Summary
Zhenyu Liao is a Research Associate Professor at Huazhong University of Science and Technology with a decade of experience at the intersection of statistics, machine learning, and large-scale neural network theory. He completed a Ph.D. at Université Paris-Saclay focusing on a random matrix framework for high-dimensional machine learning, and held a postdoctoral appointment at UC Berkeley working with Prof. Michael Mahoney across statistics and ICSI. His background blends rigorous theoretical research with applied signal and image processing from advanced studies in France and an undergraduate foundation in optoelectronics from HUST. Zhenyu’s work emphasizes provable understanding of learning systems in large dimensions, making him adept at translating complex mathematical tools into insights for modern neural networks. He maintains an active academic presence with a personal website and GitHub showcasing his research, signaling both openness and reproducibility. Colleagues value his cross-cultural training and ability to bridge European theoretical traditions with US research environments.
10 years of coding experience
1 year of employment as a software developer
Master’s Degree, Signal and image processing, Second year of Master, Master’s Degree, Signal and image processing, Second year of Master at École Supérieure d'Électricité
Master’s Degree, Information Technology, First year of master, Master’s Degree, Information Technology, First year of master at Université Paris Sud (Paris XI)
Bachelor of Science (BS), Optoelectronic, Bachelor of Science (BS), Optoelectronic at Huazhong University of Science and Technology
Doctor of Philosophy (Ph.D.), Statistics and Machine Learning, Doctor of Philosophy (Ph.D.), Statistics and Machine Learning at Université Paris-Saclay
Chinese, English, French