جستجوی استاد راهنمای دانشگاهی

Ke-Wei Huangمشاهده پروفایل

دانشیار

• Machine Learning
• FinTech
• Data Science & Business Analytics
• +۶ مورد دیگر

Ke-Wei Huang is an Associate Professor at the Department of Information Systems and Analytics, National University of Singapore (NUS), and Executive Director of the Asian Institute of Digital Finance (AIDF). He joined NUS in 2007, holding prior roles including Assistant Dean of Graduate Studies and founding director of NUS's FinTech MSc/PhD programs. Huang holds a PhD from NYU Stern and degrees from National Taiwan University. His research focuses on machine learning for social science, FinTech, data mining in finance, and IT labor economics. Notable works include studies on hierarchical forecasting, AI's impact on jobs, and pricing strategies for digital goods. Education: PhD in Information Systems, NYU Stern (2007) MSc in Information Systems, NYU Stern (2002) MBA in Finance, National Taiwan University (1997) BSc in Electrical Engineering, National Taiwan University (1995) Research Interests: Machine Learning applications in FinTech, data science for financial forecasting, labor economics of IT professionals, and pricing models for digital goods. His work bridges econometrics and computational methods, addressing challenges like missing data, measurement bias, and hierarchical variable decomposition. Awards & Grants: $1.6M Singapore NRF Grant (2020) for AI-driven financial text analysis Multiple teaching excellence awards (2013–2016) Best paper nominations at ICIS, WITS, and CSWIM Advising & Labs: Advised 8 PhD graduates, including faculty at Chinese University of Hong Kong and South China University of Technology. Active in FinTech education, leading courses like Machine Learning for Finance and Risk Analytics. Research teams focus on AI's societal impact, financial innovation, and data-driven decision-making.

Muhammad Azmi UMERمشاهده پروفایل

مدرس

• Machine Learning
• Data Science
• Cyber Physical Systems
• +۳ مورد دیگر

Dr. Muhammad Azmi UMER is a Lecturer at DHA Suffa University and a Ph.D. Scholar at Karachi Institute of Economics and Technology, Pakistan. His research focuses on Machine Learning applications in Cyber Physical Systems (CPS), particularly intrusion detection in industrial control systems like the SWaT testbed. He holds a Master’s in Computer Science from Karachi Institute of Economics and Technology and a Bachelor’s from the University of Karachi. His academic work emphasizes cybersecurity challenges in smart grids, IoT healthcare systems, and adversarial machine learning techniques. Key contributions include developing decision tree-based intrusion detection frameworks and adversarial attack simulations for industrial systems. He collaborates with researchers like Dr. Jit BISWAS and Dr. Eyasu G. CHEKOLE within interdisciplinary teams. Publications span machine learning applications in smart cities, CPS security protocols, and IoT conceptual frameworks. His research bridges theoretical models with practical implementations in critical infrastructure security and urban technology systems.

Bo Anمشاهده پروفایل

استاد

• Artificial Intelligence
• Multiagent Systems
• Computational Game Theory
• +۹ مورد دیگر

Bo An is a President's Chair Professor and Head of the Division of Artificial Intelligence at the College of Computing and Data Science , Nanyang Technological University, Singapore . He also holds a courtesy appointment as Professor at the School of Physical & Mathematical Sciences and serves as Director of the Centre of AI-for-X. Previously, he was a Nanyang Assistant Professor (2014-2018), Associate Professor at the Chinese Academy of Sciences (2012-2013), and Postdoctoral Researcher at the University of Southern California (2010-2012). His academic journey began with B.Sc. and M.Sc. degrees from Chongqing University, followed by a Ph.D. in Computer Science from the University of Massachusetts, Amherst (advised by Victor Lesser). Research Interests : Artificial Intelligence Multiagent Systems Computational Game Theory Reinforcement Learning Automated Negotiation Optimization Research Impact : Applications in infrastructure security (deployed by US Coast Guard and Federal Air Marshals), e-commerce, sensor networks, and financial technology. Over 150 publications in top venues like AAMAS, IJCAI, AAAI, ICML, NeurIPS, KDD, and ACM/IEEE Transactions. Scientific Recognition : 2010 IFAAMAS Victor Lesser Distinguished Dissertation Award 2012 INFORMS Wagner Prize 2018 & 2022 Nanyang Research Awards 2017 Microsoft Collaborative AI Challenge IEEE Intelligent Systems 'AI's 10 to Watch' (2018) Leadership Roles : Editor-in-Chief of IEEE Intelligent Systems, Associate Editor for AIJ, JAAMAS, and ACM Transactions. Served as General Co-Chair for AAMAS'23 and Program Chair for IJCAI'27.

• Distributed Systems Security
• Distributed Algorithms
• Algorithms in Networking
• +۳ مورد دیگر

Haifeng Yu serves as Dean's Chair Associate Professor in the Department of Computer Science at the National University of Singapore's School of Computing. He actively contributes to academic governance as a Member of the Faculty Teaching Excellence Committee (FTEC) and teaches graduate courses including CS4231 Parallel and Distributed Algorithms and CS5223 Distributed Systems. His educational background includes: Ph.D. in Computer Science, Duke University, USA (2002) M.S. in Computer Science, Duke University, USA (1999) B.E. in Computer Science, Shanghai Jiao Tong University, P.R. China (1997) Professor Yu's research centers on Distributed Systems Security —particularly blockchain vulnerabilities like sybil attacks—and Distributed Algorithms for dynamic networks. His work bridges theoretical foundations with practical applications in vehicle-to-vehicle communication and disaster recovery systems, where mobile devices form ad-hoc networks when infrastructure fails. Current projects include BCube and Flint for overcoming blockchain's 50% barrier and Massively Parallel Aggregation in dynamic networks. Analysis of his 2018-2022 publications reveals a dominant focus on blockchain scalability challenges and dynamic network theory. Key trends include developing Byzantine fault tolerance beyond malicious majority thresholds, establishing fundamental lower bounds for network diameter uncertainty, and optimizing sublinear algorithms for T-interval dynamic networks. His work consistently targets top-tier venues like IEEE Security & Privacy (Oakland), JACM, and PODC. His research excellence is recognized through multiple prestigious awards: Best Paper at ACM SPAA (2020) Best Paper at ACM SIGCOMM (2010) Best Paper at ACM/IEEE IPSN (2009) Best Paper at USENIX NSDI (2006) Professor Yu mentors graduate students including Yuda Zhao and Irvan Jahja, with whom he co-authored seminal works on network diameter costs and dynamic network lower bounds. His research is supported by competitive grants enabling participation in premier conferences where he serves on program committees for PODC, DISC, SIGCOMM, CCS, and Oakland. He leads the BCube/Flint research group investigating blockchain security and dynamic network algorithms, with findings having direct implications for vehicle communication systems and post-disaster recovery networks.

Jonathan Scarlettمشاهده پروفایل

دانشیار

• Machine Learning
• Information Theory
• High-Dimensional Statistics
• +۳ مورد دیگر

Jonathan Scarlett is an Associate Professor jointly appointed in the Department of Computer Science, Department of Mathematics, and Institute of Data Science at the National University of Singapore (NUS). He also serves as Assistant Dean (Graduate Studies) in the School of Computing. His research focuses on information theory, machine learning, and high-dimensional statistics, with applications to optimization, group testing, and statistical inference. Education: Ph.D. (Information Engineering), University of Cambridge (2014) B.Eng. (Electrical Engineering) and B.Sci. (Computer Science), University of Melbourne (2010) Research Interests: Algorithmic foundations of machine learning and statistical estimation Information-theoretic limits and adaptive algorithms Applications in group testing, compressed sensing, and DNA storage Robust optimization under uncertainty and adversarial settings His work bridges theoretical guarantees with practical algorithm design, emphasizing scalable solutions for high-dimensional problems. Key Achievements: Recipient of Singapore NRF Fellowship (2018) and NUS Presidential Young Professorship Listed in MIT Technology Review's 'Innovators Under 35' Asia Pacific (2021) Over 100 publications in top venues like ICML, NeurIPS, and IEEE Transactions Advising & Grants: Supervised multiple PhD students in areas like Bayesian optimization, group testing, and compressed sensing Lead researcher on projects supported by NRF and NUS grants Developed novel frameworks for safe Bayesian optimization and robust bandit algorithms Labs & Collaborations: Active in the Information Theory and Statistical Learning Group at NUS, collaborating with global institutions like EPFL and MIT on data science challenges.

Jingxian Wangمشاهده پروفایل

استادیار

• Artificial Intelligence
• Wireless Systems
• Satellite Networks
• +۹ مورد دیگر

Jingxian Wang is an NUS Presidential Young Professor and Assistant Professor in the Department of Computer Science at the National University of Singapore's Faculty of Computing. His research builds next-generation wireless systems and satellite networks, with primary focus on integrating AI with wirelessly networked devices from WiFi to satellites. He earned his PhD from Carnegie Mellon University and previously served as a research scientist at Microsoft Research in Redmond, where he led the Smart Surface for 6G and Space initiative. His educational journey includes: PhD, Carnegie Mellon University Wang's research spans Wireless Systems , Satellite Networks , Artificial Intelligence , and Internet of Things , emphasizing AI-augmented wireless systems. His interdisciplinary work bridges robotics , materials science , and AI to develop sustainable sensing methods, robust communication networks, and multimodal AI techniques. Key projects include Multimodal AI for IoT (funded by Microsoft's Accelerate Foundation Models Program) and Satellite IoT Networks. His publication trends reveal accelerating integration of AI into wireless systems, with recent focus on satellite networking, soft robotics actuation, and generative models for IoT. The research consistently targets real-world deployment challenges in battery-free systems and space networks. His scientific contributions have earned prestigious recognition: ACM SIGMOBILE Doctoral Dissertation Award 2023 Communications of the ACM Research Highlights (2021, 2022) ACM SIGMOBILE Research Highlights 2021 Best Paper Awards at IPSN 2021 and UbiComp 2020 Microsoft Research Fellowship 2020 Emerging Rockstar in IEEE Pervasive Computing 2024 Wang actively mentors doctoral students and postdoctoral researchers through his AIoT Group. His grant portfolio includes Microsoft's Accelerate Foundation Models Research Program funding for multimodal AI projects, with ongoing work targeting satellite IoT infrastructure and wireless-powered soft robotics. Future directions emphasize foundation models for space networks and battery-free IoT systems. He leads the AIoT Group, fostering cross-disciplinary collaboration between computer scientists, roboticists, and materials engineers to pioneer wireless sensing and actuation technologies.

• Cybersecurity
• Privacy-Preserving Computation
• Cryptography
• +۲ مورد دیگر

Dr. YANG Guomin is an Associate Professor of Computer Science at Singapore Management University's School of Computing and Information Systems, where he coordinates the BSc Cybersecurity Track. His research focuses on privacy-preserving cryptography, authentication systems, and secure IoT frameworks. Research spans cryptographic protocols for cloud security, blockchain applications, and federated learning with emphases on efficiency and practical implementation. Recent publications demonstrate innovations in threshold authentication, redactable blockchains, and privacy-aware communication protocols. Advisees include LI Huilin and WANG Jiaheng, with research projects examining hardware-enhanced encryption, biometric authentication policies, and space network security. Work consistently addresses tension between security guarantees and computational efficiency in distributed systems.

Haiyang Xueمشاهده پروفایل

استادیار

• Cryptography
• Post-quantum cryptography
• Threshold cryptography
• +۵ مورد دیگر

Affiliations Full-time Assistant Professor of Computer Science at the School of Computing and Information Systems (SCIS) , Singapore Management University (SMU). Research focuses on cryptography, post-quantum systems, and secure protocols. Previously affiliated with PolyU for select teaching and collaborations. Education PhD in Computer Science, Chinese Academy of Sciences (2015). Research Interests Specializes in advanced cryptographic techniques including: Post-Quantum Cryptography (e.g., lattice-based systems) Threshold Cryptography (e.g., secure distributed ECDSA) Zero-Knowledge Proofs and Privacy-Preserving Technologies Authenticated Key Exchange (AKE) protocols Efficient implementations of cryptographic primitives (e.g., Kyber, NewHope) Notable Awards First Prize (LAC.PKE) and Second Prize (SIAKE, LAC.KEX) in Chinese Post-Quantum Cryptography Competition (2020) Best Paper Awards at IWSEC 2015 and ProvSec 2014 Advising & Collaborations Advises PhD students JIANG Bowen and WANG Jiaheng at SMU. Collaborates with researchers such as Guofeng Tang (post-doc) and international teams. Active in organizing conferences (e.g., CCS, ProvSec) and contributes to open-source projects like the Preprocess-then-NTT library. Labs & Teams Leads research initiatives at SMU focused on cryptographic protocol design and implementation. Collaborates with PolyU on advanced security projects.

Chen Binbinمشاهده پروفایل

دانشیار

• Wireless Networking
• Distributed Systems
• Cyber Security for Critical Infrastructures
• +۳ مورد دیگر

Chen Binbin is an Associate Professor and Associate Head of Pillar (Innovation and Enterprise) in the Information Systems Technology and Design (ISTD) pillar at Singapore University of Technology and Design (SUTD). He serves as Deputy Director for the Future Communications Research and Development Programme (FCP), Singapore. Previously, he was a Principal Research Scientist at the Advanced Digital Sciences Center (now Illinois ARCS), affiliated with the University of Illinois. Education: PhD in Computer Science from National University of Singapore, and Bachelor's from Peking University. Research focuses on wireless networking, distributed systems, and cyber security for critical infrastructures like smart grids and industrial control systems. His work addresses secure communications, intrusion detection, and resilience against cyber-physical threats. Notable contributions include error-estimating coding, provenance verification in ICS, and AI-driven network security solutions. Key awards include the 2010 ACM SIGCOMM Best Paper Award for error-estimating coding research. His grants span agencies like Singapore's National Research Foundation (NRF), Cyber Security Agency (CSA), and Energy Market Authority (EMA). He leads projects on secure smart grid communication, industrial control system defense, and AI-enhanced cybersecurity tools. Technical leadership involves developing frameworks like CyberSAGE for security assessment and CMD for IoT malware detection. Active in collaborations with industry and government, his work bridges theory and practice in securing critical infrastructure systems.

• Human-Computer Interaction (HCI)
• Computer Supported Cooperative Work (CSCW)
• Ubiquitous Computing
• +۳ مورد دیگر

Tony Tang is an Associate Professor in the School of Computing and Information Systems at Singapore Management University (SMU), where he leads the RICELab (Rethinking Interaction, Collaboration, and Engagement). Previously, he held roles at the University of Toronto and University of Calgary. His research focuses on Human-Computer Interaction (HCI), including Human-AI interaction, mixed reality interfaces, and ubiquitous computing. Education : PhD in Electrical and Computer Engineering, University of British Columbia (2010) MSc in Computer Science, University of Calgary (2005) BSc in Computer Science and Psychology, Simon Fraser University (2002) Research Interests : Tang’s work bridges theoretical and applied HCI, emphasizing systems that enhance human collaboration and interaction with technology. His lab explores topics like AI feedback mechanisms, mixed reality environments, and interfaces for distributed teams. Awards & Grants : ACM CHI Academy Member (2014) Funded by NAVER ($1.25M over 5 years), Meta ($30K), and SMU-SUTD Tier 1 Grant (S$100K) Advising & Grants : Supervised 26 graduate students and multiple postdoctoral fellows. His grants include work on immersive analytics and teleconferencing tools for physiotherapy. Labs & Teams : Directs the RICELab, which designs novel interaction systems for collaboration and learning. Active in the HCI community, serving as General Co-chair for CSCW 2022.

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

Professor TAN Ah Hwee is a Full-time Faculty member and Lee Kong Chian Professor of Computer Science at the School of Computing and Information Systems (SCIS) at Singapore Management University (SMU). He serves as the Associate Dean (Research) in SCIS and leads research in Artificial Intelligence, Machine Learning, and Health Informatics. His work spans neural networks, multi-agent systems, and healthcare applications such as Mild Cognitive Impairment prediction. He holds a PhD from Boston University (1994). Research Focus: His research integrates adaptive resonance theory, federated learning, and spatial-temporal modeling. Key areas include knowledge graph refinement, episodic memory systems for Activity of Daily Living (ADL) prediction, and explainable AI in multi-agent reinforcement learning. He also develops technologies for aging-in-place support and social media analytics. Recent Contributions: Recent work emphasizes hierarchical multi-agent models (HiSOMA), federated learning frameworks (FedART), and AI-driven health monitoring systems. His publications address challenges in self-organizing neural networks, context-aware reinforcement learning, and medical diagnostics through ambient sensing. Advising & Impact: Advises students like TEH Seng Khoon and Cassandra TAN Hui Ming. His projects include the eHealthPortal for elderly support and Silver Assistants for aging-in-place solutions. Research outputs bridge theoretical advancements in AI with real-world applications in healthcare and smart environments.

• Computer Science
• Economics
• Mathematics
• +۳ مورد دیگر

Assoc Prof Xiaohui Bei is an Associate Professor at Nanyang Technological University (NTU), holding dual appointments in the School of Physical & Mathematical Sciences (Division of Mathematical Sciences) and the College of Computing & Data Science. His research focuses on algorithmic game theory, fair division, auction design, and computational economics. He earned his Ph.D. from Tsinghua University in 2012 under Prof. Andrew Yao and held postdoctoral positions at NTU and the Max Planck Institute for Informatics. His work bridges theoretical computer science and economics, addressing challenges in fair resource allocation, truthful mechanisms, and market design. Key interests include cake-cutting protocols, auction optimization, and voting systems with mixed goods. He has contributed to foundational studies on Nash welfare, submodular valuations, and connectivity constraints in fair division. Prof. Bei’s research is supported by grants exploring topics such as optimal auction mechanisms and dynamic resource allocation. His publications often emphasize practical algorithmic solutions to complex economic challenges, ensuring both efficiency and fairness.

JIANG Lingxiaoمشاهده پروفایل

استاد

• Software Engineering
• Artificial Intelligence
• Data Science
• +۷ مورد دیگر

Professor Lingxiao Jiang is a full-time faculty member at the School of Computing and Information Systems (SCIS), Singapore Management University (SMU) , where he serves as Director of the Centre for Research on Intelligent Software Engineering (RISE) . His research and teaching focus on software engineering , program analysis , code search & reuse , and deep learning of code to enhance software quality, development productivity, and security. PhD, University of California, Davis (2009) Professor Jiang's research explores context-aware software deep learning , code clone detection , and security & privacy through tools like DECKARD (code clone detection), EqMiner (functionally equivalent code), and SmartEmbed (smart contract security). His work leverages distributed computing , symbolic execution , and neural program models for large-scale code analysis. Recent publications highlight trends in deep learning-based code analysis , smart contract vulnerabilities , and automated program transformation . Key themes include code clone detection , semantic patches , and cross-language API mappings . Scientific Awards ACM SIGSOFT Impact Paper Award (2018) for scalable code clone detection As advisor, Professor Jiang has mentored 14 graduate students, including Lucia (Ph.D. 2014) , Shaowei Wang (Ph.D. 2015) , and current advisees in intelligent software engineering. He leads multiple grants on code mining , security of digital platforms , and AI systems governance . RISE Lab at SMU develops tools like MANDO (smart contract analysis), iTiger (issue title generation), and TreeCaps (code processing with capsule networks). The lab actively recruits researchers in software engineering and AI.

• Business Analytics
• Operations Research
• Machine Learning
• +۵ مورد دیگر

Dr. Hong Ming Tan is a Senior Lecturer at the Department of Analytics and Operations, NUS Business School, and a Research Fellow at the Institute of Operations Research and Analytics (IORA) at National University of Singapore. He holds a PhD in Operations Research and Analytics (2021), MSc in Mathematics (2017), and BSc (Hons) in Applied Mathematics and Economics (2013) from NUS. Doctor of Philosophy, Operations Research and Analytics (2021) Master of Science, Mathematics (2017) Bachelor of Science (Hons), Applied Mathematics and Economics (2013) His research spans Business Analytics , Machine Learning , Operations Research , and Pharmacogenetics . Recent work includes: EcoVal Framework for efficient data valuation in ML Personalized Mental Health through adaptive testing and clustering Antibiotic Resistance modeling using antiresistic strategies CYP2D6 Methylation prediction for precision medicine His publications demonstrate expertise in ML optimization , healthcare informatics , behavioral analytics , and decision science . Current projects include AI-led Smart Data Centre Management and SIA Corp Lab research. He serves as Chair of the Department Finance Committee and advisor to student clubs like Business Analytics Consulting Team. His work addresses real-world challenges in industrial operations, healthcare diagnostics, and educational innovation.

Rakesh Nagiمشاهده پروفایل

استاد

• Data Science & Analytics
• Machine Learning & AI
• Operations Management
• +۷ مورد دیگر

Rakesh Nagi is a Professor and Head of the Engineering Systems and Design Pillar at Singapore University of Technology and Design (SUTD), where he joined in August 2023. He concurrently holds the Donald Biggar Willett Professorship at the University of Illinois, Urbana-Champaign (UIUC), on leave. His academic leadership includes serving as Department Head of Industrial and Enterprise Systems Engineering at UIUC (2013–2019) and as Interim Director of the Illinois Applied Research Institute (2016–2018). Previously, he was Chair of Industrial and Systems Engineering at the University at Buffalo (SUNY) from 2006 to 2012. Education: PhD (1991) and MS (1989) in Mechanical Engineering from the University of Maryland, College Park, with work at the Institute for Systems Research and INRIA, France. BE (1987) in Mechanical Engineering from the University of Roorkee (now IIT Roorkee), India. Research focuses on Data Science, Machine Learning, Operations Research, GPU-accelerated computing, and military applications. Key areas include Big Graphs, High-level Information Fusion, Production Systems, and Multi-Agent Systems. His work often leverages parallel computing and optimization techniques. Recipient of prestigious awards: IISE David F. Baker Award (2022), INFORMS Koopman Award (2021, 2018), and multiple DARPA Graph Challenge recognitions. Contributions span over 100 peer-reviewed articles in top journals (e.g., Operations Research, IEEE Transactions) and conferences. Research projects include Hybrid AI/ML-Optimization for cloud workflows, GPU-accelerated algorithms for multi-target tracking, and interventions against illicit supply chains. Active collaborations with IBM-Illinois and NSF-funded initiatives address strategic resource allocation and network analysis. Labs/Teams: Leads the Engineering Systems and Design Pillar at SUTD and coordinates interdisciplinary projects at UIUC’s Coordinated Science Laboratory.