Summary
Li Zhang is an applied ML and data science researcher with eight years of experience building models and tooling at the University of Toronto and in industry labs. Their work spans synthetic and missing-data methods, curriculum learning, ensemble distillation for psychological tasks, SEC filing classification using LLMs and decision forests, and neurosymbolic image generation with diffusion models. Currently balancing multiple research roles and an AI lab automation position, they bridge experimental research and practical automation to accelerate model development and dataset creation. Known for combining statistical methods with modern neural approaches, Li brings a pragmatic focus on robustness and context-aware AI that surfaces in both academic projects and applied lab systems.
7 years of coding experience
Bachelor of Science - BS, Computer Science, Bachelor of Science - BS, Computer Science at University of Toronto
High School Diploma, Passed, High School Diploma, Passed at Thornhill Secondary School