Baojia Tong is a machine learning engineer with a decade of experience applying advanced ML and data-driven methods to real-world problems, currently building models at Suno in Cambridge. He holds a Ph.D. in experimental particle physics from Harvard, where he developed novel signal regions and ML-driven event selection that substantially boosted sensitivity in LHC searches. At Meta he led an accuracy workstream that improved a high-impact metric on novel devices by over 50%, pairing algorithm development with experimental data collection and simulation frameworks. Previously he built graph-based deep learning systems for document intelligence and productionized extraction pipelines for financial documents at Kensho. Comfortable moving between research-grade C++ and production ML stacks, he also has a track record of saving computation time at scale and mentoring teams. Outside of engineering, he balances rigorous scientific thinking with a playful team presence—an occasional sh*tposter and dedicated dogfooder.
10 years of coding experience
14 years of employment as a software developer
High School, High School at Beijing No.4 High School
Bachelor of Science (BS), Physics, 4.0, Bachelor of Science (BS), Physics, 4.0 at California Institute of Technology
Doctor of Philosophy (Ph.D.), Physics, Doctor of Philosophy (Ph.D.), Physics at Harvard University
Contributions:2 PRs, 162 pushes, 3 branches in 2 years 5 months
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