جستجوی استاد راهنمای دانشگاهی

LU Wen Feng is an Adjunct Associate Professor in the Department of Mechanical Engineering at the National University of Singapore (NUS), affiliated with the College of Design and Engineering. His research focuses on advanced manufacturing technologies, including additive manufacturing, robotics, and AI-driven systems. He explores sustainable design methodologies, smart manufacturing innovations, and bioprinting applications. Key areas include optimizing material processes, enhancing mechanical properties of printed materials, and developing autonomous robotic solutions for industrial tasks. Contact: mpelwf@nus.edu.sg , located at E3-02-07. Research Interests : His work bridges AI and manufacturing, emphasizing Knowledge graph integration for additive manufacturing, Autonomous robotic systems in industrial settings, Bioprinting for tissue repair with smart bioinks, Topology optimization for lightweight and sustainable structures, Material characterization and process engineering for 3D-printed composites. Recent Article Trends : LU Wen Feng's 2025 articles highlight advancements in AI-augmented manufacturing systems (e.g., MaViLa, AutoMEX) and sustainable design workflows. His 2024 studies address material anisotropy, corrosion behavior, and topology optimization strategies for lattice structures. These trends reflect his interdisciplinary approach to solving challenges in additive manufacturing, robotics, and biomedical applications. Awards : No scientific awards explicitly mentioned. Advising & Grants : No current graduate students or grants listed. His research likely integrates industry-academia collaborations given the focus on applied manufacturing technologies. Labs/Teams : Not explicitly detailed, but his work suggests involvement in advanced manufacturing labs and AI-robotics teams at NUS.

• Additive Manufacturing
• Robotics
• Smart Manufacturing
• +۴ مورد دیگر

Yintong Huo is a tenure-track Assistant Professor in the Department of Computer Science at Singapore Management University (SMU), School of Computing and Information Systems. He joined SMU in early 2024 after completing his PhD at The Chinese University of Hong Kong (CUHK) under Prof. Michael R. Lyu. His academic journey includes a Bachelor's degree from the University of Electronic Science and Technology of China. Education: PhD in Computer Science and Engineering, The Chinese University of Hong Kong (2024) Bachelor's degree, University of Electronic Science and Technology of China Huo's research focuses on intelligent software engineering , particularly empowering AI models (especially LLMs) for software development, testing, and operations. His work spans AI4SE, LLM4SE, AIOps, code intelligence, and multimodal software engineering . Two flagship projects define his current research: LogPAI - an open-source AI platform for automated log analysis adopted by leading tech companies, and WebPAI - a multimodal intelligence project for automatic webpage development. His research addresses critical challenges in software reliability, log analysis, and UI code generation through innovative applications of AI. His recent publications reveal a strong trend toward multimodal approaches in software engineering , combining vision and language models for UI code generation, and increasingly sophisticated applications of LLMs for log analysis and software reliability. Huo's work demonstrates exceptional impact, with multiple papers accepted at top-tier venues including ASE, ICSE, and FSE with high acceptance rates (e.g., 9.5% for ASE'25). Scientific Awards: ICSE Distinguished Reviewer Award (2025) ISSRE Distinguished Reviewer Award (2024) IEEE Open Software Services Award (2022, for LogPAI with 3k+ GitHub stars and 70k+ downloads) ACM SIGSOFT CAPS Travel Grants (ASE'23, ICSE'24, FSE'24) Nomination for Best Teaching Assistant Award (2022) National Scholarship (2019) Huo actively mentors students at multiple levels, currently supervising PhD students Shi Ying Chang and Dan Huang (co-supervised with Prof. David Lo), research engineer Minxing Wang, and visiting students including Shiwen Shan. His undergraduate mentee Truong Hai Dang will intern at Apple Inc. He maintains strong industry connections, with his LogPAI project adopted by world-leading tech companies. Huo serves on program committees for major conferences including ASE'25, ICSE'26, and FSE'26, and is recruiting fully-funded PhD students and research assistants for projects in AI4SE and multimodal software engineering. Huo leads the LogPAI and WebPAI research initiatives, which have evolved into substantial open-source projects with significant industry adoption. His team focuses on practical applications of AI in software engineering, with particular emphasis on reliability and usability in real-world systems. The research environment benefits from SMU's strong position in software engineering research, where the university ranks No. 2 globally in Software Engineering according to CSRankings (2020-2025).

• Intelligent Software Engineering
• AI for Software Engineering (AI4SE)
• LLM for Software Engineering (LLM4SE)
• +۷ مورد دیگر

Abhik Roychoudhury is a Provost's Chair Professor of Computer Science at the National University of Singapore (NUS), leading the Trustworthy and Secure Software (TSS) research group since 2001. His work focuses on automated program repair, software testing, security, and agentic AI. He is a Senior Advisor at SonarSource following the acquisition of his startup AutoCodeRover. He holds an ACM Fellowship and has received the ICSE Most Influential Paper Award for program repair research. Education: M.S. and Ph.D. in Computer Science from State University of New York at Stony Brook (1997-2000). Research interests include program analysis, software security, and AI-driven software engineering. His team has pioneered techniques like SemFix and Angelix for program repair, and AFLNet for protocol fuzzing. He has served as editor-in-chief of ACM TOSEM and conference chair for ICSE and FSE. Awards include the NUS Outstanding Graduate Mentor Award (inaugural recipient) and IEEE New Directions Award. His work bridges academia and industry, with contributions to projects like the DesCartes initiative for critical urban systems. Key collaborations include Microsoft on API repair and IBM on AI research centers. His recent focus includes agentic AI for software engineering, reflected in AutoCodeRover's acquisition by SonarSource.

• Software Testing
• Program Analysis
• Program Repair
• +۴ مورد دیگر

Marcel Böhme is a faculty member at the Max Planck Institute for Security and Privacy (MPI-SP) , leading the Software Security research group. His work focuses on foundational advancements in fuzzing , statistical program analysis, and scalable vulnerability discovery. Education: PhD from National University of Singapore (NUS) Research interests span: Statistical and causal frameworks for software testing Efficiency/Scalability of automated testing Fundamental limits of vulnerability detection Practical fuzzing technology (e.g., Entropic in LibFuzzer) Recent publications highlight trends in: Machine learning for security analysis Privacy-preserving statistical methods Future-proof security frameworks Protocol fuzzing with large language models Scientific accolades include: ERC Consolidator Grant (2024) NUS Outstanding Young Alumni Award (2022) ARC DECRA (2019) Multiple ACM Distinguished Paper Awards He serves as: Spokesperson for Research Group Leaders at Max Planck Society Guest Editor-in-Chief for ACM TOSEM PC Chair for ASE'25 and ISSTA'26

• Software Engineering
• Software Security
• Foundations of Program Analysis
• +۹ مورد دیگر

Bowen Xu is an Assistant Professor in the Department of Computer Science at North Carolina State University (NC State), College of Engineering. His research focuses on software engineering, machine learning, and program analysis, particularly in securing AI models and improving code quality. He holds a PhD from Singapore Management University (SMU), where he also conducted postdoctoral research. Education: PhD in Computer Science, Singapore Management University (SMU) Postdoctoral Researcher, SMU School of Computing and Information Systems Research Interests: AI for Code, Backdoor Attacks on Code Models, Vulnerability Detection Code Representation Learning, Model Compression, Safety of AI Systems Chatbot Development for Developers, Automatic Code Review Key Contributions: Developed PTM4Tag+, a Stack Overflow tag recommendation system using pre-trained models Explored stealthy backdoor attacks in code and reinforcement learning systems Pioneered work on automatic vulnerability repair using LLMs and broader input analysis Awards: 2022: Honorable Mention Award (ACSAC) 2018: Highly Commended Full Paper Award (ESEM) Service Roles: Editorial Board Member, Empirical Software Engineering Journal Program Committee Co-chair for ICSE/FSE Research Tracks Organized workshops like FORGE, MaLTeSQuE, and SEA4DQ Labs & Teams: Leads the Softmax Lab at NC State, advising 12+ students across PhD, Master's, and undergraduate levels. Alumni include industry professionals at Microsoft, Barclays, and Marvell Semiconductor.

• Software Engineering
• Machine Learning
• Program Analysis
• +۱۲ مورد دیگر

Xiaofei Xie is an Assistant Professor at the School of Computing and Information Systems (SCIS), Singapore Management University (SMU). He received his PhD from Tianjin University in 2018 and was a postdoctoral researcher at Nanyang Technological University (2018-2021) before joining SMU in 2022. His research focuses on software engineering, AI systems, and cybersecurity. Dr. Xie's primary research areas include program analysis, software testing, vulnerability detection, and quality assurance of AI systems. His work spans: Testing methodologies for autonomous systems and games AI security including backdoor detection and model robustness Automated program repair and code generation Formal methods and semantic code analysis His recent publications demonstrate strong emphasis on AI/ML system testing, cybersecurity applications, and program analysis techniques. Research trends show increasing focus on LLM-based program repair, autonomous system validation, and federated learning security. Major Awards: ACM SIGSOFT Distinguished Paper Awards (ASE'23, ISSTA'22, ASE'19, FSE'16) CCF Outstanding Doctoral Dissertation Award (2019) 3rd place in AI Singapore's Trusted Media Challenge (2022) Wallenberg-NTU Presidential Postdoctoral Fellowship (2019) APSEC Best Paper Award (2020) He currently advises 7 PhD/Master's students including CHENG Mingfei, KONG Jiaolong, and YU Jiongchi. Dr. Xie leads research in software reliability and AI security at SMU's SCIS.

• Software Engineering
• Artificial Intelligence
• Cybersecurity
• +۵ مورد دیگر

Dr. LIANG Zhenkai is an Associate Professor and Chairman of the Department of Computer Science at the National University of Singapore's School of Computing. He also serves as the Lead Principal Investigator for the National Cybersecurity R&D Lab (NCL). With extensive experience in academic leadership and cybersecurity research, Dr. Liang has established himself as a prominent figure in the field of system and software security. Dr. Liang received his Ph.D. in Computer Science from Stony Brook University in 2006 and his B.S. degrees in Computer Science and Economics from Peking University in 1999. His dual background provides a unique perspective on security challenges that bridges technical expertise with economic understanding. Dr. Liang's research focuses on system and software security , with particular emphasis on security in emerging platforms including Web, mobile, and Internet-of-Things (IoT) systems. His specific research interests include program analysis, Web and IoT system security, and virtualization. As the leader of the Curiosity Research Group, his team pursues missions centered around "Understanding systems (理解系统), abstracting knowledge (提炼知识), and connecting facts (参悟规律)". This philosophical approach to security research has yielded numerous significant contributions to the field. Dr. Liang's recent publications demonstrate a strong evolution from fundamental security mechanisms to sophisticated solutions addressing AI security, blockchain, and advanced vulnerability analysis. His work increasingly integrates machine learning techniques with traditional security approaches, focusing on developing robust defenses against sophisticated attacks while maintaining system usability. The trend shows a progression toward addressing contemporary challenges in large language models, secure system observability, and vulnerability propagation analysis. Dr. Liang has received numerous prestigious awards recognizing his research excellence: Outstanding Paper Award at ACSAC (2003) Best Paper Award at USENIX Security Symposium (2007) ACM SIGSOFT Distinguished Paper at ESEC-FSE (2009) Best Paper Award at W2SP Workshop (2014) Annual Teaching Excellence Award at NUS (2014, 2015) As an educator, Dr. Liang has taught various undergraduate and graduate courses including CS3235 Computer Security, CS5231 Systems Security, and CS5321 Network Security. His teaching philosophy, which he has published on in "Tool, Technique, and Tao in Computer Security Education," emphasizes both technical expertise and philosophical understanding of security principles. He has successfully mentored numerous students and researchers in the cybersecurity field. Dr. Liang leads the Curiosity Research Group, which actively seeks curious minds to join their exploration of security systems. The group maintains strong connections with industry and government cybersecurity initiatives, particularly through the National Cybersecurity R&D Lab (NCL). Their research environment encourages innovative thinking with the requirement that "Curiosity is required, while mentality for repairing things (such as bicycles) is a plus."

• system and software security
• Web security
• mobile security
• +۶ مورد دیگر

Shin Hwei Tan is an Associate Professor (Gina Cody Research Chair) at the Department of Computer Science and Software Engineering , Concordia University, Montreal, Canada. Previously, she worked as an Assistant Professor at the Southern University of Science and Technology (SUSTech) since June 2018. Her academic journey includes a PhD from the National University of Singapore under Abhik Roychoudhury and MS/BS degrees from the University of Illinois at Urbana-Champaign, co-advised by Darko Marinov and Lin Tan. Education: PhD in Computer Science (National University of Singapore, 2018) MS in Computer Science (University of Illinois at Urbana-Champaign, 2012) BS in Computer Science (University of Illinois at Urbana-Champaign) Her research interests span Automated Program Repair , Software Testing , Open-source Software Development , Genetic Improvement , Program Analysis , and Comment Analysis . She actively applies machine learning and formal methods to improve software reliability. Recent work includes LMDefects (Codex-generated bugs dataset), Droix (Android app repair), and Codeflaws (program repair benchmark). Her research outputs demonstrate expertise in automated patch generation , static analyzer testing , and quantum software verification . Key projects include Concoction (vulnerability prediction), SAScope (static analysis framework testing), and COMFUZZ (compiler fuzzing). She has secured significant grants including a NSERC Discovery Grant (2024–2028) and ECR Young Researcher Fund (2019). Scientific Awards: ACM-W Rising Star Award (2025) ICSE/SANER Distinguished Paper Awards (2023–2025) Google Anita Borg Memorial Scholarship (2015) David J. Kuck Outstanding MS Thesis Award (2013) Multiple Best Reviewer Awards She serves as General Chair for FSE 2026 , Guest Editor-in-Chief for TOSEM , and workshop co-chair for APR@ICSE series. Her teaching focuses on software engineering practices with real-world open-source projects. She also co-founded the ACM-W Montreal Professional Chapter in 2025.

• Automated Program Repair
• Open-source Software Development
• Software Testing
• +۹ مورد دیگر

Liqian Chen is a Professor of Computer Science at the National University of Defense Technology (NUDT), Changsha, China. His research focuses on program analysis, abstract interpretation, and automated program repair, with a strong emphasis on numerical stability and software verification. Recent publications address advanced topics in floating-point error detection, vulnerability analysis, and invariant generation for neural networks. Key contributions include tools like F-IKOS (static analyzer for Fortran programs), AutoRNP (floating-point error repair tool), and Software Apron (numerical abstract domain library). Scientific Awards: ACM SIGSOFT Distinguished Paper Award (ISSTA 2024) He serves on program committees for major conferences such as ASE 2025, SAS 2025, and SETTA 2025, and acts as Guest Editor for journals like Automated Software Engineering Journal and Journal of Systems Architecture .

• Program Analysis
• Abstract Interpretation
• Automated Program Repair
• +۶ مورد دیگر

Djordje Zikelic is an Assistant Professor of Computer Science at Singapore Management University's School of Computing and Information Systems. He holds a PhD from the Institute of Science and Technology Austria (ISTA), where he was advised by Krishnendu Chatterjee and Petr Novotný. His research focuses on formal methods for ensuring correctness, safety, and trustworthiness of software and AI systems, with an emphasis on probabilistic systems, program verification, and safe autonomy. He has received awards including the Outstanding PhD Thesis and Outstanding Scientific Achievement awards from ISTA. Education: PhD in Computer Science, ISTA (2023) Bachelor's and Master's in Mathematics, University of Cambridge Research Interests: Formal verification of probabilistic systems Trustworthy AI and neural network certification Runtime monitoring and control synthesis Blockchain protocol analysis Teaching: CS423: Heuristic Search and Optimization (Spring 2025/2024) His recent work includes advancements in supermartingale-based verification, neural controller certification, and automated analysis of blockchain systems. He serves on program committees for top conferences like AAAI, CAV, and IJCAI and actively mentors students in PhD, internship, and visiting roles.

• Formal Methods
• Trustworthy AI
• Program Analysis and Verification
• +۶ مورد دیگر

Prof. Liu Yang is a full Professor and University Leadership Forum Chair at the School of Computer Science and Engineering, Nanyang Technological University (NTU). He holds the President’s Chair in Computer Science and Engineering and serves as Executive Director of the Cyber Research Programme Office and Cyber Security Research Centre @ NTU. His research focuses on Cybersecurity, Software Engineering, and Artificial Intelligence, with contributions in formal verification, program analysis, and deep learning systems. He leads projects like the Securify initiative and develops tools such as the Process Analysis Toolkit (PAT) for system verification. Education: Ph.D. (2010) and Bachelor of Computing Science (2005) from National University of Singapore. Research Interests: Cybersecurity (malware analysis, vulnerability detection), Software Engineering (formal verification, program analysis), AI (security, robustness, explainability), and Automotive Security. His work bridges formal methods, program analysis, and machine learning to address challenges in secure systems and autonomous systems. Notable Achievements: Over 6000 citations (2020), H-index 38, awards include Nanyang Assistant Professor (2013), NRF Investigatorship (2020), and ACM Distinguished Speaker. His research spans journals like IEEE Transactions on Software Engineering and conferences such as NeurIPS, CVPR, and ICSE. Grants and Leadership: Principal Investigator of grants totaling over 5M SGD, including projects on vulnerability detection, formal verification, and cybersecurity. Organizes international conferences like ASE, ICSE, and FM, and serves on editorial boards such as IEEE Access. Labs/Teams: Leads the Cyber Security Research Centre @ NTU and collaborates on projects like the HP-NTU Digital Manufacturing Corp Lab and the National Satellite of Excellence in Singapore.

• Cybersecurity
• Software Engineering
• Artificial Intelligence
• +۳ مورد دیگر

Chris Poskitt is an Associate Professor of Computer Science (Education) at the School of Computing and Information Systems (SCIS) at Singapore Management University (SMU). He also serves as Director of the BSc (IS) Smart-City Management & Technology Major and Director of Undergraduate Administration at SCIS. Dr. Poskitt is an active member of the System Analysis and Verification (SAV) research group within SCIS. Dr. Poskitt completed his PhD in 2014 at the University of York (UK) under the supervision of Detlef Plump. Prior to joining SMU, he was a postdoctoral researcher for three years at ETH Zürich, where he worked with Bertrand Meyer. His academic journey reflects a strong foundation in formal methods and software engineering principles. Dr. Poskitt's research broadly addresses the problem of engineering correct and secure software and systems. His work spans several key areas including software engineering, formal methods, cybersecurity, and computer science education. He has developed innovative techniques for testing and defending cyber-physical systems using fuzzing and machine learning, tools for analyzing execution models of concurrency APIs, and logics for reasoning about the correctness of graph-rewriting programs. His research projects include AI agent safety, autonomous vehicle testing, critical infrastructure security, defending cyber-physical systems, analyzing actor-like concurrency models, verifying graph programs, and software engineering education. Dr. Poskitt's recent publications (2024-2026) demonstrate a strong focus on safety and security of autonomous systems, particularly autonomous vehicles and LLM agents. His work combines formal methods with practical applications, addressing challenges in runtime enforcement, causality analysis, and automatic repair of system behaviors. There's a clear progression from foundational work on graph transformation and formal verification toward applied research on cyber-physical systems and AI safety, with an increasing emphasis on real-world impact. Dr. Poskitt serves as research advisor to students including Huang Shaofei, WANG Haoyu, and ZHAO Lu. His research has been supported by various grants that have enabled publications across top software engineering and security venues including ICSE, FSE, ASE, and IEEE Transactions. He has served on numerous prestigious program committees including ICSE, FSE, ASE, and ICGT, indicating recognition by his peers in the software engineering community. Dr. Poskitt is part of the System Analysis and Verification (SAV) group at SMU's School of Computing and Information Systems. This research group focuses on formal methods and verification techniques for software systems, with particular emphasis on safety and security properties. His work often involves collaboration with researchers at institutions including ETH Zürich and other international partners.

• Software Engineering
• Formal Methods
• Cybersecurity
• +۵ مورد دیگر

Prateek SAXENA is an Associate Professor in the Computer Science Department at the School of Computing, National University of Singapore. He serves as Co-Director of the CRYSTAL Centre and teaches courses including CS3235 Computer Security and CS5562 Trustworthy Machine Learning. His research spans multiple domains within computer security and systems. Dr. SAXENA earned his Ph.D. in Computer Science from the University of California, Berkeley (2012), an M.S. in Computer Science from Stony Brook University (2007), and a B.E. in Computer Engineering from the University of Pune, India (2004). His research focuses on building better security and privacy in practical systems through principled approaches combining formal reasoning, tools and ideas from several computer science domains. Current research thrusts include machine learning security, decentralized systems security, security processors, and automatic program translation. His work has resulted in several practical artifacts powering real-world systems, including spinoffs like Zilliqa and Kyber Network. His publication record demonstrates consistent high-impact research across security domains including web security, blockchain, trusted execution environments, and machine learning security. His work shows a progression from foundational web security research to cutting-edge work on blockchain systems and machine learning security. MIT Technical Review, Top 10 Innovators under 35, Asia - 2017 Security and Privacy Research Award, 2018 Young Research Award, NUS, 2017 David J. Sakrison Memorial Prize for outstanding doctoral work, UC Berkeley, 2012 AT&T Best Applied Security Research Paper Award 2010 Dr. SAXENA has advised numerous successful PhD students who have gone on to prominent positions at Microsoft Research, Georgia Tech, ETH Zurich, and industry leaders like Zilliqa and Kyber. His research has been generously supported by CISCO Research, Google, Intel, Symantec, MoE-Singapore, DSO Labs, and NRF-Singapore. He leads the KISP Lab (Keep It Secure and Private), which has produced influential research in blockchain, trusted execution environments, and security tools.

• Computer Security
• Machine Learning Security
• Trustworthy AI
• +۴ مورد دیگر

David LO is the OUB Chair Professor of Computer Science at the Singapore Management University , leading the SOAR research group and directing the Information Systems & Technology Cluster. His research bridges software engineering , cybersecurity , and data science , focusing on socio-technical aspects and automated tools for bug/vulnerability detection.

• Software Engineering
• Cybersecurity
• Data Science
• +۵ مورد دیگر

Carlo A. Furia is an Associate Professor in the Software Institute at the Faculty of Informatics , Università della Svizzera italiana (USI) in Lugano, Switzerland. His research focuses on formal methods for software engineering , including automated verification, exception handling analysis, and empirical evaluation of software quality techniques. PhD in Computer Science from Politecnico di Milano Master of Science in Computer Science from University of Illinois at Chicago Laurea in Computer Science and Engineering from Politecnico di Milano Research interests span Java bytecode analysis , software reliability , and Bayesian data analysis for empirical studies. His recent work includes verification tools like AutoProof and empirical comparisons of programming languages. He actively contributes to conferences such as FM , ASE , and journals like Empirical Software Engineering (EMSE) . Teaching includes courses like Software Analysis and Software Design & Modeling . He leads the ATOM research group which develops open-source software analysis tools.

• Formal Methods for Software Engineering
• Java Bytecode Analysis
• Automated Program Verification
• +۳ مورد دیگر