Tao Han

Tao Han

Associate Professor

New Jersey Institute of Technology

Tao Han is an associate professor in the Helen and John C. Hartmann Department of Electrical and Computer Engineering at the New Jersey Institute of Technology (NJIT) where he earned his Ph.D. in Electrical Engineering. Before joining NJIT, he was an assistant professor in the Electrical and Computer Engineering Department at the University of North Carolina at Charlotte (UNCC). At NJIT, he directs the Ubiquitous Networking and Intelligent Computing System (UNICS) Lab focusing on the design and development of new network protocols and machine learning algorithms for next-generation wireless networks and edge computing systems. He wins the prestigious NSF CAREER Award 2021 and is an IEEE senior member.

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

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Latest News

  • Congratulations to Yang! He starts his career as a research scientist with Nokia Bell Labs at Murray Hills, NJ.
  • Congrats! Our paper “Atlas: Automate Online Service Configuration in Network Slicing” is accepted for presentation at ACM CoNEXT 2022.
  • Congrats! Our paper “NeuLens: Spatial-based Dynamic Acceleration of Convolutional Neural Networks on Edge” is accepted for presentation at ACM MobiCom 2022.
  • Congrats! Our paper “DeepMix: Mobility-aware, Lightweight, and Hybrid 3D Object Detection for Headsets” is accepted for presentation at ACM MobiSys 2022.
  • Congrats! Our paper “DistrEdge: Speeding up Convolutional Neural Network Inference on Distributed Edge Devices” is accepted for presentation at IEEE IPDPS 2022.
  • Congrats! Our paper “Deep Reinforcement Learning for End-to-End Network Slicing: Challenges and Solutions” is accepted for publicaiton in IEEE Network.
  • Congrats! Pedro will work as an intern at Google at Mountain View, CA, during summer 2022.
  • Congrats! Yang will work as an intern at Nokia Bell Labs at Murray Hills, NJ, during summer 2022.
  • Congrats! Our paper “Towards Secure and Intelligent Network Slicing for 5G Networks” is accepted for publicaiton in IEEE Open Journal of the Computer Society.
  • Congrats! Our paper “OnSlicing: Online End-to-End Network Slicing with Reinforcement Learning” is accepted for presentation at ACM CoNEXT 2021.
  • Congrats! Our paper “Constraint-Aware Deep Reinforcement Learning for End-to-End Resource Orchestration in Mobile Networks” is accepted for presentation at IEEE ICNP 2021.
  • Congrats! Our paper “Towards Revenue-Driven Multi-User Online Task Offloading in Edge Computing” is accepted for publication in IEEE Transactions on Parallel and Distributed Systems.
  • Congrats! Our paper “Survey on Sleep Mode Techniques for Ultra-Dense Networks in 5G and Beyond” is accepted for publication in Elsevier Computer Networks.
  • Dr. Qiang Liu joined the Department of Computer Science and Engineering, University of Nebraska - Lincoln as a tenure track assistant professor in August 2021.
  • Dr. Tao Han received the prestigious NSF CAREER Award to study domain-specific deep reinforcement learning technologies for network automation in wireless edge computing networks.
  • Congrats! Our paper “LiveMap: Real-Time Dynamic Map in Automotive Edge Computing” has been accepted to present at IEEE INFOCOM 2021.
  • Congrats! Qiang has successfully defended his Ph.D. dissertation and will join Nokia Bell Labs as a Member of Technical Staff starting from Jan. 2021.
  • Congrats! Pedro has been selected as “Charlotte INNO under 25” who are a collection of Charlotte’s best and brightest young tech leaders.
  • Our paper “EdgeSlice: Slicing Wireless Edge Computing Network with Decentralized Deep Reinforcement Learning” is accepted for presentation at IEEE ICDCS, 2020. (acceptance rate: 18%)
  • Our paper “TrustServing: A Quality Inspection Sampling Approach for Remote DNN Services” is accepted for presentation at IEEE SECON, 2020. (acceptance rate: 27.9%)

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