جست‌وجوی استاد و پژوهشگر

• Environmental Sociology
• Political Economy
• Quantitative Methods
• +۱ مورد دیگر

Dr. Annika RIEGER is an Assistant Professor of Sociology at the Singapore Management University's School of Social Sciences. She holds a Ph.D. in Sociology from Boston College (2023), an M.A. in Sociology from Boston College (2018), and a B.S. in Sociology from Southern Methodist University (2016). Her research examines the intersection of corporations, civil society, and environmental policy through quantitative and computational methods. Her work focuses on three primary areas: environmental sociology (studying anthropogenic drivers of climate change), political economy (analyzing corporate responses to societal pressure), and organizational behavior (investigating barriers to institutional reform in energy sectors). Recent publications demonstrate a consistent focus on corporate environmental accountability, with methodological strengths in multilevel analysis of longitudinal datasets. Her work employs innovative approaches to studying earnings calls, investment patterns, and regulatory impacts across multiple countries.

OH Lih Binمشاهده پروفایل

دانشیار

• Digital Transformation
• Information Systems Leadership
• Platforms & Innovation
• +۵ مورد دیگر

Dr. OH Lih Bin is an Associate Professor (Educator Track) and Deputy Head (Teaching and Degree Programmes) in the Department of Information Systems and Analytics at the National University of Singapore (NUS) School of Computing. He holds a Ph.D., M.Sc., and B.Sc. in Information Systems and Computer Science from NUS. Prior to his academic career, he worked at A*STAR and held roles at Xi'an Jiaotong University and Monash University. His research focuses on digital transformation, platforms & innovation, experiential learning in computing education, and information ethics. Education: Ph.D. in Information Systems, National University of Singapore M.Sc. in Information Systems, National University of Singapore B.Sc. (Honours I) in Computer & Information Sciences, National University of Singapore Research Interests: Dr. Oh explores adult learning through mobile micro-learning platforms, innovation capability development, and service system innovation. He investigates ethical issues in IT, including whistleblowing and web accessibility advocacy. His work bridges theory and practice in experiential learning and digital transformation. Publications Trends: His articles span ethical IT practices, social media user behavior, and retail channel integration. Key themes include consumer value co-creation, the impact of interactivity on e-retail performance, and the role of Confucian ethics in organizational reporting behaviors. Awards: Halbrecht Associates Book Prize (1998) Best Paper Award, Conf-IRM (2009) Multiple nominations at ECIS, ICIS, and WHICEB Teaching & Leadership: Serves as Deputy Head overseeing teaching and programs. Teaches courses like IS3103 (Information Systems Leadership) and IS5128 (Digital Innovation). Previously held roles as Academic Director of International Affairs at XJTU. Labs/Teams: Engaged in research projects such as enhancing adult learning via mobile platforms and investigating differential impacts of web/mobile interactivity.

QIAO Dandanمشاهده پروفایل

دانشیار

• Digital Transformation
• Platforms & Innovation
• Data Science & Business Analytics
• +۵ مورد دیگر

QIAO Dandan is an Associate Professor in the Department of Information Systems and Analytics at the National University of Singapore (NUS), School of Computing. She holds a PhD from Tsinghua University and a visiting scholar appointment at the University of Texas at Austin. Her research focuses on digital platforms, computational social science, and the economics of dark web transactions. Notable contributions include analyzing darknet market dynamics, the impact of financial incentives on online reviews, and ride-hailing services' societal effects. Education: Ph.D., Information Systems, Tsinghua University, 2018 Visiting Scholar, University of Texas at Austin, 2015–2017 B.S., Information Systems, Beijing University of Posts and Telecommunications, 2012 Research Interests: Darknet market enforcement and crime suppression Incentive mechanisms in online prosocial behavior Predictive analytics for crowdfunding and e-commerce Platform design and digital transformation strategies Awards: 2024 AIS Early Career Award 2023 ISS Gordon B. Davis Young Scholar Award Multiple grants from Singapore's Ministry of Education and the NET Institute Advising & Grants: Ph.D. coordinator for NUS Department of Information Systems and Analytics Secured MOE Tier-1 and Tier-2 grants Editorial roles at Information Systems Research and MIS Quarterly Labs & Teams: Deputy Director of the Centre for Computational Social Science and Humanities (CSSH) at NUS.

Yingda Zhaiمشاهده پروفایل

استادیار

• Economics of Information Systems
• Digital Transformation
• Platforms & Innovation
• +۳ مورد دیگر

Yingda Zhai serves as an Assistant Professor in the Department of Information Systems and Analytics at the National University of Singapore's School of Computing. His academic foundation includes a Ph.D. in Economics from the University of Texas at Austin, an M.Sc. in Economics from Baylor University, and a B.A. in Finance from Shandong University. His research spans Economics of Information Systems , focusing on digital transformation, platform innovation, and computational social science. Key interests include dynamic pricing mechanisms, queueing theory applications in cloud computing, information design in digital economies, and social media's impact on societal trust structures. His work bridges theoretical economics with practical IT industry challenges. Analysis of his publications reveals a strong emphasis on resource allocation efficiency in cloud environments, with pioneering work on how large-scale providers mitigate demand uncertainty through market segmentation and strategic throttling. His research directly addresses real-world problems in cloud computing economics, particularly how providers optimize profits while managing unpredictable user demands. Faculty Teaching Excellence Award 2021 Faculty Teaching Excellence Award 2022 Dr. Zhai teaches advanced courses including BT4212 Search Engine Optimization and Analytics and BT5126 Hands-on with Business Analytics. His research projects investigate critical digital economy challenges such as trust dynamics in online societies and optimal pricing strategies for resource-constrained digital platforms. Current work examines correlated internet traffic effects on cloud pricing during demand surges like those experienced during the pandemic.

Poh Leong Hienمشاهده پروفایل

دانشیار

• Mechanics of Materials
• Damage Mechanics
• Multi-scale Methods
• +۴ مورد دیگر

Dr. Poh Leong Hien is an Associate Professor in the Department of Civil and Environmental Engineering at the National University of Singapore (NUS). He holds a Ph.D. from NUS and Eindhoven University of Technology (2011), following B.Eng. (2003) and M.Eng. (2005) degrees from NUS. His research focuses on multi-scale material modeling, damage mechanics, and higher-order continua, with applications in engineering materials and structures. Education: Ph.D., National University of Singapore & Eindhoven University of Technology, 2011 M.Eng. (Accelerated Master’s Programme), NUS, 2005 B.Eng. (First Class Honours), NUS, 2003 Research Interests: Mechanics of materials and damage mechanics Multi-scale methods and homogenization Higher-order continuum theories Computational material modeling His recent publications emphasize advanced materials under extreme conditions, such as metallic glasses and ultra-high-performance composites, alongside computational methods like isogeometric analysis and machine learning-driven homogenization. Key contributions include optimizing auxetic structures and improving failure prediction in heterogeneous materials. Awards include the Lee Kong Chian Graduate Scholarship (2006–2010) and the Institution of Engineers Singapore Gold Medal (2004). Advising and grants: While specific student/advisor details are not listed, his research group likely focuses on computational mechanics and material science. No grants are explicitly mentioned. Labs/Teams: No specific lab affiliations are noted in the provided text.

Low Ying Minمشاهده پروفایل

دانشیار

• Offshore Engineering
• Stochastic Dynamic Analysis
• Moorings and Risers
• +۶ مورد دیگر

Dr. Low Ying Min is an Associate Professor in the Department of Civil and Environmental Engineering at the National University of Singapore. He holds leadership roles including Director of the Ocean Infrastructures and Renewables Cluster and Programme Manager for the MSc Offshore Technology. His research focuses on stochastic dynamic analysis of moorings and risers, with contributions to offshore engineering reliability and fatigue analysis. He serves as Associate Editor for the ASME Journal of Offshore Mechanics and Arctic Engineering and editorial board member for Marine Structures and Ocean Engineering. Dr. Low earned a PhD from the University of Cambridge (2007) and MEng from Imperial College London (2000). His professional activities include organizing technical committees for the OMAE conference and ISSC Congress. Notable awards include the OMAE Appreciation Award (2019) and the Montrose Prize (2000). His research interests span floating structures, random vibration, and reliability analysis. Recent work emphasizes long-term fatigue analysis and extreme response prediction under stochastic loads. He has pioneered variance reduction techniques and surrogate modeling approaches to enhance computational efficiency in offshore structural analysis. Teaching areas include design of floating structures, moorings/risers, and wave hydrodynamics. Over 60 publications reflect his expertise in riser fatigue, seabed scour, and probabilistic modeling. Current projects focus on AI-driven reliability assessment and data-driven analysis of offshore systems.

Guo Yangمشاهده پروفایل

استادیار

• Eco-industrial Development
• Sustainable Infrastructure Systems
• Industrial Sector Decarbonization
• +۳ مورد دیگر

Guo Yang is a Presidential Young Professor/Assistant Professor in the Department of Civil and Environmental Engineering at National University of Singapore (NUS). His research focuses on eco-industrial development, sustainable infrastructure systems, and industrial decarbonization. Before joining NUS in 2023, he held roles as an Associate Research Scholar at Princeton University (2022–2023), Schmidt Science Fellow (2020–2022), and postdoctoral researcher at Tsinghua University (2019–2020). Education: PhD in Environmental Science and Engineering from Tsinghua University (2019), dual B.S. in Environmental Science and Computer Science (2014). Notable awards include the Early Career Award from the Chinese Society for Industrial Ecology (2022), Schmidt Science Fellowship (2020), and multiple doctoral dissertation recognitions. Research emphasizes synergistic approaches to industrial decarbonization, including green hydrogen deployment, infrastructure symbiosis, and policy implications for eco-industrial parks. His publications span Nature Chemical Engineering, Nature Communications, and Environmental Science & Technology, addressing carbon mitigation strategies and sustainable infrastructure design. Key contributions include modeling energy infrastructure transitions, analyzing industrial park emissions reduction, and exploring material science applications in additive manufacturing and nanocomposites.

Meng Qiangمشاهده پروفایل

استاد

• Transportation Network Modeling and Optimization
• Urban Mobility Systems
• Shipping and Intermodal Freight Transportation
• +۵ مورد دیگر

Professor Meng Qiang serves as Professor in the Department of Civil and Environmental Engineering (CEE) at the National University of Singapore (NUS), where he directs both the Centre for Transport Research (CTR) and the NUS Guangzhou Research Translation and Innovation Institute (NUS-GRTII). His academic leadership extends to editorial roles including Co-Editor-in-Chief of Multimodal Transportation and Advisory Editor for Transportation Research Part E . His educational background spans Bachelor of Science from East China Normal University (1984), Master of Science from Chinese Academy of Sciences (1989), and PhD in Civil Engineering from Hong Kong University of Science and Technology (2000). Prior to joining NUS, he held academic positions at Shandong Normal University where he became Professor in the Information and Management School after completing his PhD. Professor Meng's research expertise focuses on three interconnected domains: urban mobility modelling and optimization (including AI-based traffic prediction, autonomous vehicle operations, and EV infrastructure planning); shipping and intermodal freight transportation (covering liner network optimization, container logistics, and maritime cybersecurity); and quantitative risk assessment of transport operations (particularly for urban tunnels and maritime safety). His work integrates advanced computational methods with real-world transportation challenges, as evidenced by over 260 high-impact publications. His scholarly impact is demonstrated through consistent recognition as a Top 2% Scientist in logistics and transportation (Stanford University, 2019-2022) and numerous prestigious awards including the Omega Best Paper Award (2023), TSL Freight Transportation Award (2020), and Singapore MOT Minister's Innovation Award (2009). His publications reveal evolving research trajectories toward autonomous vehicle integration, maritime decarbonization, and AI-driven transportation solutions. Best Paper Award of Omega 2023 Member, Academy of Engineering Singapore (2022) TSL Best Paper Award in Freight Transportation and Logistics (2020) OCDI Takeuchi Yoshio Logistics Award (2019) Chang Jiang Scholar Chair Professor (2017) WCTR Society Prize for Best Paper (2013) Singapore MOT Minister's Innovation Award (2009) Professor Meng has supervised 17 PhD students and mentored 20 postdoctoral fellows, with many graduates achieving prominent academic positions internationally including Distinguished Young Scholars in China. His industry contributions include the QRAFT risk assessment software for road tunnels and an AI-based traffic prediction model developed with ST Engineering. He leads the Centre for Transport Research which conducts government and industry-funded projects addressing Singapore's transportation challenges through advanced modeling and optimization techniques.

Shaoning Hanمشاهده پروفایل

استادیار

• Mathematical Optimization
• Mixed-Integer Nonlinear Programming
• Nonsmooth Optimization
• +۳ مورد دیگر

Shaoning Han is a Presidential Young Professor (Assistant Professor) in the Department of Mathematics and the Institute of Operations Research and Analytics (IORA) at the National University of Singapore (NUS). He previously held a postdoctoral position at the University of Southern California (USC), working under Prof. Jong-Shi Pang. His research focuses on mathematical optimization, including mixed-integer nonlinear programming, nonsmooth optimization, and their applications in operations research and data science. Han earned his Ph.D. in Industrial Engineering from USC under Prof. Andrés Gómez and a B.S. in Mathematics from the University of Science and Technology of China (USTC). His work emphasizes advancing optimization methodologies, particularly for problems involving complementarity constraints, indicator variables, and sparsity. Recent contributions include progressive MIP methods for indefinite QPs, real-time solutions for banded matrix problems, and convexification techniques for nonconvex optimization. Han is actively recruiting PhD students interested in mathematical optimization. Research Highlights: His articles span theoretical advances (e.g., epi-stationarity analysis, parametric variational inequalities) and applied frameworks (e.g., robust SVMs, binarized neural networks). Key themes include polynomial-time solvability of MRFs, convex relaxations for low-rank functions, and sparse signal estimation. Awards: Third Place, INFORMS JFIG Paper Competition (2023) Journal of Global Optimization Best Paper Honorable Mention (2023) Teaching: Courses include MA5243 (Advanced Mathematical Programming) and MA3252 (Linear and Network Optimization). Labs/Teams: Active member of IORA, NUS’s Smart Nation Research Cluster.

• Stochastic Models
• Applied Probability
• Algorithms in Stochastic Models
• +۳ مورد دیگر

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.

Yap Rolandمشاهده پروفایل

دانشیار

• Constraint Programming
• Optimization
• Combinatorial Problems Modelling
• +۵ مورد دیگر

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.

Gianmarco Mengaldoمشاهده پروفایل

استادیار

• Computational Science and Engineering
• Data Science
• Machine Learning
• +۷ مورد دیگر

Dr. Gianmarco Mengaldo is an Assistant Professor in the Department of Mechanical Engineering at the National University of Singapore (NUS), affiliated with the College of Design and Engineering. He holds an Honorary Research Fellowship at Imperial College London (UK). His academic journey includes a PhD in Aeronautical Engineering from Imperial College London and degrees from Politecnico di Milano (BSc, MSc in Aerospace Engineering). His research integrates computational science, applied mathematics, and machine learning to address complex systems in engineering, climate science, healthcare, finance, and solid earth physics. Key focuses include data-driven pattern identification, high-fidelity multi-physics simulations, and AI-driven predictive modeling. Recent work explores financial explainable AI, climate impact modeling with small language models, and robust ESG analysis. His methodologies span neurosymbolic AI, hybrid deep learning systems, and stochastic-chaotic modeling for extreme weather prediction.

KHOO Boo Cheongمشاهده پروفایل

استاد

• Fluid Mechanics
• Computational Fluid Dynamics
• Numerical Methods
• +۷ مورد دیگر

Professor KHOO Boo Cheong is a faculty member in the Department of Mechanical Engineering at the National University of Singapore (NUS), affiliated with the College of Design and Engineering. He holds a BA (Hons.) from the University of Cambridge (1980), an MEng from NUS (1984), and a PhD from MIT (1989). His research focuses on Computational Fluid Dynamics (CFD) , Numerical Methods , and Fluid Mechanics , with applications to aerodynamics, turbulence, and fluid-structure interaction. Recent work emphasizes machine learning integration in CFD, bio-inspired UAV design, and icing mechanics for aerospace systems. Key research trends include advancing high-fidelity simulations for complex flows (e.g., turbulence modeling, cavitation suppression), optimizing fluid-structure systems (e.g., lightweight shells, train aerodynamics), and developing novel experimental techniques (e.g., light field PIV, wind spectra analysis). His contributions bridge theoretical CFD innovations with practical engineering challenges in transportation, renewable energy, and robotics. Professor Khoo collaborates on projects involving pressure gain combustion systems , ventilated supercavitating models , and quantum algorithms for fluid dynamics . His lab’s work often combines advanced numerical modeling with experimental validation, addressing real-world issues like wind effects on trains, ice accretion on airfoils, and autonomous navigation systems.

Tong Xinمشاهده پروفایل

دانشیار

• Probability Theory
• Stochastic Optimization
• Machine Learning
• +۳ مورد دیگر

Tong Xin is Associate Professor in the Department of Mathematics at National University of Singapore. His research develops theoretical frameworks for high-dimensional stochastic systems, focusing on algorithmic stability in optimization and sampling methods. Core research areas include dimension-independent convergence guarantees for stochastic gradient descent, efficiency of ensemble Kalman methods in inverse problems, and replica exchange techniques for non-convex optimization. Recent work establishes robustness bounds for Markov Chain Monte Carlo variants and analyzes generalization errors in machine learning. Applications span uncertainty quantification in physical systems, statistical inference for non-i.i.d. data streams, and computational methods for large-scale inverse problems. Editorial roles include SIAM Journal of Uncertainty Quantification and Statistics and Computing.

• Computer Vision
• Deep Learning
• Object Detection
• +۳ مورد دیگر

Chunluan Zhou is a researcher at Nanyang Technological University (NTU), Singapore, with a PhD in Computer Vision and Deep Learning. His research focuses on object detection, pedestrian detection, transformer-based tracking, and occlusion reasoning. He has published extensively in top-tier conferences and journals such as ICCV, CVPR, ECCV, TIP, and TCSVT. Education: PhD from NTU under Prof. Junsong Yuan and Prof. Kai-Kuang Ma, M.Eng from Zhejiang University, and B.Eng from Harbin Institute of Technology. Research Interests: Computer Vision and Deep Learning, with emphasis on object detection, occlusion reasoning, transformer networks, and video analysis. His work addresses challenges like heavily occluded pedestrian detection, weakly supervised learning, and scene-debiasing action recognition. Professional Contributions: Active reviewer for top conferences (CVPR, ICCV, ECCV, NeurIPS) and journals (TIP, TCSVT, PR). His recent research includes scene-debiasing open-set action recognition (SOAR), cyclic self-training for object detection, and transformer-based visual tracking methods like AiATrack. Labs/Teams: Collaborates with Prof. Junsong Yuan's research group, focusing on computer vision and deep learning applications.