Hi! I’m Megan, a second year PhD student in Computer Science at MIT CSAIL, advised by Professor Armando Solar-Lezama. Previously, I obtained my bachelor degree in Computer Science from Caltech where I worked with Professor Yisong Yue. My research interests center at the intersection of deep learning, reasoning, interpretable machine learning, and program synthesis. I seek to design machine learning systems that are human-interpretable, robust, and highly generalizable to difficult tasks with limited data.

I’m grateful to be supported by the MIT Presidential Fellowship in 2022-2023 and the NSF Graduate Research Fellowship (GRFP).

Publications

MeMo: Meaningful, Modular Controllers via Noise Injection
Megan Tjandrasuwita, Jie Xu, Armando Solar-Lezama, Wojciech Matusik
In submission to ICML 2024.

How Can Large Language Models Help Humans in Design and Manufacturing?
Liane Makatura, Michael Foshey, Bohan Wang, Felix HähnLein, Pingchuan Ma, Bolei Deng, Megan Tjandrasuwita, Andrew Spielberg, Crystal Elaine Owens, Peter Yichen Chen, Allan Zhao, Amy Zhu, Wil J Norton, Edward Gu, Joshua Jacob, Yifei Li, Adriana Schulz, Wojciech Matusik
Harvard Data Science Review 2024

ZeroC: A Neuro-Symbolic Model for Zero-shot Concept Recognition and Acquisition at Inference Time
Tailin Wu, Megan Tjandrasuwita, Zhengxuan Wu, Xuelin Yang, Kevin Liu, Rok Sosic, Jure Leskovec
NeurIPS 2022, ICML 2022 Beyond Bayes Workshop
[code]

Neurosymbolic Programming for Science
Jennifer J. Sun*, Megan Tjandrasuwita*, Atharva Sehgal*, Armando Solar-Lezama, Swarat Chaudhuri, Yisong Yue, Omar Costilla-Reyes
NeurIPS 2022 AI4Science Workshop

Interpreting Expert Annotation Differences in Animal Behavior
Megan Tjandrasuwita, Jennifer J. Sun, Ann Kennedy, Swarat Chaudhuri, Yisong Yue
CVPR 2021 CV4Animals Workshop
[code]

Individual Evolutionary Learning and Zero-Intelligence in the Continuous Double Auction
Jasmina Arifovic, Anil Donmez, John Ledyard, Megan Tjandrasuwita
Handbook of Experimental Finance, Edward Elgar Publishing, 2022, pp. 225–249

Teaching Experience

Caltech Teaching Assistant, Jan 2022 – Jun 2022
Held office hours and graded problem sets for graduate-level computer science courses: “Machine Learning and Data Mining” (CS/EE 155) and “Advanced Machine Learning Methods” (CS/EE 159). Gave a lecture for CS 159.

Computer Science Instructor in K-12 Education, Jan 2022 – Mar 2022
Designed computer science curricula, prepared lesson plans, and taught students of diverse backgrounds at local high schools partnered with Caltech.

Volunteer Tutor with Caltech Y Rise, 2018 – 2022
Taught local high school students in math and science.

Honors and Awards

NSF Graduate Research Fellowship (GRFP), 2022
MIT Stata Family Presidential Fellowship, 2022
Caltech Bhansali Family Prize in Computer Science, 2022
Northern California Associates Research Fellowship, 2021
Caltech Summer Undergraduate Research Fellowship, 2019