جست‌وجوی استاد و پژوهشگر

Rahul Jainمشاهده پروفایل

استاد

• Quantum Computation
• Information Theory
• Complexity Theory
• +۳ مورد دیگر

Rahul Jain is a Professor in the Department of Computer Science at the National University of Singapore (NUS), School of Computing. He was promoted to full Professor from January 2020, having previously served as Associate Professor (July 2013-July 2013) and Assistant Professor (November 2008-July 2013). He is also a Principal Investigator at the Centre for Quantum Technologies (CQT), Singapore since November 2008. Dr. Jain earned his Ph.D. in Computer Science from Tata Institute of Fundamental Research, Mumbai (2003) and B.Tech. in Electrical & Electronics Engineering from Indian Institute of Technology, Mumbai (1997). Prior to joining NUS, he conducted postdoctoral research at UC Berkeley (2004-2006) and at the Institute for Quantum Computing, University of Waterloo, Canada (2006-2008). His research spans quantum computation, information theory, complexity theory, communication complexity, and cryptography. Dr. Jain has made significant contributions to quantum information theory, particularly in quantum communication complexity, quantum key distribution, and quantum algorithms. His work bridges theoretical computer science with quantum information processing, exploring fundamental limits of quantum computation and communication. His research demonstrates strong expertise in both theoretical proofs and practical applications of quantum information principles. Analysis of Dr. Jain's recent publications (2022-2025) reveals a consistent focus on quantum cryptography foundations, quantum communication protocols, and quantum information theory. His work frequently appears in top theoretical computer science venues including FOCS, STOC, and QIP, as well as leading journals like IEEE Transactions on Information Theory. Key themes include non-malleable quantum codes, quantum state redistribution, quantum communication complexity, and quantum cryptographic protocols with rigorous security proofs. Award under the VISITING ADVANCED JOINT RESEARCH FACULTY SCHEME (VAJRA) 2017-18 by Department of Science and Technology, Government of India BEST of 2016 by ACM Computing Reviews Young Researcher Award, National University of Singapore, 2012 Best paper award at STOC 2010 IBM Distinguished Dissertation Award, 2005 TAA-Sasken Best Thesis Award, 2005-2006 Dr. Jain has supervised numerous graduate students who have secured positions at Harvard University, IBM, JPMorgan Chase, University of Waterloo, and other prestigious institutions. His research is supported by significant grants including the VAJRA Faculty Scheme award. He serves as Associate Editor for the Journal of Computer and System Sciences and on program committees for major conferences including ITCS 2025, FOCS 2022, and QIP 2022-2014. At CQT, he leads research in quantum information theory and quantum algorithms, contributing to Singapore's position as a regional hub for quantum computing research.

• Programming Languages
• Software Engineering
• Compilers
• +۵ مورد دیگر

Manuel Rigger is an Assistant Professor at the National University of Singapore in the School of Computing and leads the Trustworthy Engineering of Software Technologies (TEST) Lab . His research focuses on improving data-centric systems , particularly their reliability, having found over 1,000 unique bugs in database systems. Education : PhD in Computer Science (2019) and MSc in Software Engineering (2015) from Johannes Kepler University Linz; MPhil in Chinese Philosophy (2015) from Xiamen University Research Highlights : Developed SQLancer – an automated testing framework that found 500+ bugs in DBMSs; created Query Plan Guidance (QPG) for efficient logic bug detection; received best paper awards at ICSE '23 and EuroSys '24 Scientific Awards : Recipient of 6 distinguished artifact/reviewer awards Major industry support from Google, AWS, and Microsoft Developed tools adopted by Oracle GraalVM and SQLite Teaching : Lecturer for CS3213 Foundations of Software Engineering and CS6223 Advanced Topics in Software Testing . Supervises multiple PhD/MSc theses on database testing and compiler reliability.

Leow Wee Khengمشاهده پروفایل

دانشیار

• Medical Image Analysis
• Computer Vision
• 3D Modeling
• +۵ مورد دیگر

Associate Professor Leow Wee Kheng is affiliated with the Department of Computer Science at the School of Computing, National University of Singapore . His career spans over three decades with expertise in medical image analysis , computer vision , and surgical simulation . Ph.D. in Computer Science, University of Texas at Austin (1994) M.Sc. in Computer Science, National University of Singapore (1989) B.Sc. in Computer Science, National University of Singapore (1985) His research focuses on medical image analysis for craniofacial surgery and stroke diagnosis, 3D modeling of anatomical structures, and computer vision techniques like robust PCA and texture analysis . Recent work includes knee joint motion modeling and forearm rotation simulation for clinical applications. Key trends in his 2017-2025 publications involve skull reconstruction algorithms , multi-objective optimization for digital media, subject-specific biomechanical modeling , and low-rank decomposition techniques in visual computing. Collaborations include institutions like Singapore General Hospital and National Taiwan University Hospital . Scientific Awards : CAIP 2017 Best Paper Award 2007 Andrew P. Sage Best Transactions Paper Award Faculty Teaching Excellence Award (AY2015/16) Annual Teaching Excellence Award (AY2015/16) He has mentored numerous students in medical imaging , computer vision , and biomedical modeling . Current and former advisees include Chen Ying , Vineta Lum Lai Fun , and Long Huizhong (Ph.D.).

Heyuan Shiمشاهده پروفایل

دانشیار

• Software Quality Assurance
• Kernel Fuzz Testing
• Operating System Security
• +۳ مورد دیگر

Heyuan Shi is an Associate Professor at the School of Electronic Information, Central South University since 2023. He earned his B.S. (2015) and Ph.D. (2020) from Central South University and Tsinghua University respectively. His research focuses on software quality assurance with emphasis on kernel fuzz testing , open source software security , and AI application security . Presided over 10+ projects including NSFC General Program (No.62472448) and National Key R&D Sub-Project Published 30+ CCF-A/B papers across software security, machine learning, and quantum testing Supervised 15+ graduate students in software quality assurance areas His recent 2024-2025 publications demonstrate expertise in: LLM-enhanced patch classification Quantum neural network verification Hypergraph adversarial attacks RTOS fuzzing techniques Scientific recognition includes: 2024 Beijing Science & Technology Progress Award (First Prize) Hunan Province Xiaohe Sci-Tech Talent (2023) China Association for Science & Technology Young Talent (2025-2027) Active in academic service as PC member for FM2024 and reviewer for IEEE Transactions journals. Leads industry collaborations with Alibaba and Beijing Institute of Aerospace Metrology.

Guillaume A SARTORETTIمشاهده پروفایل

استادیار

• Robotics
• Multi-Agent/Multi-Robot Systems
• Distributed/Decentralized Control
• +۴ مورد دیگر

Guillaume A SARTORETTI is an Assistant Professor in the Mechanical Engineering Department at the National University of Singapore (NUS), part of the College of Design and Engineering. He specializes in distributed/decentralized coordination of multi-agent systems, with a focus on robotics, stochastic modeling, and reinforcement learning. His work spans applications in multi-robot systems, articulated robots, and swarm intelligence. Joined NUS in 2019 after a postdoctoral fellowship at Carnegie Mellon University (CMU) and a PhD from EPFL. Education: PhD in Robotics (EPFL, 2016); MSc and BSc in Mathematics/Computer Science (University of Geneva). Research interests include: Multi-agent pathfinding Decentralized control policies Swarm intelligence Reinforcement learning applications in robotics Recent publications emphasize scalable solutions for multi-agent systems, traffic signal control, and safe robotic exploration. His 2018 MFI postdoctoral fellowship recognized work on distributed reinforcement learning for pathfinding. Current projects involve bio-inspired locomotion and collaborative learning frameworks for heterogeneous robots.

• Mobile Generative AI
• Edge General Intelligence
• Quantum Computing and Networking
• +۳ مورد دیگر

Roles & Affiliations: Professor and President's Chair Professor in Computer Science and Engineering at Nanyang Technological University (NTU), Singapore. Member of the IEEE and IET, with roles in editorial boards of major journals like IEEE Transactions on Network Science and Engineering and IEEE Communications Surveys & Tutorials. Current positions: Editor-in-Chief of IEEE Transactions on Network Science and Engineering, Area Editor in multiple journals including IEEE Communications Surveys and Tutorials. Education: Ph.D. (2008) and M.Sc. (2005) in Electrical and Computer Engineering from the University of Manitoba, Canada. B.Eng. (1999) in Computer Engineering from King Mongkut's Institute of Technology Ladkrabang, Thailand. Research Interests: Focuses on mobile generative AI, edge general intelligence, quantum networking, incentive mechanisms, and wireless communication systems. Explores applications in 6G, IoT, UAV networks, and secure communication. Recent Articles & Trends: 15 most recent articles highlight advancements in generative AI for wireless networks, quantum computing integration, secure communication protocols, and AI-driven network optimization. Key themes include semantic communication frameworks, RIS-aided systems, and federated learning in edge networks. Awards: Over 20+ prestigious awards including IEEE Fellow (2017), IET Fellow (2022), Stuart Meyer Memorial Award (2024), and multiple best paper awards at top conferences like IEEE WCNC and IEEE ICC. Advising & Grants: Advisor to numerous students (not listed explicitly). Active in funding initiatives for AI in wireless systems, quantum networks, and low-altitude economy networking. Leads projects on GenAI for networking and 6G innovations. Labs & Teams: Research focuses on CCDS labs at NTU, collaborating on projects like GenAI for ISAC, mobile edge computing, and secure federated learning systems.

DU Mingمشاهده پروفایل

استاد مهمان

• Global Economic Governance
• International Law
• Rule of Law in China
• +۳ مورد دیگر

Professor DU Ming is a Visiting Professor in Chinese Law and Co-Director of the Global Policy Institute at Durham University. He holds an LLM from Harvard Law School and a DPhil from the University of Oxford. His research focuses on global economic governance, China's approach to international law, and the development of legal frameworks in contemporary China. He advises on complex international disputes and sits on editorial boards of leading law journals. **Education:** Tsinghua University School of Law (China) LLM, Harvard Law School (Victor and William Fung Fellow) DPhil, University of Oxford (Clarendon Scholar) **Research Interests:** His work bridges legal theory and practice, particularly in cross-border trade/investment law, corporate governance, and the ethical implications of emerging technologies. Recent publications explore federated learning governance, model licensing, and AI ethics within legal systems. **Awards:** Victor and William Fung Fellowship (Harvard) Clarendon Scholarship (Oxford) His advisory roles and legal practice in New York and Beijing inform his research on transnational legal challenges. Collaborations span technical and legal domains, addressing issues like data privacy in federated learning systems.

Shaohui Foongمشاهده پروفایل

دانشیار

• Robotics
• Aerospace Engineering
• Control Systems
• +۴ مورد دیگر

Shaohui Foong is an Associate Professor in the Engineering Product Development (EPD) pillar at Singapore University of Technology and Design (SUTD). He previously served as a Visiting Assistant Professor at MIT's Department of Mechanical Engineering (2011). His research focuses on innovative robotics and UAV systems, medical technology, and design-centric pedagogy. Core projects include magnetic localization for medical devices, nature-inspired aerial robotics (e.g., THOR hybrid UAV), and competitive engineering design activities like Designettes. Research interests span biomimetic flight systems, autonomous navigation, and interdisciplinary educational frameworks. Notable innovations include the Transformable HOvering Rotorcraft (THOR), which merges fixed-wing and rotor-wing capabilities, and magnetic localization for nasogastric tube tracking. His work emphasizes practical applications in healthcare, infrastructure inspection, and environmental monitoring. Teaching emphasizes ethical engineering practice and hands-on design. He actively mentors students across PhD, master’s, and undergraduate levels, offering research opportunities in robotics, control systems, and medical technology. Collaborative projects with industry and academic partners are encouraged, with a focus on sustainability and technological innovation. Current research trends reflect a blend of bio-inspired design, advanced control algorithms, and cross-disciplinary problem-solving. Recent publications highlight advancements in monocopter dynamics, hybrid UAV architectures, and sensor integration for medical and industrial applications.

Yan Jieمشاهده پروفایل

استاد

• Biophysics
• Molecular Biology
• Mechanobiology
• +۳ مورد دیگر

Professor Yan Jie is a distinguished academic at the National University of Singapore, holding faculty positions at the Mechanobiology Institute and the Department of Physics. He also maintains an affiliation with the Centre for BioImaging Sciences under the Department of Biological Sciences. Professor, Mechanobiology Institute (MBI), NUS Professor, Department of Physics, NUS Professor, Centre for BioImaging Sciences, NUS Dr. Yan's research lies at the intersection of biophysics, molecular biology, and mechanobiology. His work focuses on understanding how mechanical constraints influence biomolecular stability, including: Force-dependent conformations and interactions of nucleic acids and proteins Mechanosensing at cell-ECM adhesion and cell-cell junctions Chaperone-mediated protein folding mechanisms Chromosome packaging and DNA damage repair dynamics His recent publications highlight advancements in: Mechanical stabilization of biomolecular complexes via energy landscape modeling Multi-domain interactions in cytoskeletal proteins Force-transducing mechanisms in bacterial membranes Calcium signaling in stem cell mechanical properties Dr. Yan has mentored a diverse team including PhD students Kayo Kumadaki, Lin Yueying, Guo Yanyu, Sun Yuze, Liu Jingzhun, Dasvit Shetty, and former student Pang Si Ming. His lab integrates single-molecule biophysical methods with theoretical modeling to explore mechanical regulation at the molecular and cellular level.

• Cloud Computing
• Cloud Engineering
• Information Systems
• +۲ مورد دیگر

ZHOU Yu Xuan, Sophia serves as an Adjunct Lecturer at the School of Computing and Information Systems (SCIS) within Singapore Management University (SMU), contributing to the institution's academic mission in technology education. Her educational background includes: PhD in Electrical and Computer Engineering from National University of Singapore, Singapore Her research trajectory centers on Cloud Computing infrastructure, with specialized expertise in Cloud Management and Engineering. This encompasses resource orchestration, service deployment frameworks, and operational optimization of distributed cloud environments, addressing critical industry challenges in scalability and system reliability. Her professional activities align with SCIS's focus on cutting-edge information systems development and practical technology implementation.

• Supply Chain Coordination
• Spreadsheet Modeling
• Decision Making & Optimization
• +۳ مورد دیگر

Professor Michelle Cheong Lee Fong is a full-time faculty member at the School of Information Systems, Singapore Management University. She holds leadership roles as Associate Dean for Post-Graduate Professional Education and Director of the Doctor of Engineering program, and is actively involved in designing educational frameworks for technology-driven learning. Current affiliations: Singapore Management University (School of Information Systems) Research focus: Supply chain coordination, spreadsheet modeling, and educational technology Key courses taught: Computer as an Analysis Tool, Financial Modeling, Process Modeling Her research interests in supply chain coordination span strategic hub location optimization, tactical supplier coordination, and operational transportation planning. She also specializes in spreadsheet modeling for business decision-making, having developed textbook resources and case studies for logistics networks and financial planning. Recent work explores AI's role in digital education, including ChatGPT's impact on assessment design and ethical considerations in AI-driven pedagogy. The articles she has written or co-authored demonstrate expertise in operations research, educational technology, and AI applications. Topics include optimization theory, heuristic algorithms for scheduling, and digital assessment frameworks that integrate learning analytics. Her work bridges spreadsheet modeling's pedagogical value with modern challenges like ChatGPT's influence on student learning. Her teaching portfolio includes courses such as IS102 (Computer as an Analysis Tool), IS304 (Process Modeling), and FNCE645 (Financial Modeling). These courses emphasize practical skills in translating business requirements into technology solutions through spreadsheet-based analytical frameworks.

Rakesh Nandiمشاهده پروفایل

پژوهشگر ارشد

• Queueing systems
• Stochastic modelling
• Numerical optimisation
• +۱ مورد دیگر

Rakesh Nandi is a Research Fellow at the Aviation Studies Institute (ASI) of Singapore University of Technology and Design (SUTD). He previously held a research fellowship under Dr. Shrutivandana Sharma at the Engineering Systems and Design (ESD) school at SUTD. His work focuses on optimizing and analyzing air traffic networks, with projects such as Network Capacity and Network Collaboration under Professor Peter Jackson. Rakesh earned his Ph.D. in Mathematics from National Institute of Technology Raipur (2020) and an M.Sc. in Applied Mathematics from Guru Ghasidas University (2013). His research interests span queueing systems , stochastic modeling , numerical optimization , and network modeling/scheduling . He collaborates on projects requiring advanced computational and analytical methods for discrete-time queueing systems. His recent publications (2018–2022) emphasize queueing theory applications, stochastic processes, and optimization in discrete-time systems. Key topics include D-BMAP/G/1 queues, GI/D-MSP queue analysis, and N-policy control strategies. While no scientific awards are listed, Rakesh demonstrates active research in operations research and applied mathematics. He has no documented advisees or grants mentioned. He contributes to interdisciplinary teams at ASI and ESD, focusing on aviation systems and network efficiency.

Seth Gilbertمشاهده پروفایل

دانشیار

• Distributed Systems
• Algorithmic Techniques
• Blockchain Technology
• +۳ مورد دیگر

Seth Gilbert is the Dean's Chair Associate Professor and Head of the Department of Computer Science at the National University of Singapore. His research focuses on designing robust, scalable algorithms for large-scale distributed systems, particularly in the domains of Byzantine agreement, dynamic networks, and contention resolution. He holds a PhD from MIT (advised by Nancy Lynch) and completed a postdoc at EPFL under Rachid Guerraoui. His work emphasizes three core techniques: accountability (identifying network failures), work-sharing (task distribution in asynchronous environments), and contention resolution (efficient resource allocation). Notable contributions include the DConstructor (PODC 2020) and Polygraph (ICDCS 2021) protocols for accountable Byzantine agreement. He has received multiple awards, including the Edsger W. Dijkstra Prize (2021) and Best Paper Awards at DISC, ICDCS, and IPDPS. Prof. Gilbert has served as program chair for DISC 2021, OPODIS 2019, and SPAA 2016, and currently chairs the DISC Steering Committee. His career includes industry experience at Microsoft (Visual Studio team) and early work on solar car engineering at Yale University.

Lin Weisiمشاهده پروفایل

استاد

• Artificial and Augmented Intelligence
• Computer Science and Engineering
• Electrical and Electronic Engineering
• +۵ مورد دیگر

Prof. Lin Weisi is an Associate Dean (Research) and Professor at the College of Computing & Data Science, Nanyang Technological University (NTU). He holds the President's Chair in Computer Science and is a Fellow of IEEE and IET. His research focuses on image processing, video compression, multimedia communication, and AI-driven applications. He has authored over 400 refereed papers, holds 16 patents, and contributed to international standards. Notable contributions include the COVID-19 Test Strip Reader and databases like the Retargeted Image Subjective Quality Database . He leads the ROSE Lab and has supervised numerous students and researchers globally. His awards include Fellowships from SIET and excellence recognitions in China and Singapore. Educational Background: B.Sc./M.Sc. (Electronics/Digital Signal Processing, Sun Yat-Sen University), Ph.D. (Computer Vision, King’s College London). Research Interests: Perception-based modeling, neural network compression, AI for environmental monitoring, and perceptual quality assessment. His work bridges academic research and industrial deployment, emphasizing practical applications. Grants & Projects: Managed over 10 major projects in digital multimedia, including collaborations with institutions like the Institute for Infocomm Research and Tencent. Current initiatives include lightweight deep learning for image processing and AI-driven climate monitoring. Awards & Honors: Recognized as a Chartered Engineer, Honorary Fellow of SIET, and recipient of prestigious awards in China and internationally.

Tianyang Huمشاهده پروفایل

استادیار

• Statistical Machine Learning
• Representation Learning
• Deep Generative Modeling
• +۷ مورد دیگر

Tianyang Hu is a postdoctoral researcher at the National University of Singapore, set to join the Chinese University of Hong Kong, Shenzhen as an Assistant Professor in Fall 2025. His academic journey includes a PhD in Statistics from Purdue University under Prof. Guang Cheng, an M.S. in Statistics from the University of Chicago, and a B.S. in Mathematics from Tsinghua University. PhD in Statistics, Purdue University M.S. in Statistics, University of Chicago B.S. in Mathematics, Tsinghua University His research lies at the intersection of statistics and artificial intelligence, focusing on statistical machine learning, representation learning, and deep generative modeling . He is particularly interested in the theoretical foundations of AI, including diffusion models, large language models (LLMs), and overparametrized neural networks. His recent work explores the duality between prompting and fine-tuning, contrastive learning mechanisms, and efficient sampling in generative models. The trends in his recent publications show a strong emphasis on diffusion models , especially in conditional generation, sampling efficiency, and integration with language models. His work spans both theoretical analysis and practical algorithm design, with applications in image generation, 3D modeling, and multimodal reasoning. He has contributed to understanding the behavior of in-context learning in transformers and the role of regularization in deep networks. His scientific achievements include: Spotlight presentation at NeurIPS 2023 Spotlight presentation at NeurIPS 2022 Oral presentation at ICML Workshop 2025 Tianyang Hu is actively building his research group and is seeking PhD/MPhil students and research assistants with strong theoretical and practical AI skills. He has held research positions at Huawei Noah’s Ark Lab and is currently mentored by Prof. Kenji Kawaguchi at NUS. His work has been supported by collaborations across academia and industry, though specific grants are not listed in the text. While no formal lab name is mentioned, his future group at CUHK-Shenzhen is expected to focus on theoretical AI and generative models , with research directions in LLMs, diffusion models, and representation learning.