Summary
Kalvin Kao is a Senior Data Scientist with nine years of experience applying ML and systems engineering to real-world medical sensor data, currently analyzing continuous glucose monitoring at Abbott Diabetes Care. He combines a strong engineering foundation from MIT and systems work at Roche with a UC Berkeley MIDS (4.0 GPA) focus on production-ready machine learning, evidenced by recent projects like a factorization-machine CTR predictor on GitHub. Comfortable bridging research and product, he has taught data science at Berkeley and brought sensor R&D experience from Medtronic and MIT into regulated healthcare settings. Known for practical experimentation and clean, reproducible workflows, he focuses on turning noisy physiological signals into actionable insights for clinicians and patients.
9 years of coding experience
6 years of employment as a software developer
B.S., Biological Engineering, B.S., Biological Engineering at Massachusetts Institute of Technology
Master of Information and Data Science (MIDS), GPA: 4.0/4.0, Master of Information and Data Science (MIDS), GPA: 4.0/4.0 at UC Berkeley School of Information