Summary
Junzheng Wu is a Senior Associate Machine Learning engineer and PhD in Computer Science from the University of Ottawa with eight years of hands-on experience building deep learning systems across NLP, computer vision, and time-series domains. He has authored six publications and led projects that range from deploying 70B-parameter language models and open-sourcing Llmreflect to developing medical imaging and stroke-segmentation pipelines using TensorFlow and EfficientNet. Skilled in PyTorch, Hugging Face, llama.cpp, LangChain, TensorFlow, and production tooling (Poetry, PyTest, CI), he bridges research-grade models with reproducible engineering and deployment. His background includes innovative lab automation and neuroscience imaging work that informed robust behavior-recognition models, and he has applied control-theory techniques (custom PID) to hardware like thermal cyclers — a hint at his comfort spanning software, math, and embedded interaction. Based in Old Toronto, he focuses on shipping practical LLM and deep-learning solutions that integrate local and cloud model stacks for real-world problems.
8 years of coding experience
6 years of employment as a software developer
Bachelor's degree Computer Software Engineering, Bachelor's degree Computer Software Engineering at Southwest Jiaotong University
Doctor of Philosophy - PhD Deep Learning Protein-protein Interaction Contractive Learning NLP Computer Vision, Doctor of Philosophy - PhD Deep Learning Protein-protein Interaction Contractive Learning NLP Computer Vision at University of Ottawa