Dr. Mei Qi is a Senior Lecturer in the Department of Analytics and Operations at the NUS Business School, National University of Singapore. Her research focuses on transportation logistics, supply chain optimization, and applied mathematics. She has contributed to advancements in metamaterials and antenna technology, with notable work published in journals like International Journal of Production Economics and Advanced Optical Materials . Dr. Qi emphasizes innovative teaching methodologies, advocating for interactive and relevant learning experiences. Her strategies include staying current in her discipline, integrating real-world business projects, and adopting case-based teaching to enhance student engagement and retention. She aims to tailor educational processes to optimize learning outcomes through adaptive designs. Her research interests span metamaterial applications in antenna design, terahertz technology, and electromagnetic scattering control. Recent projects involve metasurface-based solutions for communication devices and broadband radiation pattern optimization. Dr. Qi actively collaborates with industry partners to translate theoretical insights into practical systems. Teaching philosophy: 'Teaching is a process designed for efficiency, engagement, and continuous improvement. I push relevant content at students' 'pulling' pace while stimulating holistic discipline understanding.'
Dong Jin Song is a full Professor at the National University of Singapore's School of Computing, Department of Computer Science. He joined NUS in 1998 and was promoted to Professor in 2016 after serving as Associate Professor (2005) and Assistant Professor. He has held various leadership roles including Deputy Head of CS Department (2023-2024), NUS Senate Member (2020-current), and Assistant Dean (Graduate Office, SoC). PhD, University of Queensland, Australia (1993-1995) BInfTech with First Class Honours, University of Queensland, Australia (1989-1992) - Major in Software Engineering Professor Dong's research spans formal methods, safety and security systems, probabilistic reasoning, sports analytics, and trusted machine learning. He is best known for co-founding the PAT verification system which has attracted thousands of registered users from over 150 countries and won the 20-year ICFEM Most Influential System Award in 2018. He also co-founded 'Silas: Trusted Machine Learning' and the Dependable Intelligence company. His work bridges formal verification with practical applications in security, AI, and even sports analytics where he developed Markov Decision Process models for tennis strategy analysis. His recent publications show a strong trend toward integrating formal methods with modern AI systems, particularly focusing on trustworthy AI, LLM verification, and security applications. The research spans multiple high-impact venues including ICML, NeurIPS, IEEE Transactions, and top security conferences like USENIX Security, reflecting his interdisciplinary approach that combines formal verification with machine learning, security, and practical applications. Professor Dong has received numerous honors including the ACM SIGSOFT Distinguished Paper Award for ICSE 2020, the 20-Year ICFEM Most Influential System Award (2018), and being named a Fellow of the Institute of Engineers Australia (2018). His awards reflect both theoretical contributions to formal methods and practical impact on software engineering. ACM SIGSOFT Distinguished Paper Award for ICSE 2020 NUS Research Recognition Award (2020) Fellow of Institute of Engineers Australia (2018) 20-Year ICFEM Most Influential System Award (2018) Best Paper Award at ICECCS (2015 and 2012) Professor Dong has successfully supervised 33 PhD students, many of whom have become tenured faculty members at leading universities worldwide including The University of Auckland, Aston University, Singapore Management University, and Monash University. His students have gone on to successful careers in both academia and industry at organizations like Google, Apple, HP Research Lab, and IBM. He has served on the editorial boards of prestigious journals including ACM Transactions on Software Engineering and Methodology and has been active in numerous conference organizing committees. Through his research group and commercial ventures (Dependable Intelligence), Professor Dong has built a strong team focused on formal verification, trusted AI systems, and practical applications of model checking. His work has evolved from foundational formal methods research to cutting-edge applications in AI safety and security, maintaining a consistent thread of rigorous verification throughout his career.
Leong Hon Wai is an Associate Professor at the National University of Singapore (NUS) in the Department of Computer Science under the School of Computing . He also participates in the University Scholars Programme (USP). With a Ph.D. in Computer Science from the University of Illinois at Urbana-Champaign and a B.Sc. in Mathematics (1st Class Honours) from the University of Malaya , Prof. Leong has been a cornerstone of NUS since 1987, previously serving as Division Head for Computer Science and Assistant Dean for Special Programmes . His work bridges computational theory with practical applications in bioinformatics , transportation logistics , and VLSI CAD . Education: B.Sc. in Mathematics, University of Malaya (1st Class Honours) Ph.D. in Computer Science, University of Illinois at Urbana-Champaign Research Interests span the design of efficient algorithms across diverse domains. Key areas include: Bioinformatics : Algorithmic solutions for genomic island detection, protein function prediction, and genome sorting. VLSI CAD : Applied research in computer-aided design for integrated circuits. Logistics : Algorithms for resource allocation, scheduling, and dynamic route planning. Computational Thinking : Pedagogical approaches to simplify complex concepts for non-computer science audiences. His publications reflect interdisciplinary collaboration, particularly at the intersection of algorithm design and biological systems , with a focus on problems like protein function prediction and genome rearrangement . The scientific community has recognized his contributions through fellowships and teaching awards , including the Annual Teaching Excellence Award and Inspiring Mentor Award from NUS. Awards & Honors : Fellow, Singapore Computer Society (2009) NUS Annual Teaching Excellence Award (2009) Inspiring Mentor Award (NUS, 2009) USP Teaching Award (2008) Best Paper Award (APCCAS-1992) Best Presentation Award (ICCD-1985) Excellent Instructor (UIUC, Spring 1985) Teaching & Outreach initiatives include founding Singapore’s Special Programme in DISCS , pioneering NUS’s modular curriculum aligned with ACM standards, and leading the National Olympiad in Informatics (NOI) since 1998. He also co-organizes the annual 24-hour Code::XtremeApps (CXA) competition, engaging primary school students through platforms like Scratch and micro-bit . His passion for computational thinking extends to the course GET1031 for non-majors and outreach programs in K-12 education. Professional Service includes leadership roles in the Singapore Computer Society (SCS), organizing conferences like SEARCC'99 , and serving on the SCS Executive Committee (1994–2007). He is a member of prestigious societies: ACM , IEEE , and ISCB .
Yap Roland is an Associate Professor at the School of Computing, National University of Singapore (NUS), and a member of the Institute of Operations Research and Analytics (IORA). His research focuses on constraint programming and solving, optimization, combinatorial problems, vehicle routing, and big data applications. He actively contributes to advancing methodologies in computational logic, software security, and algorithm design. His work spans theoretical foundations of constraint satisfaction (CSP/SAT) and practical applications in database systems, graph neural networks, and transportation logistics. Notable contributions include benchmarking tools like OSS-Bench for coding LLMs, novel approaches to detecting logic bugs in graph databases, and enhancing security through randomized pointer techniques. His research bridges algorithmic theory and real-world challenges in AI, cybersecurity, and efficient resource allocation. Yap Roland has published extensively in top-tier venues such as the International Conference on Principles and Practice of Constraint Programming (CP) and the International Conference on Theory and Applications of Satisfiability Testing (SAT). His recent work emphasizes scalability, fairness in machine learning, and robustness against memory errors in software systems.
