked down mismatches between expected and actual outputs with the engineering team before releases.
VP of Technology
VP of Development
Undergraduate Advisory Group
Executive board
Undergraduate Researcher, Computational Perception & Cognition Lab
Advised by Prof. Aude Oliva. Open-source eye-tracking pipeline and pilot studies on AI-generated versus real visual content.
Undergraduate Researcher
Randomized experiments and field studies on AI-supported reflection and decision-making. Co-author on a CHI 2026 paper.
Instructor Assistant
Co-led 20 scholars through a full-stack web development curriculum: HTML, CSS, JavaScript and UI/UX.
Finance Academy Scholar
Top 4 of 16 teams. Pitched an IPO strategy and share allocation model to Reddit executives.
Awards and selections
Nine cards. Draw three.
First draw
Second draw
Third draw
★ Today’s arcade ★Oct 11
Insert coin · new scores daily
Say hi! Or hello! Or 你好! Or ¡Hola! Or teach me your language :)
Also onInstagramBeliLetterboxd
Palette: cool summer. Set in DM Serif Display and Schibsted Grotesk. Charms and cards drawn by hand in code.
Cambridge, Massachusetts · Updated October 2026
Classic view