Academic Profile : Faculty

Prof Liu Yang
Professor, College of Computing & Data Science
President’s Chair in Computer Science and Engineering
Executive Director for Cyber Research Programme Office (CRPO), Cyber Research Programme Office (CRPO)
Executive Director for Cyber Security Research Centre @ NTU (CYSREN), Cyber Security Research Centre @ NTU (CYSREN)
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Dr. Liu Yang is a full professor in Nanyang Technological University, Executive Director of Cyber Security Research Centre @ NTU, and Executive Director of CyberSG R&D Programme Office (CRPO). In 2019, he received the University Leadership Forum Chair professorship at NTU, the President's Chair in 2024.
Dr. Liu specializes in software engineering, cybersecurity and artificial intelligence. His research has bridged the gap between the theory and practical usage of program analysis, data analysis and AI to evaluate the design and implementation of software for high assurance and security. Many of his research has been successfully commercialized. By now, he has more than 600 publications in top tier conferences and journals, 30+ best paper awards and one most influence system award in top software engineering conferences. He is also leading several major research centers and programs including Cysren, CRPO, Trustworthy AI in NTU (TAICeN) and CREATE center with ICL on medical device security. He has received a number of prestigious awards including MSRA Fellowship, TRF Fellowship, Nanyang Assistant Professor, Tan Chin Tuan Fellowship, Nanyang Research Award, ACM Distinguished Speaker, NRF Investigatorship and NTU Innovator (Entrepreneurship) Award.
Dr. Liu specializes in software engineering, cybersecurity and artificial intelligence. His research has bridged the gap between the theory and practical usage of program analysis, data analysis and AI to evaluate the design and implementation of software for high assurance and security. Many of his research has been successfully commercialized. By now, he has more than 600 publications in top tier conferences and journals, 30+ best paper awards and one most influence system award in top software engineering conferences. He is also leading several major research centers and programs including Cysren, CRPO, Trustworthy AI in NTU (TAICeN) and CREATE center with ICL on medical device security. He has received a number of prestigious awards including MSRA Fellowship, TRF Fellowship, Nanyang Assistant Professor, Tan Chin Tuan Fellowship, Nanyang Research Award, ACM Distinguished Speaker, NRF Investigatorship and NTU Innovator (Entrepreneurship) Award.
For cybersecurity, we are working at malware modeling, detection, classification and generation with the focus on Javascript malware, desktop malware and Android malware. We are developing tools for vulnerability modeling and detection using machine learning and (both static and dynamic) program analysis on binary code. In our Securify research project (2015 - 2020), we are performing formal verification on security system from hardware, hypervisor, programs to security protocol using different verification approaches. Recently, we embark on the research on Automotive Security and autonomous vehicle Security in their security design, runtime security monitoring and response, and also the security testing and certification.
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.
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.
- AI-based Software Analysis for Security and Reliability
- Autonomous AI Agent Network on Blockchain
- Holistic and Practical Remediation of Software Vulnerability
- IN-CYPHER (IMPERIAL/NTU CYBER PROTECTION FOR HEALTHCARE)
- President's Chair in Computer Science and Engineering
- Security Analysis of Future Software
- The Science of Certified AI Systems
- Theme 3: Algorithms for Privacy, Security and Provenance
- Thrust B: Artificial Intelligence and Software Engineering (IAF-ICP)
- Thrust B: Artificial Intelligence and Software Engineering (RCA)
- Towards Building Unified Autonomous Vehicle Scene Representation for Physical AV Adversarial Attacks and Visual Robustness Enhancement
- TrustFUL: Trustworthy Federated Ubiquitous Learning
- TrustFUL: Trustworthy Federated Ubiquitous Learning (SCSE)
- TRUSTWORTHY AI CENTRE NTU (TAICeN)
- TRUSTWORTHY AI CENTRE NTU (TAICeN) (NTU)
- TRUSTWORTHY AI CENTRE NTU (TAICeN) (NUS)
- TRUSTWORTHY AI CENTRE NTU (TAICeN) (SMU)