Scholar
Julia Balla
Google Scholar ID: 5qojH9oAAAAJ
Massachusetts Institute of Technology
Citations & Impact
Citations
31
H-index
4
i10-index
1
Publications
7
Co-authors
8
list available
Resume (English only)
Academic Achievements
- Published several papers, such as 'Implicit Augmentation from Distributional Symmetry in Turbulence Super-Resolution' (NeurIPS ML4PS Workshop 2025), 'AI-Assisted Discovery of Quantitative and Formal Models in Social Science' (Nature Humanities & Social Sciences Communications 2025), etc.; Won the Most Commercially Exciting Research Award at ICML AI4Science Workshop 2024.
Research Experience
- Involved in multiple research projects, including turbulence super-resolution, AI-assisted quantitative and formal model discovery in social science, etc.
Education
- PhD: MIT EECS, co-advised by Professors Tess Smidt and Tommi Jaakkola; M.S.: Computer Science at the University of Oxford, DeepMind scholar; B.S.: Mathematics with Computer Science at MIT.
Background
- Research Interests: ML methods that capture and exploit geometric structure, particularly in the context of generative modeling and AI for scientific discovery. Background: Third-year PhD student at MIT EECS.
Miscellany
- Taught high school students about reinforcement learning, behavioral economics, and complex systems at MIT HSSP and MIT Splash; Participated in a mini-project for the Graph Representation Learning course at Oxford and wrote a final blog post for MIT 6.S898: Deep Learning.
