Summary
Xuhang He is a research-driven machine learning engineer and PhD student in computer science who blends a strong mathematical background with practical experience building and optimizing deep learning pipelines. With roughly a decade of experience, he has contributed to visual place recognition research at NYU and implemented production-oriented automation and validation tools in hardware-focused engineering roles. He excels at translating complex research into reproducible experiments and scalable code, having expanded datasets, improved cross-dataset evaluation, and optimized model training strategies. Comfortable in Python and C++, he also tutors and mentors peers in algorithms and software fundamentals. Based in California, he is transitioning from applied research roles into a PhD program where he continues to push self-supervised and co-visibility reasoning work toward real-world impact. An understated strength is his ability to bridge lab research and engineering tooling, turning experimental ideas into reliable pipelines.
10 years of coding experience
2 years of employment as a software developer
Bachelor of Science - BS, Computer Science, 3.94, Bachelor of Science - BS, Computer Science, 3.94 at New York University
Doctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at University of California, Merced