Algorithm Developer Intern at Hudson River Trading
New York, New York, United States
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Summary
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Rockstar
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Top School
Sitong An is an algorithm developer and machine learning researcher who bridges cutting-edge ML with experimental high-energy physics, currently interning at Hudson River Trading and completing a PhD at Carnegie Mellon. With eight years of experience across CERN, DESY, Fermilab and industry internships, Sitong has applied graph neural networks, pruning/quantization workflows, and novel boosting techniques to real-world physics and genomics problems. A Marie Skłodowska-Curie fellow and INSIGHTS ITN alumnus, they have translated academic ML advances into production-oriented benchmarks and client-facing computer vision adaptations at KPMG Netherlands. Comfortable in Python, C++, ROOT and parallel computing, Sitong combines deep domain expertise in particle physics with practical algorithm engineering for low-latency, high-throughput environments. Notably, they’ve automated hyperparameter and working-point optimization pipelines and adapted state-of-the-art research into deployable solutions beyond academia.
8 years of coding experience
2 years of employment as a software developer
Singapore-GCE O Level, Singapore-GCE O Level at Catholic High School 公教中学
Exchange Programme, Physics, Exchange Programme, Physics at Massachusetts Institute of Technology
Master of Natural Sciences (Physics) and Bachelor of Arts, Master of Natural Sciences (Physics) and Bachelor of Arts at University of Cambridge
Doctor of Philosophy - PhD, Experimental High Energy Physics, Doctor of Philosophy - PhD, Experimental High Energy Physics at Carnegie Mellon University
Singapore-GCE A Level, Singapore-GCE A Level at Hwa Chong Institution
Master of Science - MS, Machine Learning, Master of Science - MS, Machine Learning at Machine Learning Department at CMU
Contributions:1 review, 56 commits, 1 PR in 8 months
prototypetmvainferencemachine-learning
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Sitong An - Algorithm Developer Intern at Hudson River Trading