جستجوی استاد راهنمای دانشگاهی

Dr. Robin Varennes is a Research Fellow at the School of Physical and Mathematical Sciences , Nanyang Technological University . His research focuses on plasma flow dynamics in tokamaks, turbulence analysis, and machine learning applications for fusion energy systems. Former postdoctoral researcher at the Laboratory of Plasma Physics (France) PhD graduate from Institute of Research on Fusion by Magnetic Confinement (France) Research Fields of Interest: Plasma Physics, Magnetic Confinement Fusion, Turbulence Modeling, Machine Learning Applications Scientific Contributions: Investigated magnetic ripple effects on neoclassical equilibrium and turbulent momentum drive interactions with magnetic braking in tokamak simulations. Aix-Marseille University Doctoral School Thesis Award

• Plasma Physics
• Magnetic Confinement Fusion
• Turbulence Modeling
• +۴ مورد دیگر

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.

• Reinforcement Learning
• Multi-Agent Systems
• Foundation Models
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Assoc Prof Ser Aik QUEK is an Honorary Fellow in the Department of Analytics and Operations at the National University of Singapore (NUS) Business School since January 2022. He holds a PhD in Sciences from the University of California, Berkeley (1987), preceded by a Master of Science from MIT (1981), a Diploma in Mathematical Statistics from the University of Cambridge (1978), and a First-Class Honors Bachelor of Science from Victoria University of Manchester (1975). His research focuses on Transportation & Logistics , Applied Mathematics , and Machine Learning , with notable contributions to manufacturing strategy, healthcare operations, and appointment systems optimization. His work often employs advanced statistical methods like the ACE algorithm to analyze nonlinear relationships in complex systems. Teaching Philosophy: Prioritizes student empowerment through personalized engagement, encouraging innovation and integrity. Courses taught include Predictive Analytics, Decision Analytics, and Business Analytics fundamentals, blending technical skills with strategic thinking. Collaborations: Available for projects in industry partnerships, advisory roles, and interdisciplinary initiatives. Proficient in English and Mandarin. Active on LinkedIn and Facebook for academic networking.

• Transportation and Logistics
• Supply Chain Management
• Applied Mathematics
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Chaithanya Bandi is an Associate Professor at the National University of Singapore (NUS) in the Analytics and Operations Department of the NUS Business School, with a joint appointment in the Department of Mathematics. His research focuses on decision-making under uncertainty, robust optimization, and their applications in operations management, healthcare, e-commerce, and energy systems. He develops robust optimization models for queueing control, risk optimization, and mechanism design. Key research areas include robust queue inference, two-stage distributionally robust optimization, and multi-item auction mechanisms. He has contributed to operational challenges in healthcare (e.g., patient re-entry scheduling), energy systems (electricity generation optimization), and e-commerce (price optimization for fashion products). His work integrates theoretical advancements with practical implementations in large-scale systems. Recent publications emphasize adversarial evaluation of large language models, dynamic scheduling algorithms, and robust policies for uncertain environments. His methodologies often involve novel optimization frameworks and scalable computational approaches. Dr. Bandi holds a PhD in Operations Research and has collaborated with industry leaders like Flipkart and healthcare providers to apply his models in real-world settings. His contributions bridge theoretical rigor and practical applicability in complex operational systems.

• Operations Research
• Robust Optimization
• Queueing Theory
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XU Yixin is a full-time Lecturer in the Department of Computer Science at the School of Computing and Information Systems, Singapore Management University (SMU). They hold a PhD from the University of Melbourne, awarded in 2021, and contribute to both teaching and research in computing disciplines. Their research interests span a broad range of areas in modern computing, with a focus on intelligent and data-driven systems. Key areas include: Artificial Intelligence and Machine Learning Data Management and Mining Decision Making and Optimization Applications in Sustainable Living Their teaching encompasses foundational and applied topics such as Computing Fundamentals, Data Management, and Machine Learning & Applications. Although no recent publications are listed, their expertise suggests active engagement in AI and data science education and applied research. Notable recognitions and scientific awards: No awards listed in the provided information. XU Yixin advises students and contributes to academic supervision, though no specific advisees are named. They are involved in curriculum development and pedagogical initiatives related to computing education. There is no mention of external grants or sponsored research projects. Research and teaching activities are conducted within the academic environment of the School of Computing and Information Systems at SMU, which supports interdisciplinary work in information systems and computational technologies.

• Artificial Intelligence
• Data Science
• Machine Learning
• +۷ مورد دیگر