Summary
Kuan Wei is a Senior Data Scientist with six years of experience combining rigorous chemical engineering research and production ML to deliver data-driven solutions across industry and academia. Currently at StackAdapt after a stint as an Applied Scientist at Amazon, he builds models and pipelines using Python, PyTorch/TensorFlow, and SQL to turn complex datasets into actionable insights. His background includes first-author published microbiology research and materials science experiments where he translated experimental results into statistical evidence and meaningful efficiency gains (up to 98% drug-use reduction and 42% adsorption improvement). Comfortable with both classical ML and deep learning, he pairs strong quantitative rigor from McGill and UPenn with practical engineering—automating analyses and deploying models in production. Colleagues value him for bridging domain science and ML, and his public writing and GitHub presence reflect a habit of documenting lessons learned beyond code.
6 years of coding experience
6 years of employment as a software developer
Master's degree, Computer and Information Technology, 4.00/4.00, Master's degree, Computer and Information Technology, 4.00/4.00 at University of Pennsylvania
Bachelor of Engineering (B.Eng.), Chemical Engineering, 3.94/4.00, Bachelor of Engineering (B.Eng.), Chemical Engineering, 3.94/4.00 at McGill University
English, Chinese