Summary
Taoli Cheng is an interdisciplinary postdoctoral researcher based in Montreal with 11 years of experience applying machine learning to fundamental physics problems. At Mila and Université de Montréal he develops physics-informed neural architectures, generative models for event simulation, and anomaly-detection methods that accelerate scientific discovery, building on prior analysis consulting at CERN. Trained as a theoretical physicist (PhD) and with research stints at Max Planck and the Chinese Academy of Sciences, he combines deep domain knowledge with practical ML engineering. His work emphasizes interpretability and explainability, making complex models more trustworthy for experimental workflows. Less obvious: he bridges high-energy physics and ML production needs, translating research prototypes into tools usable by large collaborations.
11 years of coding experience
4 years of employment as a software developer
Theoretical Physics, Theoretical Physics at Max Planck Institute for Physics
Doctor of Philosophy - PhD, Theoretical Physics, Doctor of Philosophy - PhD, Theoretical Physics at Chinese Academy of Sciences
Bachelor's degree, Applied Physics, Bachelor's degree, Applied Physics at East China University of Science and Technology