Academic Profile

Jun Zhao is an Assistant Professor in the School of Computer Science and Engineering (SCSE) at Nanyang Technological University (NTU). He received a PhD degree in Electrical and Computer Engineering from Carnegie Mellon University (CMU), Pittsburgh, PA, USA in May 2015, and a bachelor's degree in Information Engineering from Shanghai Jiao Tong University, China in June 2010. One of his papers was a finalist for the best student paper award in IEEE International Symposium on Information Theory (ISIT) 2014. His research interests include the following:
• AI and Data Science: federated learning, deep learning, adversarial machine learning, computer vision (CV), natural language processing (NLP), reinforcement learning, optimization, etc.
• City Brain and Smart Nation: federated learning, Internet of Things IoT, cloud/edge/fog computing, 6G wireless communications, signal processing, smart grid, cyber-physical systems CPS
• Security and Privacy: federated learning, blockchains, adversarial machine learning, differential privacy, applied cryptography, secure multi-party computation

Prospective PhD students, postdocs, and visiting students/researchers can
email JunZhao@NTU.edu.sg,
or add WhatsApp request at http://www.ntu.edu.sg/home/junzhao/whatsapp.png
or add Wechat request at http://www.ntu.edu.sg/home/junzhao/wechat.png
junzhao_1_2.JPG picture
Asst Prof Zhao Jun
Assistant Professor, School of Computer Science and Engineering

• AI and Data Science: federated learning, deep learning, adversarial machine learning, computer vision (CV), natural language processing (NLP), reinforcement learning, optimization, etc.
• City Brain and Smart Nation: federated learning, Internet of Things IoT, cloud/edge/fog computing, 6G wireless communications, signal processing, smart grid, cyber-physical systems CPS
• Security and Privacy: federated learning, blockchains, adversarial machine learning, differential privacy, applied cryptography, secure multi-party computation
 
  • Blockchain Empowered Internet of Vehicles towards Intelligent Transportation

  • Blockchain Theory and Practice: Security, Scalability and Novel Applications

  • Collecting and Analyzing Data from Users with Strong Privacy Protection

  • Combinatorial Stochastic Analysis for the Connectivity of Random Graphs - Applications to Vehicular and Wireless Networks

  • Cyber-Physical Attacks in Transmission Systems Using Digital Twin

  • High-performance, High-energy-efficiency and High-reliability (H3) based Smart Air-Balancing System with Artificial Intelligence (AI), Internet of things (IoT) and Fault Detection & Diagnostics (FDD)Technologies

  • Intelligent Reflecting Surface Aided Wireless Networks with Mobile Edge Computing

  • Large Vertical Take-Off & Landing (VTOL) Research Platform:Prototype development and demonstration

  • Leveraging Blockchains for Secure and Privacy-Aware Distributed Machine Learning

  • Robustness Certification and Training of Deep Neural Networks
 
  • Jun Zhao. (2019). A Survey of Intelligent Reflecting Surfaces (IRSs): Towards 6G Wireless Communication Networks. arXiv, .

  • Huimei Han, Jun Zhao, Dusit Niyato, Marco Di Renzo, Quoc-Viet Pham. (2019). Intelligent Reflecting Surface Aided Network: Power Control for Physical-Layer Broadcasting. arXiv, .

  • Jun Zhao. (2019). Optimizations with Intelligent Reflecting Surfaces (IRSs) in 6G Wireless Networks: Power Control, Quality of Service, Max-Min Fair Beamforming for Unicast, Broadcast, and Multicast with Multi-antenna Mobile Users and Multiple IRSs. arXiv, .

  • Jun ZHAO. (2019). tbd.

  • Ning Wang, Xiaokui Xiao, Yin Yang, Jun Zhao, Siu Cheung Hui, Hyejin Shin, Junbum Shin, and Ge Yu. (2019). Collecting and analyzing multidimensional data with local differential privacy. IEEE 35th Annual International Conference on Data Engineering (ICDE).