Wallenberg-NTU PPF 2019-2021

Chen Ci

Chen Ci

School of Electrical and Electronic Engineering, NTU
Previous Affiliation: PhD, Guangdong University of Technology, UK.
Email: [email protected]
Homepage: https://sites.google.com/view/cichen/biography


Ci Chen received the B.E. and Ph.D. degrees from School of Automation, Guangdong University of Technology, Guangzhou, China, in 2011 and 2016, respectively. From 2016 to 2018, he was with The University of Texas at Arlington, USA and The University of Tennessee at Knoxville, USA, as a Research Associate. He is now a Wallenberg-NTU Presidential Postdoctoral Fellow with School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore. He serves as a Subject Editor for International Journal of Robust and Nonlinear Control and an Associate Editor for Advanced Control for Applications: Engineering and Industrial Systems.

Research Interests: Reinforcement learning for feedback control


PPF Project: Towards a Reinforcement Learning Framework for Efficient Decision Making of Heterogeneous Networked Autonomous Systems
Abstract: In modern-day society, different subgroups are interacting with each other for realizing a common goal. Examples are found in the ground and aerial vehicles for a disaster rescue operation and also in multiple energy sources connecting to the grid for the power supply. However, the lack of global situational awareness intends to fall into the trap of a nearly local objective against a global objective, which makes heterogeneous networks prone to an unreliable decision in a certain context. This research will seek a new reinforcement learning structure to cooperatively and efficiently coordinate agents in heterogeneous networked autonomous systems.
​Li Haoliang

Li Haoliang

School of Electrical and Electronic Engineering, NTU
Previous Affiliation: PhD, NanyangTechnological University, Singapore.
Email: [email protected]
Homepage: -


Dr Haoliang obtained his B.Eng degree from University of Electronic Science and Technology of China in 2013, and the Ph.D. degree from Nanyang Technological University, Singapore, in 2018. He was a project officer in 2018 and a research fellow from July 2018 to May 2019 in Rapid-Rich Object Search Lab, NTU. He is now a Wallenberg-NTU presidential postdoc fellow in NTU. He received the doctorate innovation award from NTU in 2019.

Research Interests: AI security, multimedia forensics


PPF Project: improving Face Recognition Security based on AI
Abstract: Biometrics has nowadays become the universal interest in the areas such as forensics and identification. Among the various biometrics information (fingerprint, face, palm, veins, iris, gait), “face" is the most popular one as face recognition only needs a camera which is available on most of the smart-phones. Due to the rapid development of face recognition technology (e.g. deep learning), face recognition has been applied to many applications, such as mobile security (e.g. phone unlocking), financial transaction based on mobile phone (e.g. Alipay, WeBank), etc. Despite the success of face recognition system, it is vulnerable to spoofing attack which can be conducted with a special medium. An attacker can easily bypass the face recognition system with a printed photo/replay video/3d mask of an authenticated user. Due to the security issue raised by face spoofing, face anti-spoofing has recently emerged as an active topic with great significance for both academia and industry. However, the current methods of face spoofing detection either limited their scope to only traditional attack (photo/video) or lacked of generation capability, which did not meet the requirement of industrial application. In this proposal, I aim to study more sophisticated attack based on artificial intelligence and to improve the generalization capability of face spoofing detection by leveraging the advantage of machine learning.


​Sun Chao

Sun Chao

School of Electrical and Electronic Engineering, NTU
Previous Affiliation: PhD, Nanyang Technological University, Singapore.
Email: [email protected]
Homepage: -


Chao Sun received his B.Eng degree from University of Science and Technology of China in 2013. Then he obtained the PhD degree from School of Electrical and Electronics Engineering, Nanyang Technological University, Singapore in 2018, supervised by Prof. Guoqiang Hu. After graduation, he worked as a research fellow at Nanyang Technological University till May 2019. Currently, he is a Wallenberg-NTU Presidential Postdoctoral Fellow at Nanyang Technological University.

Research Interests:His research interests include cooperative control of multi-agent systems, distributed optimization, online optimization and noncooperative games.


PPF Project: Distributed Time-varying Optimization with Applications to Swarm Robots
Abstract: Centralized optimization has been widely used in robotic related applications. For example, in trajectory optimization problems and collision avoidance problems. However, centralized optimization methods use global information, which may bring large communication and computation burden, especially when the scale of the robots is large. This project aims to study distributed optimization and online optimization based techniques for coordination and performance optimization of swarm robots, and propose improved algorithms for applications in coordinated trajectory tracking control, formation control, and collaborative exploration and surveillance, etc.
​Xie Xiaofei

Xie Xiaofei

School of Electrical and Electronic Engineering, NTU
Previous Affiliation: PhD, Tianjin University, China.
Email: [email protected]
Homepage: https://xiaofeixie.bitbucket.io


Xiaofei Xie is a presidential postdoctorial fellow in Nanyang Technological University, Singapore. He received Ph.D from Tianjin University. He won the CCF Outstanding Doctoral Dissertation Award in China. His research mainly focus on program analysis, loop analysis, traditional software testing and security analysis of artificial intelligence. He has made some top tier conference/journal papers relevant to software analysis in ISSTA, FSE, TSE, ICSE, AAAI, IJCAI and CCS. In particular, he won two ACM SIGSOFT Distinguished Paper Awards.

Research Interests: Program analysis, software security, program verification and quality assurance of deep learning systems


PPF Project: Enhancing the Resilience of Deep Learning Models used for Cyber-Security against Adversarial Attacks
Abstract: Over the last decade, deep learning has become an integral part of artificial intelligence. It has enabled great leaps of progress in the domains of computer vision, robotics, finance, medicine, and more. However, these deep learning models are often trained and executed without considering the possibility of a malicious actor. Such an actor can abuse this powerful tool at any point of its life cycle. For example, the attacker may evade detection, force a system to cause damage, or even reveal confidential information contained within its training data. Although multiple defence techniques exist, they either apply to computer vision problems, or can be evaded by countering the countermeasures. Therefore, to better secure deep neural networks, we must develop the necessary tools to form a proactive arms-race. In this way, we can safely rely on deep neural networks to perform sensitive tasks and behave as expected. By implementing these tools, we will be able to fully utilize deep learning to further improve our quality of life.
Xu Qianwen

Xu Qianwen

School of Electrical and Electronic Engineering, NTU
Previous Affiliation: PhD, National University of Singapore, Singapore.
Email: [email protected]
Homepage: https://sites.google.com/view/qianwenxu/home


Dr. Qianwen Xu received the B.Sc. degree from Tianjin University, China in 2014 and PhD degree from Nanyang Technological University, Singapore in 2018, both in electrical engineering. She has worked as a research associate in Hong Kong Polytechnic University and a postdoc research fellow in Aalborg University. Currently, she is a Wallenberg-NTU Presidential Postdoc Fellow in Nanyang Technological University in Singapore. She is awarded the Wallenberg-NTU Presidential Postdoc Fellowship, Humboldt Research Fellowship for Postdoctoral Researchers, Chinese Government Award for Outstanding Self-Financed Students Abroad, Excellent Doctorate Research Work in Nanyang Technological University, etc. Her research interests include control, stability, reliability and optimization of microgrids and smart grids. In this area, she has published 10 journal papers in IEEE Transactions as first author

Research Interests: Control, stability, reliability and optimization of microgrids and smart grids


PPF Project: Attack-resilient Coordinated Control and Stabilization for Cyber-physical Microgrids
Abstract: : As a promising smart grid technology, microgrid has attracted great attention in the modern grid for the renewable energy integration as well as the transportation electrification. The microgrid is a typical cyber-physical system with sophisticated software-based control and communication networks. The attacks in cyber system may cause instability or even disruption of the whole microgrid. Considering the large amount of complex data in the microgrid cyber system for forecasting and optimization as well as the tightly coupled cyber and physical system, artificial intelligence technologies (i.e., generative adversarial network and reinforcement learning) will be employed together with advanced control methods to ensure the stable and resilient operation of microgrids under cyberattacks. An attack resilient framework will be developed in this project for cyber-physical microgrids, for detection, control and stabilization of the system under cyberattacks.