Han Wang is a Co-Founder and CTO with 12 years of cross-disciplinary experience blending applied mathematics, software engineering, and cybersecurity to build resilient platforms for high-risk domains. Based in Palo Alto, he leads Upfort’s technical vision for sustainable cyber insurance while drawing on hands-on experience hardening networks during deployments with U.S. Army Cyber Command and advising DARPA projects. CISSP certified and trained at Stanford (MS) and UC Berkeley (BS), he pairs rigorous computational math expertise with production-grade systems work—evident in his contributions to mixed-integer conic solvers in the embotech/ecos project where he improved robustness and memory usage. He has a track record in quantitative research and national-security–grade AI and imaging algorithms, translating complex models into reliable, auditable software. Practical, security-first engineering and an uncommon blend of academic rigor and operational experience inform his approach to productizing risk.
12 years of coding experience
3 years of employment as a software developer
Bachelor of Science (BS), Engineering Mathematics and Statistics, Bachelor of Science (BS), Engineering Mathematics and Statistics at University of California, Berkeley
Accelerator Program, Summer 2017, Accelerator Program, Summer 2017 at Y Combinator
Master of Science (MS), Computational Mathematics and Engineering, Master of Science (MS), Computational Mathematics and Engineering at Stanford University
A lightweight conic solver for second-order cone programming.
Role in this project:
Backend Developer
Contributions:79 commits, 6 pushes, 1 branch in 8 months
Contributions summary:Han contributed to the development of a mixed-integer conic solver, adding files related to mixed-integer second-order cone programming (MISOCP) and its setup and cleanup functionalities. Their work involved modifying input parameters, creating and managing nodes, and integrating the mixed-integer module with the existing ECOS solver. The user also refactored the MI wrapper, optimizing memory usage and removing dynamic allocation, improving the robustness of the code.
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