Shanghai Qi Zhi Institute PI, Assistant Professor at IIIS, Tsinghua.
Jingzhao got Ph.D. graduate from the Computer Science program at the Massachusetts Institute of Technology, recipient of the Berkeley Graduate Fellowship, MIT Lim Fellowship, IIIS Young Scholar Fellowship, MIT Best AI & Decision Making Master's Thesis Award, MIT Best AI & Decision Making Ph.D. Thesis Award, and other accolades. Research primarily focuses on large-scale optimization algorithms, neural network training, algorithmic complexity analysis, machine learning theory, and applications of artificial intelligence.
Personal honor:
IIIS Young Scholar Fellowship
MIT Best Master Thesis in AI and Decision making
MIT Best PhD Thesis in AI and Decision making
Berkeley Graduate Fellowship
MIT Lim Graduate Fellowship
Learning Theory
Oracle and sample complexity of learning problems
Deep learning
Analyze and accelerate neural network training
Dynamical system
Applications of dyanmical system in control, reinforcement learning and battery systems.
4. Zhang J, Wang Y, Jiang B, He H, Huang S, Wang C, Zhang Y, Han X, Guo D, He G, Ouyang M, Realistic fault detection of li-ion battery via dynamical deep learning, Nature Communications, 2023 查看PDF
3. Zhang, Peiyuan and Zhang, Jingzhao and Sra, Suvrit, Sion’s Minimax Theorem in Geodesic Metric Spaces and a Riemannian Extragradient Algorithm, SIAM Journal on Optimization, 2023 查看PDF
2. Cheng, X., Wang, B., Zhang, J., & Zhu, Y. , Fast Conditional Mixing of MCMC Algorithms for Non-log-concave Distributions, Conference on Neural Information Processing Systems (NeurIPS), 2023 查看PDF
1. Kaiyue Wen, Jiaye Teng, Jingzhao Zhang, Benign Overfitting in Classification: Provably Counter Label Noise with Larger Models, International Conference on Learning Representation (ICLR), 2023 查看PDF
