Academic Profile : Faculty

Asst Prof Zhao Jun.JPG picture
Asst Prof Zhao Jun
Assistant Professor, School of Computer Science and Engineering
External Links
 
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 https://junzhaogroupntu.github.io/images/whatsapp.png
or add Wechat request at https://junzhaogroupntu.github.io/images/wechat.png
• 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
  • Combinatorial Stochastic Analysis for the Connectivity of Random Graphs - Applications to Vehicular and Wireless Networks
  • Cyber-Physical Attacks in Transmission Systems Using Digital Twin
  • 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