Yidi Qi
Yidi Qi is a PhD candidate at Northeastern University and a Junior Investigator at the NSF AI Institute for AI and Fundamental Interactions (IAIFI).
His research lies at the intersection of AI, mathematics and theoretical physics. He is particularly interested in building AI tools to solve challenging problems in string theory, differential geometry, number theory, and other areas of mathematics. Recently, He has also become interested in auto-formalization using LEAN and large language models.
His life goal is to develop ideas and projects for the future artificial superintelligence (ASI) to learn from before it outsmarts us.
News
Research
My research follows three complementary pillars covering the full spectrum of mathematical inquiry:
AI for Approximation
Solving complex PDE systems and perform calculations that are intractable with traditional methods, such as Calabi-Yau and G2 metrics.
AI for Discovery
Exploring novel patterns, structures, and conjectures across vast physical and mathematical landscapes.
AI for Rigor
Bridging the gap between numerical approximation and formal certainty, creating pathways for computer-assisted and formally verified proofs.
Key Project
MLGeometry
An open-source Python package for computing Calabi-Yau metrics.
Publications
Authors listed in alphabetical order following mathematics conventions
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