Dongwon Han
Data Scientist
London, England, United Kingdom
Summary
👤
Senior🎓
Top SchoolDongwon Han is a PhD-trained data scientist with nine years of experience translating simulation-driven research into production-grade ML systems, currently building risk-selection and pricing pipelines at Inigo for Lloyd’s of London markets. He combines deep expertise in simulation-based inference, uncertainty quantification, and high-performance computing (MPI, CUDA) with hands-on development of PyTorch models, LLM-based document understanding, GANs and diffusion models. His background in computational physics and cosmology informs a rigorous approach to synthetic data generation and robust model evaluation for high-stakes or autonomous systems. Dongwon has a proven track record of owning end-to-end pipelines from feature ingestion through deployment and monitoring, and of turning MCMC and generative-model prototypes into scalable tools. Less obvious: his career arc spans astrophysics, full-stack Java engineering, and high-performance scientific computing, giving him a rare blend of production software engineering and advanced probabilistic modeling.
9 years of coding experience
11 years of employment as a software developer
Bachelor of Science (B.S.) Mathematics, Bachelor of Science (B.S.) Mathematics at University of Massachusetts AmherstDoctor of Philosophy (Ph.D.) Physics, Doctor of Philosophy (Ph.D.) Physics at Stony Brook University
Github Skills (33)
cosmology9
spectra9
derived9
sky9
harmonic9
orbit9
act8
simulations8
orbital-mechanics8
simulation8
image-processing8
astrophysics7
spectrum7
pixel7
pipeline7
Programming languages (5)
Github contributions (5)
dwhan89/cosmikyu
Jan 2020 - Nov 2021
Contributions:103 commits, 14 PRs, 147 pushes in 1 year 10 months
dwhan89/orphics
May 2017 - Jan 2021
A repository containing analysis and theory tools for cosmological data.
Contributions:4 PRs, 25 pushes, 7 branches in 3 years 8 months
pythontheory
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