About Me
Tao Han is an Associate Professor in the Department of Electrical and Computer Engineering at New Jersey Institute of Technology (NJIT) and an IEEE Senior Member. Before joining NJIT, Dr. Han was an Assistant Professor in the Department of Electrical and Computer Engineering at the University of North Carolina at Charlotte. Dr. Han received his Ph.D. in Electrical Engineering from NJIT in 2015 and is the recipient of NSF CAREER Award 2021, Newark College of Engineering Outstanding Dissertation Award 2016, NJIT Hashimoto Prize 2015, and New Jersey Inventors Hall of Fame Graduate Student Award 2014. His papers win IEEE International Conference on Communications (ICC) Best Paper Award 2019 and IEEE Communications Society’s Transmission, Access, and Optical Systems (TAOS) Best Paper Award 2019. His research interest includes mobile edge computing, machine learning, mobile X reality, 5G system, Internet of Things, and smart grid.
Education
Ph.D.; New Jersey Institute of Technology; Electrical Engineering; 2015
M.E.; Beijing University of Posts of Telecommunications; Computer Engineering; 2009
B.E.; Dalian University of Technology; Electrical and Computer Engineering ; 2006
M.E.; Beijing University of Posts of Telecommunications; Computer Engineering; 2009
B.E.; Dalian University of Technology; Electrical and Computer Engineering ; 2006
Experience
The University of North Carolina at Charlotte
Assistant Professor, August 2015 - July 2021
Awards & Honors
2021 NSF CAREER Award, National Science Foundation
2019 IEEE International Conference on Communications (ICC) Best Paper Award, IEEE
2019 IEEE Communications Society’s Transmission, Access, and Optical Systems (TAOS) Best Paper Award , IEEE
2019 IEEE International Conference on Communications (ICC) Best Paper Award, IEEE
2019 IEEE Communications Society’s Transmission, Access, and Optical Systems (TAOS) Best Paper Award , IEEE
2023 Spring Courses
ECE 417 - ELECT AND COMP ENGR PROJ II
ECE 698 - ST: APPLIED MACHINE LEARNING FOR SELF-DRIVING CARS
ECE 726 - INDEPENDENT STUDY II
ECE 790A - DOCTRL DISSRTN & RESEARCH
ECE 792B - PRE-DOCTORAL RESEARCH
ECE 790B - DOCTRL DISSRTN & RESEARCH
ECE 698 - ST: APPLIED MACHINE LEARNING FOR SELF-DRIVING CARS
ECE 726 - INDEPENDENT STUDY II
ECE 790A - DOCTRL DISSRTN & RESEARCH
ECE 792B - PRE-DOCTORAL RESEARCH
ECE 790B - DOCTRL DISSRTN & RESEARCH
Teaching Interests
Mobile Computing System
Applied Machine Learning
Wireless Networks
Applied Machine Learning
Wireless Networks
Research Interests
Machine learning for next-generation wireless networking and computing systems
Mobile mixed/augmented/virtual reality (MR/AR/VR) with edge computing
Internet of Things (IoT), smart grid, and Blockchain system
Mobile mixed/augmented/virtual reality (MR/AR/VR) with edge computing
Internet of Things (IoT), smart grid, and Blockchain system
Conference Proceeding
DeepMix: mobility-aware, lightweight, and hybrid 3D object detection for headsets
2022
Distredge: Speeding up convolutional neural network inference on distributed edge devices
2022
Constraint-Aware Deep Reinforcement Learning for End-to-End Resource Orchestration in Mobile Networks
2021
DeepMix: A Real-time Adaptive Virtual Content Registration System with Intelligent Detection
2021
FLeX: Trading Edge Computing Resources for Federated Learning via Blockchain
2021
LiveMap: Real-Time Dynamic Map in Automotive Edge Computing
2021
OnSlicing: online end-to-end network slicing with reinforcement learning
2021
2022
Distredge: Speeding up convolutional neural network inference on distributed edge devices
2022
Constraint-Aware Deep Reinforcement Learning for End-to-End Resource Orchestration in Mobile Networks
2021
DeepMix: A Real-time Adaptive Virtual Content Registration System with Intelligent Detection
2021
FLeX: Trading Edge Computing Resources for Federated Learning via Blockchain
2021
LiveMap: Real-Time Dynamic Map in Automotive Edge Computing
2021
OnSlicing: online end-to-end network slicing with reinforcement learning
2021
Journal Article
Salahdine, Fatima, & Opadere, Johnson, & Liu, Qiang, & Han, Tao, & Zhang, Ning, & Wu, Shaohua (2021). A survey on sleep mode techniques for ultra-dense networks in 5G and beyond. Computer Networks, 201, 108567.
Yousefvand, Mohammad, & Han, Tao, & Ansari, Nirwan, & Khreishah, Abdallah (2017). Distributed energy-spectrum trading in green cognitive radio cellular networks. IEEE Transactions on Green Communications and Networking, 1(3), 253--263.
Yousefvand, Mohammad, & Han, Tao, & Ansari, Nirwan, & Khreishah, Abdallah (2017). Distributed energy-spectrum trading in green cognitive radio cellular networks. IEEE Transactions on Green Communications and Networking, 1(3), 253--263.