Summary
Xuan Cao is a computational research scientist and PhD candidate in computer science at Brigham Young University, currently based in the San Francisco Bay Area and working on robot proficiency self-assessment at Berkeley Lab. He builds well-calibrated, fault-aware, and explainable ML models that predict autonomous robots’ task performance, combining ResNet-based architectures, Bayesian methods, Markov chains, and one-class anomaly detection. His background uniquely blends deep learning and robotics with earlier PhD and industry leadership in engineering thermophysics and environmental monitoring, where he developed and commercialized REMPI-TOFMS instrumentation and deployed emission-prediction models. With nine years’ experience spanning R&D leadership and postdoctoral automation/ML work, he focuses on robust, deployable solutions that remain resilient to hardware and environmental shifts.
9 years of coding experience
8 years of employment as a software developer
PhD in Engineering, Engineering Thermophysics, PhD in Engineering, Engineering Thermophysics at Zhejiang University
PhD, Computer Science, PhD, Computer Science at Brigham Young University