Dr. Tao Liu is a tenure-track Assistant Professor in the Department of Mathematics and Computer Science at Lawrence Technological University. He received his Ph.D. in Electrical and Computer Engineering from Florida International University (FIU) in 2020, under the supervision of Dr. Wujie Wen(now at North Carolina State University). He also earned an M.S. in Computer Engineering from FIU in 2012 and a B.S. in Computer Science from Southeast University in 2007. Before joining Lawrence Tech, Dr. Liu was a Research Associate in the Department of Electrical and Computer Engineering at Lehigh University and accumulated more than six years of full-time industry experience in software development and data analytics.

Dr. Liu’s research lies at the intersection of algorithms, architectures, and security in artificial intelligence. His work focuses on the design, acceleration, and protection of AI systems, with particular emphasis on efficient, secure, and robust deep learning for real-time, embedded, and edge applications. At Lawrence Tech, he leads research efforts on embedded deep learning, cybersecurity, and cross-domain AI, exploring how emerging hardware technologies can reduce AI latency and power consumption while enabling new capabilities in autonomous systems, IoT devices, and cyber-physical systems. A key component of his work involves adversarial machine learning, where he investigates vulnerabilities in AI models and develops defenses to ensure safety, reliability, and trustworthiness in mission-critical domains.

Dr. Liu’s research has been published in leading conferences and journals in machine learning, electronic design automation, and cybersecurity, including DAC, CVPR, ICCAD, ASP-DAC, ACSAC, HOST, WiSec, TCAD, and JTEC. He has received several recognitions, including Best Paper Nominations at ICCAD 2018 and ASP-DAC 2018, and the DAC 2017 Richard Newton Young Fellow Award.