Liang Dong

Liang (Leon) Dong

Room 301B, Rogers Engineering Building
One Bear Place #97356
Waco, Texas 76798-7356
Phone: +1-254-710-4589
Fax: +1-254-710-3010
liang_dong@baylor.edu

Liang (Leon) Dong is an associate professor of Electrical & Computer Engineering. He specializes in digital signal processing, wireless communications and networking, cyber-physical system and security, and deep learning for signal processing and communications. His research has been sponsored by Baylor VP for Research, National Science Foundation, DOD TARDEC, MDOT, NASA, and companies such as L3Harris, Intel, ExxonMobil, and Denso. Liang is a senior member of the Institute of Electrical and Electronics Engineers (IEEE) and a member of the American Physical Society (APS). He served as the faculty advisor of Baylor InterVarsity.

Ph.D., University of Texas at Austin, 2002 (Curriculum Vitae | Current Research)

Featured

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Youtube, Dec 2018
Liang (Leon) Dong's General Research Areas


Youtube, Dec 2018
Liang (Leon) Dong's Specific Research Topics


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Baylor Magazine, Feb 2015

High-flying Wi-Fi


Teaching

Research

  • Wireless and Mobile Communications

  • Next Generation (NextG) wireless and mobile systems will provide enhanced data flow, communications, analytics, and automation for our connected world. Our research explores signal processing methods, transmit/receive techniques, radio communications, spectrum utilization, and mobile edge computing for NextG systems. We build AI autonomy to support systems' security, reliability, and adaptability.

  • Internet of Things

  • NextG network systems will connect billions of heterogeneous Internet of Things (IoT) devices. The IoT perceives the physical environment, enables machine-to-machine communication, and provides low-latency computational and storage resources for smart cities, modern transportation, public health and safety, and defense. Our research focuses on energy-efficient communications and data analytics for IoT, and IoT reliability and security.
  • Artificial Intelligence Applications

  • Deep neural networks harness advanced algorithms, big data, and the computing power of modern digital systems to enable machines to learn quickly and accurately at scale. We apply Artificial Intelligence (AI) deep learning to autonomous driving, drug molecule discovery, and industrial automation.



© Liang (Leon) Dong, 2022