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I am a PhD Student in Computer Science at Georgia Institute of Technology under the supervision of Professor Vijay Ganesh. I hold a Bachelor of Science in Mathematics from the University of Toronto and a master degree in Computational Mathematics from the University of Waterloo.

I work on building Neuro-symbolic AI systems capable of mathematical reasoning by combining large language models (LLMs) and symbolic (SAT / SMT) solvers. CV (PDF)»

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Selected Publications

Citations: 63   Erdös #: 3  

2024

• Preprint "AlphaMapleSAT: An MCTS-based Cube-and-Conquer SAT Solver for Hard Combinatorial Problems", Piyush Jha, Zhengyu Li, Zhengyang Lu, Curtis Bright, and Vijay Ganesh
• Accepted "A SAT Solver and Computer Algebra Attack on the Minimum Kochen-Specker Problem", Zhengyu Li, Curtis Bright, and Vijay Ganesh. IJCAI 2024.
• Published "A SAT + Computer Algebra System Verification of the Ramsey Problem R(3, 8) (Student Abstract)", Conor Duggan, Zhengyu Li, Curtis Bright, and Vijay Ganesh. AAAI 2024.
• Published "A SAT Solver and Computer Algebra Attack on the Minimum Kochen-Specker Problem (Student Abstract)", Zhengyu Li, Curtis Bright, and Vijay Ganesh. AAAI 2024.

2022

• Published "An SC-Square Approach to the Minimum Kochen–Specker Problem", Zhengyu Li, Curtis Bright, and Vijay Ganesh. SC-Square Workshop, Part of IJCAR 22.
• Published "Automatic quantification and classification of microplastics in scanning electron micrographs via deep learning", Shi, B., Patel, M., Yu, D., Yan, J., Li, Z., Petriw, D., ... & Howe, J. Y. (2022). Science of The Total Environment.

2021

• Published "In Tetracycles: a SET Deck Magic Trick", Parker Glynn-Adey, Zhengyu Li. Math Horizons.

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Awards and Honors More »

• Dean's List Scholar - University of Toronto
• Department Honour Roll - University of Toronto Mississauga Department of Mathematical & Computational Sciences
• Best VR/AR Application - HackWestern Hackathon 2020
• Best Machine Learning Application Award - Hack the Six Hackathon 2019
• Third Place - Scotiabank & University of Toronto Big Data & A.I. Competition 2019

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Graduate Level Courses More »

• STAT 940 Deep Learning
• CM 730 Intro to Symbolic Computation
• CM 762 Data Visualization
• CM 740 Fundamentals of Optimization
• CM 770 Numerical Analysis
• QIC 710 Quantum Information Processing