James Roney is an ML research engineer at D. E. Shaw Research and a PhD student at MIT specializing in computational biology and machine learning, with a decade of experience bridging academic rigor and industry research. He has contributed to generative models for small molecules and protein structure prediction, and previously developed Bayesian MCMC methods for cancer growth modeling that led to a co-first author publication. A Harvard alumnus with summa cum laude and highest thesis honors in CS and an MS in Statistics, he combines theoretical foundations with practical implementation across Python and R tooling. Based in Cambridge, MA, James pairs teaching experience in statistics and theoretical CS with hands-on lab and industry internships, making him adept at translating complex models into reproducible software.
10 years of coding experience
2 years of employment as a software developer
Bachelor's degree, Computer Science, Summa Cum Laude, Phi Beta Kappa, Highest Thesis Honors, Bachelor's degree, Computer Science, Summa Cum Laude, Phi Beta Kappa, Highest Thesis Honors at Harvard University
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James Roney - ML Research Engineer at D. E. Shaw Research