Julia Balla

I am a first-year PhD student at MIT EECS co-advised by Professors Tess Smidt and Tommi Jaakkola. I am broadly interested in AI for scientific discovery and the interplay between symmetry and machine learning.

Previously, I completed my M.S. in Computer Science at the University of Oxford as a DeepMind scholar and my B.S. in Mathematics with Computer Science at MIT.

Publications and preprints

AI-Assisted Discovery of Quantitative and Formal Models in Social Science

Julia Balla, Sihao Huang, Owen Dugan, Rumen R. Dangovski, Marin Soljacic
arXiv:2210.00563 (2023)
[arXiv] [code]

PrivateMail: Supervised Manifold Learning of Deep Features With Differential Privacy for Image Retrieval

Praneeth Vepakomma, Julia Balla, Ramesh Raskar
Oral presentation at AAAI-22
[arXiv] [code]

Splintering with distributions: A stochastic decoy scheme for private computation

Praneeth Vepakomma, Julia Balla, Ramesh Raskar
arXiv:2007.02719 (2020)
[arXiv]

Teaching

C15061: The Mathematics of Multi-Agent Systems

I co-taught a lecture series on reinforcement learning, behavioral economics, and complex systems to high schoolers at MIT HSSP
[website]

C14311: Minecraft Fires, Social Networks, and Quantum Complexity

I co-taught a class on graph theory and complex systems science to high schoolers at MIT Splash
[slides]

Course projects

Over-squashing in Graph Neural Networks

Final blog post for MIT 6.S898: Deep Learning
[post]

Ramsey Theory

Final paper for MIT 18.204: Seminar in Discrete Mathematics
[paper]