Summary
Paul Constantine is a senior scientist and computational mathematician with 17 years of experience applying dimension reduction, reduced-order modeling, and uncertainty quantification to computational physics problems. He pioneered active subspaces for parameter studies and has translated that research into practice through surrogate models and numerical optimization across academic and industry settings. Paul has led a $2M research program, published 50+ peer-reviewed papers, and advised PhD students who now work in national labs and universities. Comfortable in Python, MATLAB, and C, he has taught undergraduate and graduate courses in computational mathematics and moved from faculty roles at Colorado School of Mines and CU Boulder to industry research at Flexcompute. Based in San Francisco, he blends deep theoretical expertise with pragmatic software skills to make high-dimensional simulation studies tractable and actionable. An uncommon strength is his track record of converting novel mathematical ideas into durable tools and curricula that propagate through both research and practice.
17 years of coding experience
13 years of employment as a software developer
B.A. Mathematics, B.A. Mathematics at University of North Texas
Ph.D. M.S. Computational and Mathematical Engineering, Ph.D. M.S. Computational and Mathematical Engineering at Stanford University