Academic Profile

Academic Profile

Asst Prof Zhao Jun

Assistant Professor, School of Computer Science and Engineering

Email: junzhao@ntu.edu.sg
Asst Prof Zhao Jun

Biography
For up-to-date information, please visit the website http://JunZhaoGroupNTU.github.io/

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
Research Interests
• 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
Current Projects
  • Advancing Privacy-Preserving Machine Learning in Theory and Applications
  • Blockchain Theory and Practice: Security, Scalability and Novel Applications
  • Collecting and Analyzing Data from Users with Strong Privacy Protection
  • 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
  • How Smart are Blockchain-based Smart Contracts? Evidence from the Finance Industry
  • 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
Selected Publications
  • Jun Zhao. (2021). For up-to-date information, please visit http://JunZhaoGroupNTU.github.io/. Group Website, .
  • Helin Yang, Zehui Xiong, Jun Zhao, Dusit Niyato, Chau Yuen, and Ruilong Deng. (2021). Deep Reinforcement Learning Based Massive Access Management for Ultra-Reliable Low-Latency Communications. IEEE Transactions on Wireless Communications, .
  • Helin Yang, Zehui Xiong, Jun Zhao, Dusit Niyato, Qingqing Wu, H. Vincent Poor. (2021). Intelligent Reflecting Surface Assisted Anti-Jamming Communications: A Fast Reinforcement Learning Approach. IEEE Transactions on Wireless Communications, .
  • Helin Yang, Zehui Xiong, Jun Zhao, Dusit Niyato, Liang Xiao, Qingqing Wu. (2021). Deep Reinforcement Learning Based Intelligent Reflecting Surface for Secure Wireless Communications. IEEE Transactions on Wireless Communications, .
  • Yang Liu, Jun Zhao, Ming Li, Qingqing Wu. (2020). Intelligent Reflecting Surface Aided MISO Uplink Communication Network: Feasibility and Power Minimization for Perfect and Imperfect CSI. IEEE Transactions on Communications, .

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