Stanley Lo is a PhD chemist and machine learning practitioner focused on accelerating materials discovery through self-driving labs and ML-for-materials. With eight years of research and engineering experience, he has developed a photochemical method for accelerated polystyrene recycling and built predictive ML pipelines and databases at Apple for OLED optimization. He bridges academic rigor and product-minded engineering—implementing and benchmarking GNNs at Kebotix and deploying Python/Postgres/AWS CI/CD systems in industry settings. At UofT he actively connects research to entrepreneurship, matchmaking teams and VC needs to turn siloed ideas into viable startups. Curious and interdisciplinary, he blends hands-on lab work, ML model development, and systems engineering to push sustainable materials solutions toward real-world impact.
8 years of coding experience
5 years of employment as a software developer
Ontario Secondary School Diploma International Baccalaureate Diploma, Ontario Secondary School Diploma International Baccalaureate Diploma at St. Francis Xavier Secondary School
Doctor of Philosophy - PhD Chemistry, Doctor of Philosophy - PhD Chemistry at University of Toronto
Contributions:5 reviews, 141 commits, 11 PRs in 10 months
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