Julia Balla

I am a second-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 in designing ML methods that exploit symmetry in data. My research is funded by the NDSEG Fellowship.

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.

CV

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
Nature Humanities & Social Sciences Communications 2025
[paper] [code]

A Cosmic-Scale Benchmark for Symmetry-Preserving Data Processing

Julia Balla, Siddharth Mishra-Sharma, Carolina Cuesta-Lazaro, Tommi Jaakkola, Tess Smidt
LoG 2024 (Extended Abstract) — Spotlight Oral
NeurIPS NeurReps Workshop 2024 (Proceedings Track)
[paper] [poster] [code]

CodonMPNN for Organism Specific and Codon Optimal Inverse Folding

Hannes Stark*, Umesh Padia*, Julia Balla, Cameron Diao
ICML ML4LMS Workshop 2024 — Most Commercially Exciting Research Award
ICML AI4Science Workshop 2024
[paper] [poster] [code]

Over-Squashing in Riemannian Graph Neural Networks

Julia Balla
LoG 2023 (Extended Abstract)
[paper] [poster]

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

Praneeth Vepakomma, Julia Balla, Ramesh Raskar
AAAI 2022 — Spotlight Oral
[paper] [code]

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]

Miscellaneous projects

Benchmarking Graph Rewiring Techniques for Graph Attention Networks

Mini-project for the Graph Representation Learning course at Oxford.
[paper] [code]

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]