Summary
Zexin Li is a Ph.D. research assistant at UC Riverside with eight years of experience bridging real-time embedded systems, on-device machine learning, and adversarial ML. He has contributed to both industry research groups (Tencent, Kwai) and academic labs (UTD, SUSTech), working on energy-efficient real-time systems, transferable adversarial attacks, and system-level optimizations for heterogeneous CPU/GPU platforms. Zexin’s work spans from deploying ML models on constrained devices to co-optimizing system and application stacks for robust ML performance in production-like settings. Notably, he has practical experience improving peer content delivery networks and deploying large-scale grey tests across thousands of edge devices, reflecting a strong systems-to-ML engineering mindset. Based in Riverside, CA, he is actively seeking collaborations on model deployment, co-optimization, and robustness improvements.
8 years of coding experience
4 years of employment as a software developer
Doctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at University of California, Riverside
Bachelor of Science - BS, Computer Science, Bachelor of Science - BS, Computer Science at South University of Science & Technology of China
Chinese, English