Ethan Sunshine is a computational scientist and Member of Technical Staff who builds machine-learning-driven surrogate models and optimization tools for chemical engineering and sustainable energy problems. With a PhD from Carnegie Mellon and four years of research-focused experience, he has developed piecewise-linear surrogate models and graph-neural-network workflows to predict chemical properties and accelerate process design. His work bridges academic rigor—PhD research and national lab internships—with product-oriented research at Quadrillion Labs and a quant internship at Hudson River Trading, demonstrating fluency in both research and production settings. Based in New York, he combines chemical engineering and mathematics training to translate quantum and data-driven simulations into practical engineering decisions, often finding elegant, computationally efficient approximations where full-scale models are impractical.
4 years of coding experience
4 years of employment as a software developer
Summer School, Chemical Engineering: Carbon Capture Pilot Plant, Summer School, Chemical Engineering: Carbon Capture Pilot Plant at Imperial College London
Bachelor of Science - BS, Chemical Engineering, Bachelor of Science - BS, Chemical Engineering at University of Notre Dame
Doctor of Philosophy - PhD, Chemical Engineering, Doctor of Philosophy - PhD, Chemical Engineering at Carnegie Mellon University
High School Diploma, High School Diploma at Salesianum School
Contributions:91 pushes, 7 branches in 1 year 3 months
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Ethan Sunshine - Member Of Technical Staff at Quadrillion Labs