|Academic Profile |
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Prof Liu Yang
Professor, School of Computer Science and Engineering
|Dr. Yang Liu obtained his bachelor and ph.d degree in the National University of Singapore in 2005 and 2010, respectively. In 2012, he joined Nanyang Technological University as a Nanyang Assistant Professor. He is currently a full professor, director of the cybersecurity lab, Program Director of HP-NTU Corporate Lab and Deputy Director of the National Satellite of Excellence of Singapore. In 2019, he received the University Leadership Forum Chair professorship at NTU.|
Dr. Liu specializes in software verification, security and software engineering. His research has bridged the gap between the theory and practical usage of formal methods and program analysis to evaluate the design and implementation of software for high assurance and security. By now, he has more than 270 publications in top tier conferences and journals. He has received a number of prestigious awards including MSRA Fellowship, TRF Fellowship, Nanyang Assistant Professor, Tan Chin Tuan Fellowship, Nanyang Research Award (Young Investigator) 2018, NRF Investigatorship 2020 and 10 best paper awards and one most influence system award in top software engineering conferences like ASE, FSE and ICSE.
For software engineering, we are working on the topics related to program specification learning and model learning, performance analysis, Android energy analysis, reliability analysis, code clone analysis, program debugging, program testing, automatic loop analysis, testing and validating deep learning algorithms using techniques like model checking, symbolic execution and machine learning. We are building tools related to these aspects. For Android system, we have been working on security analysis on App malware detection & classification, generation and data analytic, App vulnerability analysis, App testing, Android OS testing and fuzzing, and Automatic UI generation.
For multi-agent systems, we are working on the topics related to formal modeling of various multi-agent systems, particularly trust management systems and their analysis in correctness, security and robustness.
For big data, we are promoting the concept called event analytic based on behavior learning and analysis, and their applications in sports and finance systems.
- 2019 University Leadership Forum Chair in Computer Science and Engineering (Liu Yang)
- AI for SW Engineering
- An Empirical Evaluation of GDPR Compliance Violations in Mobile Apps and IoT Devices
- Automatic Checking and Verification of Security Protocol Implementations
- Automatic Open Source Component Detection and Security Risk Management for Automotive Systems
- BINSEC: Binary Analysis for Security
- Building Security Tools for Investigating and Introspecting Applications in Trusted Execution Environment
- Cloud-based Mobile App Testing Service
- Cyber Security Technologies for Automotive Electronics/Autonomous Vehicles
- Distributed Plant Modeling, fault Diagnosis, And Supervisor Control Of Large Scale Automated Maunfacturin Systems
- EDEX GRANT
- Enhancing Cyber Resilience of Deep Learning Models against Adversarial Cyber Attacks
- Formal Modeling and Analysis of Collaborative Security
- Improving Cybersecurity through Optimal Policy Design and Human Behaviour Modelling
- Mobile (iOS) Security Study for Cyber-Attack Prevention
- National Satellite of Excellence in Trustworthy Software Systems
- Productive Failure via Educational Games for Tertiary Education
- Robust Control of Large Scale Concurrent Systems with Unreliable Resources
- Robust Deep Learning Using Symbolic Abstractions
- Scalable Malware and Vulnerability Analysis Using Program Metrics
- Security Enhancements For ATM And POS Systems
- Smart Binary-level Vulnerability Assessment for Cyber-attack Prevention
- Software Vulnerability Discovery Tool Building
- Thrust B: Artificial Intelligence and Software Engineering (IAF-ICP)
- Thrust B: Artificial Intelligence and Software Engineering (RCA)
- Towards Building Trustworthy and Robust Intelligent Systems and Its Application on Human Brain
- VULNERABILITY DETECTION IN BINARY CODE
- Vulnerability Detection in Binary Code
- Y Luo, Y Yu, Z Jin, Y Li, Z Ding, Y Zhou, Y Liu. (2020). Privacy-aware UAV flights through self-configuring motion planning. 2020 IEEE International Conference on Robotics and Automation.
- K. Cheng, Y. Bai, Y.Zhou, Y. Tang, D. Sanan, Y. Liu. (2020). CANeleon: Protecting CAN Bus with Frame ID Chameleon. IEEE Transactions on Vehicular Technology , .
- Jianwen Sun, Tianwei Zhang, Xiaofei Xie, Lei Ma, Yan Zheng, Kangjie Chen, Yang Liu. (2020). Stealthy and Efficient Adversarial Attacks against Deep Reinforcement Learning. Proceedings of the 34th AAAI Conference on Artificial Intelligence (AAAI 2020).
- Y Zhou, H Hu, Y Liu, S-W Lin, and Z Ding. (2020). A distributed method to avoid higher-order deadlocks in multi-robot systems. Automatica, 112.
- Jianwen Sun, Yan Zheng, Jianye Hao, Zhaopeng Meng, Yang Liu. (2020). Continuous Multiagent Control using Collective Behavior Entropy for Large-Scale Home Energy Management. Proceedings of the 34th AAAI Conference on Artificial Intelligence (AAAI 2020).