Liang Dong is an associate professor of Electrical & Computer Engineering at Baylor University. He specializes in digital signal processing, wireless communications and networking, deep learning for signal processing and communications, and cyber-physical systems. His research is sponsored by Intel, L3, TARDEC, MDOT, DENSO, and Baylor VP for Research.
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 on the Executive Board of IEEE West Michigan Section from 2006 to 2011. He served as a Technical Program Committee member for IEEE HealthCom 2015, IEEE GlobalSIP 2015 and IEEE GlobalSIP 2016, as well as a session chair for IEEE WCNC 2013, IEEE GlobalSIP 2016 and IEEE WCNC 2018. Liang is a member of Sigma Xi, Phi Kappa Phi, and Tau Beta Pi, and a faculty advisor of Eta Kappa Nu. He is a faculty advisor of Baylor Unite InterVarsity.
Baylor Lariat, Mar 2018
Deep learning, artificial intelligence leading the way to smart houses
Youtube, Dec 2018
Youtube, Dec 2018
Baylor Magazine, Feb 2015
-                   Since 2018, all of the course materials are organized in Canvas.
- ELC 5396Introduction to Deep Learning
- ELC 4351Digital Signal Processing (Spring 2018, Fall 2017, Spring 2017, Fall 2016) [IEEE Signal Processing Magazine]
- ELC 5396Wireless Communication and Networking (Fall 2017)
- ELC 5356Statistical & Adaptive Signal Processing (Spring 2017)
- ELC 5396Digital Communications (Fall 2016)
- ELC 4438Embedded Systems Design (Spring 2016)
5G Mobile Communications
- The 5th generation (5G) mobile communication is the next generation of wireless broadband connection. To establish a ubiquitous connection of people and things, 5G has three specifications: enhanced mobile broadband, ultra-reliable low-latency communications, and massive machine-type communications. Our research focuses on dynamic spectrum sharing, orthogonal frequency-division multiple access, and multiple-input multiple-output technique for 5G.
Internet of Things
- The Internet of Things (IoT) allows users to gather data from the physical environment. New information and communication technologies make the IoT scalable and reliable to support the emerging demand for smart cities, active health, and connected cars. Our research focuses on energy-efficient communications and networking, big data analysis, and security and trustworthiness of the IoT.
- Deep neural networks use algorithms, big data, and computing power of digital systems to enable machines to learn quickly, accurately, and on a large scale. Our research explores convolutional neural network, recurrent neural network, deep reinforcement learning, generative adversarial networks, and other advanced methods that drive artificial intelligence.
© Liang Dong, 2021