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Lingjia Liu, Ph.D.

Profile Lingjia Liu, Ph.D.
Professor, Bradley Department of Electrical and Computer Engineering
Associate Director, Wireless@Virginia Tech
Virginia Tech, Blacksburg, VA, USA

Elected Member, Executive Committee
National Spectrum Consortium

439 Durham Hall
1145 Perry Street, Blacksburg, VA, USA
Phone: (540) 231-7243
Email: ljliu AT vt dot edu

Research Interests:

  • Machine learning for Wireless
    • Real-time online learning-based wireless system design and hardware prototyping
    • Incorporating communication structure knowledge in learning strategy design
    • Accelerating deep reinforcement learning for spectrum access and user/resource scheduling
  • Signal Process., Commun. & Netw. for 5G & Beyond
    • 3D mmWave massive FD-MIMO
    • Waveform design for 6G (e.g., MIMO-OTFS)
    • Computing and communication co-design for non-terrestrial networks (NTN)
    • Network slicing using open radio access network (ORAN) platform for prototyping and system design
  • Security and Privacy
    • Anomaly detection for smart grids
    • Adversarial learning for spectrum sharing
    • Differential privacy and federated learning for massive IoT networks
    • Anomaly and jamming detection for 5G networks


Lingjia Liu received the Bachelor of Science (B.S.) degree with the highest honor in Electronic Engineering Department from Shanghai Jiao Tong University, Shanghai, China, and completed his Doctor of Philosophy (Ph.D.) degree at Texas A&M University in Electrical and Computer Engineering. He spent the summer of 2007 and spring of 2008 in the Mitsubishi Electric Research Laboratory. Prior to joining the ECE Department at Virginia Tech (VT), he was an Associate Professor in the EECS Department at the University of Kansas (KU). He spent 3+ years working in the Standards & Mobility Innovation Lab of Samsung Research America (SRA) where he received Global Samsung Best Paper Award twice (in 2008 and 2010 respectively). He was a technical leader and a leading 3GPP RAN1 standard delegate from Samsung on downlink MIMO, Coordinated Multipoint (CoMP) transmission/reception, device-to-device (D2D) communications, and Heterogeneous Networks (HetNets). He was elected as the New Faces of Engineering 2011 by the Diversity Council of the National Engineers Week Foundation. From 2013 to 2017, he has been selected as U.S. Air Force Research Laboratory (AFRL)/Air Force Office of Scientific Research (AFOSR) summer faculty fellow. In 2015, he received the Miller Professional Development Award for Distinguished Research at KU. In 2021, he received College of Engineering Dean’s Award for Excellence in Research at VT.

Lingjia Liu is a senior member of IEEE. He is currently serving as an Associate Editor of the IEEE Trans. Neural Netw. and Learning Syst. (TNNLS). He was an Editor of IEEE Trans. Wireless Commun. (TWireless) from 2012 to 2017, an Editor of the IEEE Trans. Commun. (TCom) from 2015 to 2017. He has been serving as the Technical Program Committee Chair of 7 consecutive IEEE GLOBECOM Workshops on Emerging Technologies for 5G ('12-'18). He served as the Vice-Chair, Americas of the IEEE Technical Committee on Green Communications & Computing (TCGCC) from 2017 to 2019. Currently, he is an Elected Member of Executive Committee of National Spectrum Consortium and an Elected Member of the IEEE Signal Processing Society SPCOM Technical Committee.

Lingjia Liu has 200+ publications including 3 book chapters, 90+ journal publications, 5 editorials, and 100+ conference papers. He has numerous technical contributions to major 4G standards including both 3GPP LTE/LTE-Advanced and IEEE 802.16m. He has 20+ granted U.S. patents with 20+ pending applications, and 10+ essential intellectual property rights (IPRs) in major 4G standards. His research receives including 8 Best Paper Awards. Currently, his research is sponsored by many programs from various agencies including NSF/DARPA Real-Time Machine Learning (RTML) Program, NSF/Intel Partnership on Machine Learning for Wireless Networking Systems (MLWiNS) Program, DARPA Open, Programmable, Secure 5G (OPS-5G) Program, AFRL/AFOSR University Center of Excellence (UCoE) on Machine Learning for Waveform Design, and IARPA Securing Compartmented Information with Smart Radio Systems (SCISRS) Program. His research efforts have been supported in part by over $125 M in research funding, with Lingjia Liu serving as the principal investigator (PI) on more than $14 M federal research grants (personal share $8+ M).

What's New:

Available positions: research assistant positions are available for self-motivated Ph.D. students who are interested in conducting research on the topic of signal processing, machine learning and networking for Fall 2022 (click for details).

[Paper Acceptance] December 30, 2021: Our paper, Reservoir Computing Meets Extreme Learning Machine in Real-Time MIMO-OFDM Receive Processing, has been accepted to IEEE Trans. Commun. (TCOM) Congratulations Lianjun and Zhou!

[Ph.D. Defense] December 8, 2021: Our group member, Bodong Shang, successfully defended his Ph.D. dissertation and becomes Dr. Shang. Congratulations Dr. Shang! The title of Bodong's dissertation is “Unmanned Aerial Vehicles and Edge Computing in Wireless Networks”. He is the 12th Ph.D. graduated from our group. He will be working as a joint PostDoctoral Research Associate from Princeton Univresity and Virginia Tech.

[Paper Acceptance] December 3, 2021: Our paper, Real-time Machine Learning for Symbol Detection in MIMO-OFDM Systems, has been accepted to IEEE INFOCOM 2022. Congratulations Donald and Lianjun!

[Faculty Position] December 1, 2021: Our group member, Dr. Yanjun Pan, will be joining the Computer Science and Computer Engineering (CSCE) Dept. at the University of Arkansas as a tenure-track assistant professor in Spring 2022. Congratulations Yanjun!

More news can be found HERE.

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start.txt · Last modified: 2022/01/05 18:04 by lingjialiu