جستجوی استاد راهنمای دانشگاهی

Revati Godseمشاهده پروفایل

پژوهشگر ارشد

• Smart Grid
• Power System Protection
• Machine Learning
• +۳ مورد دیگر

Dr. Revati Godse is a postdoctoral research fellow at the Singapore University of Technology and Design (SUTD), supervised by Professor Aditya Mathur. She previously served as an Assistant Professor at a private institution in India and earned her doctoral degree from the Visvesvaraya National Institute of Technology (VNIT), Nagpur, India, in December 2020. Her research focuses on Smart Grid technologies, Power System Protection, and Machine Learning applications in electrical engineering. Education: PhD in Electrical Engineering from VNIT, Nagpur (2020). Research Interests: Dr. Godse’s work addresses challenges in power system reliability, including fault detection and classification, smart grid infrastructure, and machine learning-driven solutions for energy systems. She explores interdisciplinary approaches combining signal processing, cybersecurity, and sustainable energy systems. Her recent publications highlight advancements in power grid cyber ranges, electric vehicle charging ecosystems, and fault detection algorithms using mathematical morphology and SVM techniques. These contributions underscore her expertise in both theoretical and applied aspects of electrical engineering. No scientific awards have been explicitly mentioned. She collaborates with researchers at iTrust, the Institute of Trustworthy Internet of Things at SUTD, but no specific grants or advising roles for students are detailed in the provided information. Dr. Godse is affiliated with iTrust, where she contributes to cutting-edge research in trustworthy IoT systems and power grid technologies.

• Quantum algorithms
• Quantum computational complexity
• Classical information theory
• +۳ مورد دیگر

Penghui Yao is a Professor in the Department of Computer Science and Technology at Nanjing University, where he is a member of the CS Theory group. His academic career spans prestigious institutions including the Centre for Quantum Technologies at National University of Singapore, Centrum Wiskunde Informatica (CWI), Institute for Quantum Computing (IQC) at University of Waterloo, and Joint Center for Quantum Information and Computer Science (QuICS) at University of Maryland. Education: BSc in Mathematics from East China Normal University PhD from Centre for Quantum Technologies, National University of Singapore (supervised by Rahul Jain and Miklos Santha) Professor Yao's research focuses on quantum computing and theoretical computer science, with particular expertise in quantum algorithms and computational complexity. His work bridges classical and quantum information theory, with significant contributions to analysis of Boolean functions and their quantum applications. He has developed novel approaches to communication complexity problems in both classical and quantum settings, advancing our understanding of the fundamental limits of computation. His recent publications reveal a strong trend toward practical quantum algorithms with applications in distributed systems, quantum simulation, and quantum cryptography. The breadth of his work spans from theoretical foundations of quantum complexity classes to experimental implementations of quantum processes, demonstrating both depth in theoretical understanding and relevance to practical quantum computing challenges. Professor Yao actively mentors the next generation of quantum computing researchers, supervising multiple PhD and Master's students at Nanjing University while maintaining collaborations with international research groups. His service to the community includes program committee roles for major quantum computing conferences including QIP and TQC.

Ganesh Neelakanta Iyerمشاهده پروفایل

مدرس

• Software Engineering
• Agile Software Development
• Cloud Computing
• +۱۳ مورد دیگر

Ganesh Neelakanta Iyer is a Lecturer in the Department of Computer Science at the School of Computing, National University of Singapore (NUS). He holds a PhD (2012) and MSc (2008) from NUS and a B.Tech. in Computer Science and Engineering from Mahatma Gandhi University, India (2004), where he ranked first. He brings over a decade of industry experience from companies like Salesforce, NXP, and Progress Software, and prior academic roles at Amrita Vishwa Vidyapeetham and IIIT-Hyderabad. His research interests span Software Engineering , Cloud/Edge Computing , Machine Learning , AI for Cultural Heritage , and Software Engineering Education . He founded the STeAdS (Software Engineering and Technological Advancements for Society) research group in 2021, focusing on technology applications in healthcare, education, and traditional arts like Kathakali and Wayang Kulit. The recent publications highlight a strong trend in AI-driven educational technologies , including LLMs for curriculum customization, web-based DevOps learning platforms, and agile project management tools. Another major theme is AI in cultural preservation , with works on Kathakali gesture and facial expression recognition. A third stream involves distributed systems and networking , particularly in edge computing and federated learning. Faculty Teaching Excellence Award 2024, NUS AWS Educate Cloud Faculty Ambassador (2019, 2020) Certified Kubernetes Administrator (CKA) University Topper (First Rank, 2004) NUS Postgraduate Research Scholarship (2009–2012) Dr. Iyer mentors students through UROP, FYP, Master’s, and PhD projects, and has led numerous grants and initiatives in cloud computing education and AI for societal benefit. He has delivered workshops and keynote speeches across the USA, Europe, Australia, and Asia. He actively leads the STeAdS virtual research group, fostering global collaborations. As a maestro in Kathakali, he integrates traditional art with technology, composing and staging performances while applying AI to preserve and analyze this heritage.

Zhize LIمشاهده پروفایل

استادیار

• Optimization
• Federated Learning
• AI Privacy
• +۳ مورد دیگر

Zhize Li is a tenure-track Assistant Professor at the School of Computing and Information Systems, Singapore Management University (since Nov 2023), focusing on optimization, federated learning, and AI privacy. Previously, he held research roles at Carnegie Mellon University, King Abdullah University of Science and Technology (KAUST), and visiting positions at Duke University and Georgia Institute of Technology. Education: PhD in Computer Science, Tsinghua University (2019) MTech, National University of Singapore BEng, Shanghai Jiao Tong University Research Interests: Zhize Li’s work centers on large-scale/distributed/decentralized optimization and private/efficient/resilient federated learning. His research addresses challenges in communication compression, data heterogeneity, and privacy-preserving analytics in AI systems. Publication Trends: His recent articles focus on federated learning frameworks (e.g., X-VFL, SoteriaFL), optimization algorithms (e.g., SIFAR, DESTRESS), and privacy/security in distributed settings (e.g., data reconstruction attacks, three-point compressors). Keywords include Artificial Intelligence , Machine Learning , Privacy-Preserving , and Optimization . Scientific Awards: Rising Star in AI, KAUST AI Initiative (2022) Tsinghua University Outstanding Doctoral Dissertation Award (2019) National Scholarship (top 1%, 2018) Pacesetter of Outstanding Graduates (2014) Advising and Grants: Zhize Li actively recruits fully-funded PhD students, visiting scholars, and research engineers. While specific grants are not detailed, his work has been supported by multiple top-tier publications in journals like JMLR and conferences such as NeurIPS , ICML , and AAAI .

Paul Robert Griffinمشاهده پروفایل

دانشیار

• Artificial Intelligence and Data Science
• Machine Learning & Intelligence
• Information Systems & Technology
• +۵ مورد دیگر

Paul Robert Griffin is a Full-time Faculty member at Singapore Management University (SMU) , serving as an Associate Professor of Information Systems (Practice) in the School of Computing and Information Systems. He earned his PhD from Imperial College London in 1997 and has taught courses on Quantum Computing in Financial Services, Blockchain Technology, and Software Engineering. PhD, Imperial College London, 1997 Teaching: Quantum Computing, Blockchain, Software Engineering Research Interests: Artificial Intelligence, Machine Learning, Digital Transformation, Smart Contracts His research focuses on Quantum Machine Learning (QML) , with applications in financial transaction optimization, credit scoring, and time series forecasting. He has published extensively on hybrid quantum-classical models, explainable quantum neural networks, and decentralized systems. Key themes include noise resilience in QML, quantum finance, and blockchain ethics. The 15 most recent articles highlight trends in Quantum Computing for Finance , Smart Contracts , Decentralized Systems , and Explainable AI . His work bridges theoretical advancements with practical implementations in banking technology, including corporate banking operations and financial risk prediction. Advisees include PhD students ONG Weng Hwee (Lawrence) , Ramaprasad RAMAKRISHNAN , and YAU Hon Tak (Sean) . His work integrates digital transformation with cutting-edge quantum and blockchain technologies to address challenges in financial services and distributed systems.

• Operations Research
• Queueing Systems
• Stochastic Modeling
• +۵ مورد دیگر

Assoc Prof Shuangchi He is affiliated with the Industrial Systems Engineering and Management Department at the National University of Singapore. His research focuses on operations research, stochastic modeling, queueing systems, and their applications in healthcare, transportation, and communications engineering. He holds a PhD from Georgia Institute of Technology (2011). Research interests include queueing design for service systems, diffusion approximations, patient scheduling optimization, and electric vehicle-sharing network analysis. His work bridges theoretical stochastic analysis with practical applications in logistics, healthcare management, and wireless communication systems. Recent publications highlight advancements in randomized routing strategies, on-demand ride-matching algorithms, and inpatient bed assignment models. His contributions to many-server queueing theory and doubly-selective channel estimation demonstrate expertise in both operations research and signal processing domains. Prof He collaborates on topics such as inventory management policies and MIMO channel estimation techniques, reflecting his interdisciplinary approach to solving complex system-level problems.

Zhiguang Caoمشاهده پروفایل

استادیار

• Artificial Intelligence
• Data Science
• Decision Making & Optimization
• +۳ مورد دیگر

Dr. Zhiguang Cao is an Assistant Professor at the School of Computing and Information Systems (SCIS), Singapore Management University (SMU). With a PhD from Nanyang Technological University (2017), his work bridges Artificial Intelligence , Deep Learning , and Combinatorial Optimization to tackle complex logistics and urban mobility challenges. Research Advisor to PhD/Master's students: XIAO Xiangjie, YI Hang, ZHANG Ni Recipient of the World’s Top 2% Scientist recognition (2024), IEEE Transactions on Industrial Informatics Outstanding Paper Award (2022), and Nobert Wiener Review Award (2022) Completed degrees: PhD (NTU), MSc (NTU), BEng (GDUT, China) Research Interests focus on Learning to Optimize (L2Opt) and Neural Combinatorial Optimization , with applications in: Vehicle Routing Problems (TSP, CVRP, PDP) Job Shop Scheduling and Multimodal Optimization UAV Routing , Drone Delivery , and Stochastic Programming His 15 most recent publications (2024-2025) span top venues like NeurIPS , ICML , IJCAI , and IEEE Transactions journals, covering topics from multi-task vehicle routing to graph domain adaptation and learning with large language models . Scientific Awards : World’s Top 2% Scientist (Stanford, 2024) IEEE Transactions on Industrial Informatics Outstanding Paper (2022) Nobert Wiener Review Award (2022) BMW Summer School Excellent Research Work (2014) IEEE Singapore Chapter Tennis Prize (2012) Dr. Cao advises the L2Opt Research Group , which recruits PhD students and remote interns. He has served as Area Chair for ICLR, SIGKDD, ICML, and Senior PC for AAAI and IJCAI. His ongoing projects include Trustworthy Human-AI Optimization (AISG, 2025-2027) and Mobile Crowdsourcing Emergency Supplies (SMU-UofT, 2025-2026).

Tony Quekمشاهده پروفایل

استاد

• Wireless Communications
• Networking
• Network Intelligence
• +۴ مورد دیگر

Dr. Tony Quek is the Associate Provost (Artificial Intelligence and Digital Innovation) and Cheng Tsang Man Chair Professor at Singapore University of Technology and Design (SUTD). He leads the Wireless Networks and Decision Systems (WNDS) Group and serves as Director of the Future Communications R&D Programme. With a PhD from MIT and degrees from Tokyo Institute of Technology, his research focuses on wireless communications, network intelligence, non-terrestrial networks, and 6G technologies. He holds IEEE Fellow, WWRF Fellow, and Academy of Engineering Singapore Fellow titles. Notable awards include the 2024 IIT Bombay Excellence Award, 2020 Stephen O. Rice Prize, and multiple best paper awards. His leadership roles include Head of SUTD's ISTD Pillar and Deputy Director of the SUTD-ZJU IDEA initiative. Research emphasizes seamless integration of AI with communications, including IRS-aided systems, integrated sensing and communications (ISAC), and satellite networks. Over 1,000 publications span topics like UAV networks, federated learning, and MIMO systems. His work bridges theoretical advancements with industrial applications through close industry partnerships.

• Artificial Intelligence
• Data Science
• Data Mining
• +۷ مورد دیگر

ZHU Feida is an Associate Professor of Computer Science and Associate Dean for Partnerships and Engagement at Singapore Management University's School of Computing and Information Systems. He holds the Aptos Move Professorship and specializes in Artificial Intelligence, Data Science, and Blockchain Technology. His research spans federated learning, cybersecurity, cryptocurrency analysis, and privacy-preserving data systems. Education: PhD in Computer Science from the University of Illinois (2009). He teaches courses on Data Mining, Business Analytics, and Computer Analysis Tools. Research focuses on machine learning algorithms, blockchain-enhanced systems, and early detection of malicious activities in cryptocurrencies. Key areas include federated learning frameworks, decentralized data governance, and anomaly detection in large networks. Award: Aptos Move Professorship (Recipient). Advising: Supervises students including CHENG Ling, LIU Huiwen, and THIA Boon Sing. His work addresses challenges in data assetization, secure aggregation in federated systems, and interdisciplinary applications of AI. Labs/Teams: Engaged in collaborative projects on blockchain security and smart data analytics through initiatives like the International Workshop on Smart Data for Blockchain (SDBD).

Kai Fong Ernest Chongمشاهده پروفایل

استادیار

• Combinatorics
• Commutative Algebra
• Artificial Intelligence
• +۵ مورد دیگر

Kai Fong Ernest Chong is an Assistant Professor in the Information Systems Technology and Design (ISTD) pillar at Singapore University of Technology and Design (SUTD). He also served as an adjunct assistant professor at Nanyang Technological University's Division of Mathematical Sciences. His research focuses on combinatorics, commutative algebra, and artificial intelligence, particularly in algebraic machine reasoning and robust AI systems. He leads SUTD's thrust on the fundamentals of AI systems and has secured over SGD 8.3 million in research grants as principal investigator (PI) or co-investigator (Co-I). Ernest holds a PhD in Mathematics from Cornell University (2015) under Edward Swartz. He has extensive teaching experience, including courses on algorithms, discrete mathematics, and probability. His work includes pioneering algebraic machine reasoning, connecting commutative algebra to AI, and developing frameworks for federated learning and robustness against data noise. Notable achievements include a 2023 breakthrough in algebraic machine reasoning surpassing human performance in IQ test tasks and a 2003 National Science Talent Search Grand Prize for his work on twin primes. He supervises numerous PhD, master’s, and postdoctoral researchers and actively collaborates with industry partners through projects like ASTRALIS and Alpha-DRACONIS.

Tay Yong Chiangمشاهده پروفایل

استاد

• Performance Evaluation
• Database Systems
• Distributed Algorithms
• +۷ مورد دیگر

Professor Tay Yong Chiang is affiliated with the National University of Singapore as a Professor in the Department of Computer Science . He is also a Fellow at Tembusu College, contributing to academic community engagement. His career spans academia and industry, including past roles at Sequoia Systems, Microsoft, Intel Research, and VMware. Ph.D. in Applied Mathematics from Harvard University B.Sc. in Mathematics (Honours) from the University of Singapore Research focuses on performance modeling and database systems , with specific interests in caching systems, wireless protocols, Internet traffic analysis, concurrency control, and the application of local time in distributed systems. He has contributed to journals like JACM, ACM TODS, and conferences such as SIGMOD, VLDB, and INFOCOM. His publications span systems performance evaluation (1995–2017), covering database transactions , wireless protocols , caching , and distributed computing . Key journals include ACM Transactions on Modeling and Performance Evaluation of Computing Systems. He has authored books like Analytical Performance Modeling for Computer Systems and Locking Performance in Centralized Databases , and taught courses such as CS1231S Discrete Structures.

• Computer Architecture
• Computer Security
• Quantum Computing
• +۵ مورد دیگر

Assoc Prof Anupam Chattopadhyay is an Associate Professor in the College of Computing & Data Science at Nanyang Technological University (NTU), Singapore. He also holds a courtesy appointment in the School of Physical & Mathematical Sciences. His research focuses on computer architecture, security, design automation, and quantum computing. Anupam received his PhD from RWTH Aachen University in 2008, followed by roles at CoWare R&D and RWTH Aachen as a Junior Professor before joining NTU in 2014. Education: B.E., Jadavpur University, India MSc, ALaRI, Switzerland PhD, RWTH Aachen University, Germany Research Interests: Anupam’s work spans quantum computing, hardware security, AI security, post-quantum cryptography, and emerging technologies. His contributions include novel high-level synthesis techniques for cryptography, reliability estimation flows for embedded processors, and exploration of coarse-grained reconfigurable architectures. His research has been featured in major outlets like The Economist and Asian Scientist. Awards: Borcher's plaque (2008) for outstanding doctoral dissertation Nomination for Best IP Award (ACM/IEEE DATE 2016) Nomination for Best Paper Award (International Conference on VLSI Design 2018) Advising & Grants: Anupam leads a team of over 20 researchers, overseeing projects funded by various grants. He has advised numerous doctoral students and collaborates with institutions like Temasek Labs and the Indian Statistical Institute. Labs & Teams: His research group focuses on advanced topics in secure computing, quantum-resistant systems, and hardware-software co-design, leveraging cutting-edge tools and platforms for next-generation technologies.

Vladan Babovicمشاهده پروفایل

استاد

• Hydroinformatics
• Artificial Intelligence
• Machine Learning
• +۵ مورد دیگر

Professor Vladan Babovic is a leading academic and scientist in hydroinformatics at the National University of Singapore's Department of Civil Engineering. His career spans over three decades, focusing on data-driven research, computational hydraulics, and decision-making under climate uncertainties. He holds adjunct roles at the University of Idaho and University of Iowa. Babovic pioneered research institutes like the Singapore Delft Water Alliance (SDWA) and NUSDeltares, recognized with the Albert Winsemius Award in 2014. Education includes a Double Ph.D. from Delft University of Technology, M.Sc. in Hydroinformatics, and a B.Sc. in Civil Engineering from the University of Sarajevo. His expertise spans artificial intelligence, machine learning, hydrological modeling, and real options analysis for infrastructure resilience. Key contributions include genetic programming applications in hydrology and AI-driven climate adaptation strategies. Research interests emphasize integrating AI with environmental systems, including deep learning for flood mechanisms, physics-informed rainfall-runoff models, and data assimilation techniques. He has advised multiple institutions and served on councils like the International Association for Hydro-Environmental Research and the Singapore Coastal Climate Adaptation Panel. Notable awards include the IWA Fellowship (2012), Arthur Thomas Ippen Award (1999), and recognition as a Chartered Engineer. His work bridges academia and industry, addressing global water challenges through innovative methodologies and adaptive infrastructure design.

LI Rongمشاهده پروفایل

استاد

• Cellular Dynamics
• Mechanobiology
• Biomechanics
• +۶ مورد دیگر

LI Rong is a Professor (courtesy appointment) in the Department of Mechanical Engineering at the National University of Singapore (NUS), and Director of the Mechanobiology Institute (MBI), a Research Centre of Excellence at NUS. She concurrently holds a Distinguished Professorship in the Department of Biological Sciences at NUS. Previously, she served as Bloomberg Distinguished Professor of Cell Biology at Johns Hopkins School of Medicine and Department of Chemical and Biomolecular Engineering at Johns Hopkins University. Her research focuses on cellular dynamics and mechanics, integrating genetics, quantitative imaging, biophysical measurements, mathematical modeling, genomics, and proteomics. This interdisciplinary work aims to understand how eukaryotic cells transmit genomes, adapt to environments, and organize for specialized functions. Her recent publications span entity profiling, temporal data management, and big data analytics systems. Key contributions include the MAROON+ system for temporal entity profiling, HC-Store for hybrid MapReduce-RDBMS systems, and frameworks for optimizing algorithmic trading strategies using MapReduce. LI Rong's leadership roles include directing the Mechanobiology Institute and holding distinguished appointments across multiple institutions. Her work bridges engineering, biology, and computational sciences, reflecting her expertise in both mechanobiology and big data systems.

Chee Yeow Mengمشاهده پروفایل

استاد

• Coding Theory
• Combinatorics
• Data Science
• +۳ مورد دیگر

Chee Yeow Meng is the Provost and Chief Academic & Innovation Officer at the Singapore University of Technology and Design (SUTD), effective April 2025. He holds a Professor rank and oversees curricular, research, and innovation affairs. Previously, he served as Vice President (Innovation and Enterprise) at NUS and held senior roles in academia and public service, including leadership positions at the National Computer Board and Infocomm Development Authority. His education includes a BMath (Hon) and MMath from the University of Waterloo (1988-1989), followed by a PhD in Computer Science (1996). His research focuses on combinatorics' intersection with computer science, particularly coding theory, extremal set systems, and AI applications. He has pioneered work in error-correcting codes, combinatorial cryptography, and data science. Prof Chee is an associate editor for IEEE Transactions on Information Theory and a Fellow of the Institute of Combinatorics and its Applications. His awards include the Public Administration Medal (Silver, 2018) and the Long Service Award (NTU, 2018). He has founded multiple startups and holds patents in coding technologies. His recent publications emphasize innovations in coding theory applications (e.g., domain wall memories, DNA storage) and machine learning for combinatorial optimization. He actively contributes to national committees and international forums on innovation policy and AI ethics.