Find Academic Supervisors

• Strategy and Organizational Behavior
• Applied Mathematics
• Transportation and Logistics
• +5 more

Assoc Prof Cheng-Feng Chou is an Associate Professor in the Analytics and Operations Department at the National University of Singapore (NUS Business School). His research spans strategy, applied mathematics, transportation logistics, control engineering, computational theory, and psychology. He holds an Orcid identifier (0000-0002-8044-8598) and is based at 15 Kent Ridge Drive, Singapore. Research Interests: Focus on interdisciplinary areas such as supply chain resilience, sustainability in innovation, healthcare operations, and maritime logistics. His work integrates data-driven methodologies with practical applications, addressing challenges like emission compliance, resource allocation, and process flexibility. Teaching Philosophy: Emphasizes critical thinking and lifelong learning, employing diverse teaching methods to accommodate varied student needs. Uses case studies, hands-on simulations, and collaborative learning to enhance understanding of complex concepts. Notable strategies include error-based learning and real-world application examples to foster analytical skills. His publications (over 50 articles/books) address topics ranging from stochastic optimization in supply chains to healthcare resource planning. He advises students who have received awards like the Presidents Graduate Fellowship and Best Paper Awards in international conferences. Collaborations include projects with semiconductor manufacturers, hospitals, and maritime carriers. Key contributions include frameworks for process monitoring in semiconductor manufacturing, resilient supply chain models post-COVID-19, and decision-support systems for emission compliance in shipping.

Andrew LimView profile

Professor

• Stochastic Control
• Operations Research
• Financial Engineering
• +3 more

Andrew Lim is a Professor in the Department of Analytics and Operations and the Department of Finance at the National University of Singapore (NUS). He serves as Deputy Director of the Institute for Operations Research and Analytics. Previously, he was on the faculty of the Department of Industrial Engineering and Operations Research at the University of California, Berkeley (2002–2014). His research focuses on stochastic control, robust decision-making, decentralized optimization, and applications in financial engineering and operations research. His work has been published in top journals like Operations Research , Management Science , and IEEE Transactions on Automatic Control . Lim has received the National Science Foundation CAREER Award and has held editorial roles at prominent journals. His research explores topics such as dynamic portfolio selection, robust empirical optimization, and stochastic systems analysis. He has contributed to advancing methodologies in risk-sensitive control, multi-agent systems, and machine learning applications in finance. His recent work emphasizes data-driven approaches and the integration of learning algorithms into decision-making frameworks. Lim’s academic career spans over two decades, with a strong focus on bridging theoretical advancements with practical applications in finance and operations. His interdisciplinary research addresses challenges in inventory management, demand forecasting, and optimal resource allocation. He collaborates with institutions globally to develop innovative solutions for complex stochastic systems.

• New Product Development
• Innovation Sourcing
• Economics of AI
• +3 more

Zhi Chen is an Assistant Professor in the Department of Analytics and Operations at the National University of Singapore (NUS) Business School. He holds a PhD in Decision Sciences from INSEAD and a B.Eng (First Class Honours) in Industrial and Systems Engineering from NUS. His research focuses on operational challenges in innovation-driven value chains, specifically addressing R&D procurement strategies and demand forecasting for new products. He currently serves as faculty in the Analytics & Operations division and has been affiliated with NUS since January 2022. Education: PhD in Decision Sciences, INSEAD B.Eng (First Class Honours), Industrial and Systems Engineering, National University of Singapore Research Interests: Zhi's work explores two core areas: (1) Optimizing supplier base designs and information policies for innovation procurement, particularly in AI-driven sectors like autonomous vehicles; and (2) Developing methodologies to aggregate expert forecasts ("Wisdom of Crowds") while quantifying uncertainty in new product demand. His models address challenges such as data-sharing dilemmas among firms and uncertainty quantification in high-stakes decisions. Grants & Funding: His research has been supported by the National University of Singapore Start-Up Grant (Grant A-0003854-00-00). Labs/Teams: No specific lab affiliations explicitly mentioned in the provided materials.

Marcelo H. Ang Jr.View profile

Professor

• Robotics
• Mobile Manipulation
• Compliant Control
• +6 more

Marcelo H. Ang Jr. is a Professor in the Department of Mechanical Engineering at the National University of Singapore (NUS), where he also serves as the Director of the Advanced Robotics Centre. With expertise spanning robotics, control systems, and intelligent automation, he has made significant contributions to mobile manipulation, compliant control, and multi-robot systems. His work bridges theoretical foundations with practical applications in manufacturing, surveillance, and human-robot interaction. Research Interests: Robust Mobile Manipulation in Unstructured Environments Distributed Mobile Robotic Systems Man-Machine User Interface Control of Dynamic Behavior of Robot Manipulators Passive Compliance and Flexible Robots Mobile Robotics Intelligent Control using Neural Networks and Fuzzy Reasoning His research spans fundamental robotics concepts like impedance control and compliant manipulation to cutting-edge applications in multi-robot systems, autonomous navigation, and soft robotics. Recent work focuses on mobility-enhanced sensor networks, deep learning for perception, and autonomous vehicles. Scientific Awards: Awards for Excellence 2000, for Most Outstanding Paper in 1999 Volume for "A Walk-Through Programmed Robot for Welding in Shipyards" Research Activities: Professor Ang has led multiple funded projects including "Integration of Solid Modeling Systems and Robot Controller Architectures" (1990-1995), "Management of Manufacturing Technologies" (1993-1995), and "Research and Development of a Ship-Welding Robot" (1994-1997). He has supervised numerous students, including Ph.D. candidate Zheng Liu who worked on multi-robot surveillance systems. His laboratory at NUS develops advanced robotic systems for applications ranging from ship welding to autonomous vehicles.

• Optimisation Under Uncertainty
• Discrete Choice
• Social Choice
• +4 more

Chung Piaw Teo is the Stephen Riady Professor and Executive Director of the Institute of Operations Research and Analytics (IORA) at the National University of Singapore (NUS) Business School. He has held significant academic roles including Head of Department, Acting Deputy Dean, Vice-Dean of Research and Ph.D. Programs, and Chair of the Ph.D. Committee at NUS. PhD in Operations Research from MIT (1996) Bachelor of Science (Honors) in Mathematics from NUS (1990) Research Interests: Optimisation Under Uncertainty Discrete Choice Modeling Social Choice Theory Inventory Theory Supply Chain Management Combinatorial Optimisation Operations Research Publications focus on stochastic optimization, supply chain resilience, and network design, with recent works spanning 2020–2015 in journals like Management Science , Operations Research , and Mathematical Programming . Key themes include urban logistics, risk mitigation, and decision analytics. Scientific Awards: Stephen Riady Professor (2024) Provost’s Chair (2014) Faculty Outstanding Researcher Awards (2014, 2006, 2003) Nominee for University Outstanding Researcher Award (2006) Grants & Leadership: Served on international committees (INFORMS, LANCHESTER Prize, Fudan Prize) and held visiting/fellow positions at MIT, Northwestern, and Sungkyunkwan University. Currently a department editor for Management Science and associate editor for multiple journals.

• Reinforcement Learning
• Multi-Agent Systems
• Foundation Models
• +7 more

WANG Xinrun is an Assistant Professor and Lee Kong Chian Fellow at the School of Computing and Information Systems, Singapore Management University, where he joined in July 2024. He holds a PhD from Nanyang Technological University (2020). His research spans: Fundamental decision making (single/multi-agent reinforcement learning) Applied decision systems (FinTech, urban security, scientific AI) Foundation agents (computer control, automated research) with emphasis on unified frameworks for complex problem-solving. His publication portfolio (15 most recent shown) demonstrates consistent focus on reinforcement learning innovations, multi-agent game theory, and financial AI applications, with papers in ICLR, NeurIPS, AAAI, and KDD. Key trends include foundation model integration, decision-making unification, and real-world deployment. Awards include the Lee Kong Chian Fellowship. He advises PhD student ZHOU Shunchao and leads a research group developing: Reinforcement learning for FinTech Multi-agent systems for urban security Foundation agents for scientific discovery while actively recruiting students and collaborators for these initiatives.

Cheung Wang ChiView profile

Assistant Professor

• Online and data-driven optimization
• Revenue management
• Resource allocations in supply chains

Cheung Wang Chi serves as an Assistant Professor specializing in Industrial Systems Engineering and Management. His academic appointment focuses on operational research and systems optimization within supply chain contexts. Research interests emphasize: Algorithmic development for dynamic resource allocation Revenue optimization in stochastic environments Data-driven decision frameworks for logistics networks His work bridges theoretical optimization methods with practical supply chain applications, particularly in e-commerce and transportation sectors where real-time data informs resource distribution strategies.

Yuhao BaView profile

Assistant Professor

• Environmental Governance
• Public Policy Process
• Non-state Governance
• +3 more

Yuhao Ba is an Assistant Professor at the Lee Kuan Yew School of Public Policy, National University of Singapore. His research focuses on non-state governance, environmental policy, and public policy processes. He holds a PhD in Public Administration from North Carolina State University. Research interests include corporate-led environmental governance, interactions between governance systems and policy processes, and sustainability outcomes. He is also committed to promoting equity and inclusion in public policy through his work with APPAM’s Equity & Inclusion fellowship. Education: PhD (Public Administration), North Carolina State University Office: 469C Bukit Timah Road, Singapore 259772 Email: yba@nus.edu.sg His recent work explores themes like policy innovation diffusion, climate change mitigation, and organizational performance evaluation. Publications span journals in public policy, environmental governance, and statistical methodologies. No grants or student advisement information is listed in the provided materials.

Ilya SergeyView profile

Associate Professor

• Programming Languages
• Software Verification
• Distributed Systems
• +5 more

Associate Professor Ilya Sergey leads the Verified Systems Engineering (VERSE) lab at the School of Computing, National University of Singapore (NUS). He holds a PhD in Computer Science from KU Leuven and an MSc in Mathematics from Saint Petersburg State University. His research focuses on programming languages, software verification, distributed systems, and program synthesis. He is a recipient of the AITO Dahl-Nygaard Junior Prize (2019) and multiple ACM SIGPLAN Distinguished Paper Awards. His work includes developing the Scilla smart contract language and the Veil verification framework, emphasizing formal methods for ensuring software correctness. **Education**: PhD in Computer Science, KU Leuven, Belgium (2012) MSc in Mathematics and Computer Science, Saint Petersburg State University, Russia (2008) **Research Interests**: Design and Implementation of Programming Languages Formal Verification using Separation Logic Distributed Systems and Concurrency Program Synthesis and Automated Proof Repair **Recent Articles Trends**: His recent work emphasizes automated verification tools (e.g., Veil), exploit generation via synthesis, and compositional verification of Byzantine protocols. These contributions bridge foundational theory with practical applications in distributed systems and smart contracts. **Awards**: AITO Dahl-Nygaard Junior Prize (2019) ACM SIGPLAN Distinguished Paper Awards (PLDI'23, PLDI'21, POPL'19) Google, Facebook, and Amazon Research Awards **Advising & Grants**: He actively mentors PhD students in formal methods and verification. His grants include support from Google and industry partnerships. He organizes the ICFP Programming Contest and co-chairs ICFP'25. **Labs & Teams**: Leads the VERSE lab, part of the PLSE@NUS group, focusing on verified software systems and program synthesis.

Dagomir KaszlikowskiView profile

Associate Professor

• Quantum Entanglement
• Quantum Correlations
• Nonlocality
• +6 more

Dagomir Kaszlikowski is an Associate Professor at the Department of Physics, Faculty of Science, National University of Singapore (NUS), and a Principal Investigator at the Centre for Quantum Technologies (CQT). His research focuses on foundational aspects of quantum theory, particularly correlations in quantum systems, which underpin quantum nonlocality, contextuality, and quantum information processing. He leads the Dagomir Kaszlikowski Group, exploring topics like quantum supremacy through alternative formulations of quantum mechanics and the social/economic impacts of quantum technologies. His recent work includes studies on electric-magnetic duality in lattice gauge theory, quantum geometric invariance, and spatiotemporal frameworks for quantum processes. He collaborates extensively with researchers such as Jia Zhian, Sheng Tan, and Pawel Kurzynski. His group investigates quantum correlations, quantum computing, and the intersection of quantum mechanics with thermodynamic properties. His research group's publications demonstrate a consistent focus on quantum information theory, nonlocality, and contextuality across multiple platforms including optical systems and lattice models. Key themes include entanglement, quantum algorithms, and fundamental tests of quantum theory. Contact: phykd@nus.edu.sg | Office: S15-06-09, NUS

• Entrepreneurship and Innovation
• Library and Information Management
• Artificial and Augmented Intelligence
• +3 more

Assoc Prof Wang Jue is an Associate Professor at the School of Social Sciences and Director of the Nanyang Centre for Public Administration (NCPA) at Nanyang Technological University (NTU). She holds a PhD in Public Policy from Georgia Tech. Her work focuses on innovation management, science policy analysis, and AI applications in governance. Current projects explore AI implications for policy research and cross-border innovation systems. Education: PhD in Public Policy (Georgia Tech) Prof Wang’s research interests span Entrepreneurship and Innovation , Artificial Intelligence Governance , Regional Innovation Systems , and Public Policy Evaluation . She examines how technological advancements reshape policy frameworks and global talent dynamics, with notable studies on Hong Kong-Shenzhen innovation collaboration and global academic labor markets. Her recent articles analyze disciplinary AI adoption patterns in education, policy diffusion mechanisms in China, and LLM biases in public opinion modeling. These studies highlight emerging trends in computational policy analysis and cross-border knowledge ecosystems. Labs/Teams: Leads the Nanyang Centre for Public Administration, focusing on public sector innovation and governance research. Grants/Advising: Active in securing research funding on science policy and innovation metrics, though specific grants are not detailed here.

• Formal Verification
• Model Checking
• Automated Reasoning
• +9 more

Georg Weissenbacher is a Full Professor of Computer Science at Vienna University of Technology (TU Wien), working in the Institute of Logic and Computation within the Faculty of Informatics. He leads the Formal Methods in Systems Engineering research group and has established himself as a leading researcher in formal verification and automated reasoning. His educational background includes a DPhil from Oxford University (2008-2010), research at ETH Zürich (2005-2010), and a Master's degree from TU Graz (completed by 2003). He completed his Habilitation at TU Wien in 2016 with a thesis on Logical Methods in Automated Hardware and Software Verification. Weissenbacher's research focuses on developing automated tools for software and hardware verification, with particular emphasis on detecting and explaining bugs in complex systems. He is renowned for his work on heisenbugs - bugs that disappear when analyzed, which are particularly challenging in concurrent and multi-core systems. His research bridges theoretical foundations in logic with practical applications in software engineering, with significant contributions to interpolation-based verification techniques and SAT/SMT solving applications. His recent publications show a clear progression from traditional software verification toward emerging challenges in AI security, neural network verification, and sophisticated concurrency models. The research trajectory demonstrates increasing sophistication in handling complex systems properties, with a growing emphasis on probabilistic guarantees and formal methods applied to modern computing challenges. OOPSLA'18 Distinguished Paper Award for 'Randomized Testing of Distributed Systems with Probabilistic Guarantees' Weissenbacher has advised numerous PhD students and postdocs, including current researchers Mai AL-Zu'bi, Katalin Fazekas, and Sarah Sallinger. His research has been supported by significant grants including the Vienna Research Groups for Young Investigators (2011), the National Research Network 'Rigorous Systems Engineering' funded by FWF, and a Microsoft Research PhD Scholarship (2016). He actively contributes to the academic community through his service as co-chair for major conferences including CAV 2018 and FMCAD 2017. As leader of the FORSYTE research group at TU Wien, Weissenbacher oversees a vibrant research team working at the intersection of logic, verification, and practical software engineering challenges. The group is currently involved in the Doctoral College on Automated Reasoning, funded by FWF, which aims to train the next generation of researchers in this critical field.

ZHOU PanView profile

Assistant Professor

• Computer Vision
• Deep Learning
• Optimization Algorithms
• +2 more

Zhou Pan is a tenure-track Assistant Professor and Lee Kong Chian Fellow at Singapore Management University, where he directs the Language & Vision Lab. His research develops efficient AI systems for visual cognition and interaction, focusing on self-supervised learning, network architecture design, and optimization algorithms. He teaches Computer Vision and AI courses. Current research includes 3D generation models, vision-language alignment, and accelerated optimization methods. As research advisor to ZOU Xiandong, he mentors graduate research in computer vision and deep learning.

LING SanView profile

Professor

• Number Theory
• Algebraic Geometry
• Coding Theory
• +5 more

Roles and Affiliations: LING San is the Deputy President and Provost at Nanyang Technological University (NTU), Singapore, and holds the President’s Chair in Mathematical Sciences within the School of Physical and Mathematical Sciences (SPMS). He is associated with the College of Science (CoS) and has been a prominent academic leader in mathematical sciences. Education: PhD in Mathematics from University of California, Berkeley (USA, 1990) MA in Mathematics from University of Cambridge (UK, 1989) BA (First Class Honours) in Mathematics from University of Cambridge (UK, 1985) Research Interests: Focuses on algebraic number theory, coding theory, cryptography, combinatorial designs, and the arithmetic of modular curves. His work bridges pure mathematics (e.g., Galois representations) with applied domains like error-correcting codes and cryptographic protocols. Professional Service: Serves on multiple international advisory boards and committees, including the International Advisory Council of Universiti Tunku Abdul Rahman (Malaysia), VinUniversity Institutional Advisory Board (Vietnam), and ACME’s Advisory Council on Community Relations (Singapore). Active in academic governance, research policy, and interdisciplinary initiatives. Key Contributions: Pioneered advancements in quasi-cyclic codes, quantum error-correcting codes, and cryptographic schemes. His research often intersects algebraic geometry and combinatorics, yielding impactful results in information theory and secure communication. Grants and Awards: While no personal awards are explicitly stated, he has contributed to major projects and chairs committees for scientific awards (e.g., President’s Science and Technology Awards).

• Stochastic Models
• Applied Probability
• Algorithms in Stochastic Models
• +3 more

Professor Zhang Hanqin is a faculty member at the Department of Analytics & Operations, National University of Singapore (NUS), affiliated with the Institute of Operations Research and Analytics (IORA), part of NUS’s Smart Nation Research Cluster. His research focuses on stochastic models, applied probability, algorithms in stochastic systems, supply chain management, and queueing theory. He has contributed extensively to optimization in inventory systems, manufacturing systems, and service operations. His work spans theoretical advancements and practical applications, including optimal staffing for queues, assemble-to-order systems, and quantity flexible contracts. Recent studies address time-varying queues, minimal phase-type distributions, and impulse control strategies. His research bridges stochastic processes, operations research, and applied mathematics with real-world systems. Key achievements include foundational contributions to diffusion approximations, Coxian representations, and policy design for complex systems. His articles often explore multi-source inventory systems, tandem queues, and expediting strategies, reflecting a deep engagement with both theoretical rigor and industrial relevance.