Xiaokun Yang

Dr. Xiaokun Yang is an Associate Professor of Computer Engineering in the College of Science and Engineering at the University of Houston-Clear Lake. With extensive industry experience at AMD and CEC, his research bridges hardware design and AI acceleration.

Research focuses on FPGA acceleration for AI/ML, hardware/software co-design, and IoT system architectures. Publications demonstrate innovations in neural network accelerators, hardware-efficient AI, secure SoC design, and edge computing solutions. Recent work explores ReRAM-based accelerators, blockchain-secured hardware, and federated learning systems. Awards include Best Ph.D Forum Paper at ISVLSI 2014.

Education includes a Ph.D. in Electrical and Computer Engineering from Florida International University (2016) and dual M.S. degrees from FIU and Beihang University. Courses taught include Advanced Digital Systems Design, Electronics, and Senior Project. Current research projects investigate FPGA-based AI acceleration and IoT architectures.