جستجوی استاد راهنمای دانشگاهی

LEE Wee Sunمشاهده پروفایل

استاد

• Machine Learning
• Planning Under Uncertainty
• Approximate Inference
• +۳ مورد دیگر

LEE Wee Sun is a Professor in the Department of Computer Science at the National University of Singapore (NUS), where he previously served as Head of Department, Vice Dean of Undergraduate Studies, and Vice Dean of Research. His academic journey began with a B.Eng. in Computer Systems Engineering from the University of Queensland (1992) and a Ph.D. from the Australian National University (1996), followed by research roles at the Australian Defence Force Academy and MIT. Education: Ph.D., Australian National University, Canberra, Australia (1996) B.Eng. in Computer Systems Engineering, University of Queensland, Brisbane, Australia (1992) Research Focus: Professor Lee pioneers work in Machine Learning , Planning Under Uncertainty , and Approximate Inference , with emphasis on integrating AI subfields for holistic reasoning. His current projects include "Learning to Decompose for Reasoning and Planning" (enhancing LLMs via self-supervised problem decomposition) and "Learning to Reason with Visual-Linguistic Inputs" (unifying vision, language, and reasoning in single architectures). Publication Trends: Recent work (2023-2025) centers on bridging LLMs with classical AI techniques, featuring breakthroughs in uncertainty quantification, multi-task optimization, and graph-based reasoning. Key themes include sparsity-aware vehicle routing, epistemic uncertainty for reliable LLMs, and differentiable neural solvers for combinatorial problems. Awards: IJCAI-JAIR Best Paper Prize (2022) RSS Test of Time Award (2021) RoboCup Best Paper Award (IROS 2015) HRATC 1st Place (2015) IPPC POMDP Track 1st Place (2011, 2014) UAI Google Best Student Paper (2014) Semeval-1 1st/2nd Place (2007) J.G. Crawford Prize (ANU 1996) Leadership & Service: As steering committee chair for ACML and area chair for NeurIPS/ICML/AAAI/IJCAI, Professor Lee shapes global AI discourse. His administrative roles at NUS and collaborations with MIT/Singapore-MIT Alliance demonstrate commitment to advancing AI education and research infrastructure. While student advisees aren't listed, his leadership positions imply extensive mentoring. Research Ecosystem: His work drives NUS's AI initiatives including Knowledge@Computing projects on reasoning frontiers. Current efforts focus on making AI systems robust through uncertainty-aware planning and multi-modal integration, with applications in robotics, verification systems, and combinatorial optimization.

Jing Jiangمشاهده پروفایل

استاد

• Natural Language Processing
• Machine Learning
• Data Mining
• +۴ مورد دیگر

Roles and Affiliations: Full Professor at the School of Computing and Information Systems (SCIS), Singapore Management University (SMU). Research Advisor to Xiaosen Zheng and Kankan Zhou. Serves as Action Editor for Transactions of the Association for Computational Linguistics (TACL) , Program Co-Chair of EMNLP 2019, and Editorial Board Member of Computational Linguistics (2015-2017). Education: PhD in Computer Science, University of Illinois at Urbana-Champaign (2008) B.S. and M.S. in Computer Science, Stanford University Research Focus: Specializes in natural language processing (NLP), text mining, machine learning, and data mining. Current interests include question answering, social media content analysis, and combating misinformation. Explores topics like counterfactual syntax for cross-lingual understanding, interventional training for robust NLU, and bias detection in vision-language models. Publications: Over 100+ peer-reviewed papers across top conferences (ACL, EMNLP, NAACL) and journals. Recent work emphasizes multimodal analysis, hate speech detection in memes, and robustness improvements for large language models. Key themes include cross-lingual systems, knowledge base question answering, and misinformation mitigation. Grants & Advising: Supervises PhD/Master’s students in cutting-edge NLP research. Leads projects on model memorization studies, hate meme classification, and interventional training frameworks. Active in organizing conferences and editorial roles. Teaching: Teaches courses in software foundations and programming fundamentals, bridging theory and practical NLP applications.

KHOO Siau Chengمشاهده پروفایل

دانشیار

• Programming Languages
• Code Analytics
• Software Engineering
• +۷ مورد دیگر

KHOO Siau Cheng is an Associate Professor in the Department of Computer Science at the National University of Singapore (NUS) School of Computing. He also serves as Co-Director of the NUS Business Analytics Centre, established in 2013 in collaboration with the Economic Development Board of Singapore and IBM. His academic journey began with a Ph.D. in Computer Science from Yale University in 1992. Professor Khoo's research focuses on improving software developer productivity through advanced programming language theories and software engineering techniques. His work spans multiple areas including static program analysis, dynamic program optimization, code analytics, and specification mining. He has applied his expertise to develop domain-specific languages for financial data analysis and has pioneered techniques for discovering dynamic program behaviors via data-mining approaches. Research Interests: Programming Languages and Software Engineering Code Analytics and Program Analysis Specification Mining and Bug Signature Discovery Static and Dynamic Program Analysis Program Transformation and Optimization Domain-Specific Languages Professor Khoo's publications demonstrate a consistent focus on improving software quality and developer productivity. His recent work emphasizes scalable approaches to refactoring detection, bug signature mining, and specification inference, showing an evolution from theoretical foundations to practical applications in software maintenance and quality assurance. As an educator and mentor, Professor Khoo has supervised numerous graduate students to completion of their M.Sc. and Ph.D. degrees. His research projects have provided valuable training opportunities for students while addressing important challenges in software development. He has also contributed significantly to academic administration, having served as Vice Dean (Undergraduate Studies) in the School of Computing from 2005 to 2011 and currently as Co-Director of the Master of Science (Business Analytics) Programme.

• Artificial Intelligence
• Strategic Reasoning in Multi-Agent Systems
• Formal Verification
• +۶ مورد دیگر

Aniello Murano is a Professor of Computer Science at the Department of Electrical Engineering and Information Technologies , University of Naples Federico II. He serves as Scientific Director of the ASTREA (Automated Strategic Reasoning) Laboratory and leads cutting-edge research in Artificial Intelligence, Strategic Reasoning, Multi-Agent Systems , and Formal Verification . Research Interests : Strategic reasoning under perfect/imperfect information, specification/verification/synthesis of reactive systems, temporal/modal logics, automata theory, parity games, game theory, mechanism design, and formal languages. Notable Projects : PNRR Research Unit Coordinator (2023-2025) on Resilient AI, PRIN 2020 Unit Coordinator (RIPER: Resilient AI-Based Self-Programming and Strategic Reasoning), H2020-MSCA SEAL (Principal Coordinator). Awards & Honors : JPMorgan Faculty Research Award (2022), Royal Society Award (2016), Best Paper PRIMA (2015), INDAM Project Leader (2023), Italian Scientific Habilitation (2017-2018). Students & Postdocs : Supervised 6 PhD students (e.g., Silvia Stranieri, Vadim Malvone) and mentored postdocs such as Munyque Mittelmann and Bastien Maubert. Laboratory : Leads ASTREA Lab, focusing on automated strategic reasoning and resilient AI systems.

Yang Kaidiمشاهده پروفایل

استادیار

• Intelligent Transportation Systems
• Traffic Flow Theory and Control
• Multimodal Transportation Systems
• +۷ مورد دیگر

Yang Kaidi is an Assistant Professor in the Department of Civil and Environmental Engineering at the National University of Singapore (NUS), affiliated with the Institute of Operations Research and Analytics (IORA) within NUS’s Smart Nation Research Cluster. Their research focuses on intelligent transportation systems, traffic control, shared mobility, and machine learning applications in mobility. Key interests include connected and automated vehicles, privacy-preserving data sharing, and reinforcement learning for traffic optimization. Research highlights include developing parameter privacy-preserving strategies for mixed-autonomy platoons, enhancing safety in autonomous driving via transformer-based trajectory prediction, and optimizing traffic signal timing using connected vehicle data. Their work bridges theoretical control systems with practical urban mobility challenges, addressing issues like ridesourcing-public transit integration, modular transit service operations, and weaving section management in mixed traffic environments. Recent publications emphasize real-time control frameworks, cooperative safety mechanisms, and data-driven solutions for urban and highway systems. Yang’s interdisciplinary approach integrates robotics, optimization, and cybersecurity to advance smart transportation infrastructure. Their contributions are particularly notable in privacy-preserving techniques for traffic state estimation and federated learning applications. While no specific awards or grants are listed, their research aligns with Singapore’s Smart Nation initiatives through IORA’s strategic focus areas. Yang’s work has implications for future traffic management systems, autonomous vehicle coordination, and sustainable urban mobility solutions.

• Corporate Governance
• Earnings Management
• Voluntary Disclosure
• +۶ مورد دیگر

YUE Heng is a Full-time Professor of Accounting at Singapore Management University (SMU), holding dual roles as Director of the SMU-ZJU Doctor of Business Administration (Accounting & Finance) Program and Programme Director of the SMU Tsinghua Joint Master of Science in CFO Leadership. He joined SMU in 2015 after teaching at Peking University, where he earned his Bachelor's degree in Management from the Guanghua School of Management. He holds a PhD in Accounting from Tulane University's Freeman School of Business. His research focuses on corporate governance, earnings management, voluntary disclosure in emerging markets, and capital market dynamics. Notable contributions include studies on tunneling through intercorporate loans, political corruption impacts on reporting quality, and cultural influences on corporate risk-taking. His work has been published in top journals like the Journal of Financial Economics and The Accounting Review . Honors include the Liyining Research Award (2013) and the ICBC Economic Scholar Award (2011). He advises doctoral students in accounting and has contributed to curriculum development in executive education programs. His current research explores green transition challenges, audit quality in anti-corruption contexts, and information asymmetry in emerging markets. Key Research Themes: Corporate Governance Failures, Financial Transparency, Political Economy of Accounting, Emerging Market Financial Systems Teaching Areas: Advanced Financial Accounting, CFO Leadership, Financial Statement Analysis

LEE Mong Liمشاهده پروفایل

استاد

• Data Management
• Data Cleaning
• Data Fusion
• +۵ مورد دیگر

LEE Mong Li is a Professor of Computer Science at the National University of Singapore (NUS) and serves as Director of the NUS Centre for Trusted Internet and Community. She holds a Ph.D., M.Sc., and B.Sc. (First Class Honours) in Computer Science from NUS, where she was awarded the IEEE Singapore Information Technology Gold Medal as the top Computer Science student in 1989. Her academic career includes a visiting fellowship at the University of Wisconsin-Madison (1999) and consultancy with QUIQ USA (2000). Her research spans Data Management, Spatio-temporal Databases, Biomedical Informatics, and Retinal Image Analysis . She has pioneered work in data cleaning, data fusion, and analysis of semistructured data, with applications in social media analytics and healthcare. Her recent publications demonstrate strong interdisciplinary focus, particularly in AI-driven medical diagnostics including diabetic retinopathy screening and chronic kidney disease detection from retinal images. She co-authored foundational books on 'Designing Semi-structured Database' and 'Temporal and Spatio-Temporal Data Mining'. Her 150+ publications in major database conferences and journals reflect leadership in both theoretical and applied research. Recent work shows significant emphasis on Medical AI applications (retinal analysis, kidney disease prediction) Temporal fact verification systems Misinformation detection in multimodal environments Privacy challenges in large language models Key honors include: Singapore's President Technology Award (2014) for co-inventing an AI system screening eye conditions IEEE Singapore Information Technology Gold Medal (1989) She actively contributes to government-funded multidisciplinary projects building practical deployable systems. Her leadership extends to program committees of prestigious database conferences and directing the NUS Centre for Trusted Internet and Community. She teaches BT5110 Data Management and Warehousing and has co-developed an AI system for diabetic retinopathy screening deployed in Singapore's national teleophthalmology program.

Michael Qizhe Shiehمشاهده پروفایل

استادیار

• Large Language Models
• Deep Learning
• Natural Language Processing
• +۴ مورد دیگر

Michael Qizhe Shieh is an Assistant Professor in the Department of Computer Science at the National University of Singapore (NUS), affiliated with the Tree and Rock AI Lab (TRAIL). He holds a PhD and Master's from Carnegie Mellon University (Machine Learning and Language Technologies) and a Bachelor's from Shanghai Jiao Tong University's ACM Class. His research focuses on Large Language Models, Deep Learning, and Natural Language Processing, with notable contributions to semi-supervised learning techniques like Noisy Student and UDA, and the RACE benchmark for reading comprehension. Education: PhD in Machine Learning, Carnegie Mellon University (2020) Master's in Language Technologies, Carnegie Mellon University (2018) Bachelor's in Computer Science, Shanghai Jiao Tong University (2016) His research explores robustness, safety, and scalability of AI systems. He has served as Area Chair for top conferences like NeurIPS, ICML, and ICLR. Current research directions include adversarial robustness, LLM self-evaluation, and alignment mechanisms. His lab, TRAIL, emphasizes foundational AI research. Selected contributions include: Developing UDA and Noisy Student techniques for semi-supervised learning Creating the RACE benchmark for exam-based reading comprehension Advancing methods for LLM safety and adversarial defense Prospective students are encouraged to apply to NUS's PhD program for collaborative research opportunities.

Quan Quan Tanمشاهده پروفایل

پژوهشگر ارشد

• Cryptography
• Symmetric-key Cryptanalysis
• Automated Cryptanalysis
• +۲ مورد دیگر

Quan Quan Tan is a Research Fellow at Nanyang Technological University (NTU), Singapore, specializing in symmetric-key cryptanalysis and automation tools. He previously served as a Cybersecurity Engineer at CSIT, Singapore for nearly two years. His educational background includes: Ph.D. in Mathematical Sciences from NTU (2023) under Prof. Thomas Peyrin. Thesis: "Cryptanalysis of Lightweight Symmetric-Key Cryptographic Algorithms" M.Sc. in Mathematical Sciences from NTU, with research on optimization techniques for block cipher hardware implementations B.Sc. in Mathematical Sciences from NTU Dr. Tan's research focuses on automation in cryptographic design and analysis, emphasizing secure symmetric-key primitives and advanced cryptanalysis tools. His work bridges theoretical cryptography with practical security engineering through algorithm development and vulnerability assessment. Analysis of his 2020-2025 publications reveals dominant themes in symmetric-key cryptanalysis, including innovative meet-in-the-middle attacks, differential cryptanalysis frameworks, and automated verification systems. His contributions span attack methodologies (e.g., higher-order differential-linear techniques), tool development (Trail-Estimator), and novel cipher design (uKNIT-BC), demonstrating consistent advancement in lightweight and low-latency cryptographic systems.

Benjamin William Cashoreمشاهده پروفایل

استاد

• Environmental Governance
• Climate Policy
• Comparative Public Policy
• +۷ مورد دیگر

Benjamin William Cashore is the Li Ka Shing Professor in Public Management and Director of the Institute for Environment and Sustainability (IES) at the National University of Singapore's Lee Kuan Yew School of Public Policy. Previously, he spent 18 years at Yale University as a professor of environmental governance and political science, where he directed the Governance, Environment and Markets (GEM) initiative and the Yale International Fox Fellows exchange program from 2014-2019. PhD from University of Toronto Postdoctoral research at Harvard University and University of British Columbia Former policy advisor to the leader of the Canadian New Democratic Party Expertise spans Southeast Asia, North America, Latin America and Europe Cashore specializes in global and multi-level environmental governance, comparative public policy and administration, and transnational business regulation/corporate social responsibility. His research focuses on climate policy, biodiversity conservation/land use change, and sustainable environmental management of forests and related agricultural sectors. Theoretically, he examines the legitimacy requirements of non-state market driven (NSMD) global governance, the influence of economic globalization on domestic environmental policies, and anticipatory policy design for addressing 'super wicked' environmental problems. His work integrates around developing multi-stakeholder policy learning processes and nurturing multiple step policy pathways. His recent scholarship demonstrates consistent engagement with climate change governance, forest policy, and the intersections between private regulation and public policy. Cashore's publications reveal a strong focus on identifying effective governance mechanisms for addressing complex environmental challenges through both state and non-state approaches. Author of two influential books: 'Global Environmental Forest Policies: An International Comparison' (2010) and 'Governing Through Markets: Forest Certification and the Emergence of Non-State Authority' (2004) Extensive publication record in top journals across political science, environmental policy, and governance fields Cashore has developed significant expertise in designing stakeholder learning dialogues and identifying policy pathways for addressing complex environmental governance challenges. His work bridges theoretical insights with practical policy applications across multiple continents and governance contexts.

Vivy Suhendraمشاهده پروفایل

دانشیار

• Software Assurance
• Security and Privacy
• Cybersecurity
• +۱ مورد دیگر

Vivy Suhendra serves as Associate Professor of Practice and Programme Director for Master Programmes at the National University of Singapore's School of Computing, while also holding the position of Assistant Dean for Graduate Studies. Previously, she led the Singapore Cybersecurity Consortium (SGCSC) as Executive Director from 2016 to 2022, driving collaborative cybersecurity research between academia, industry, and government agencies. Her career at NUS spans over two decades, beginning as a Research Assistant before advancing to her current leadership roles. Her academic credentials include: Ph.D. in Computer Science, National University of Singapore (2009). Thesis: "Memory Optimizations for Time-predictable Embedded Software". Advisors: Abhik Roychoudhury and Tulika Mitra. B.Comp. (Honors) in Computer Science, National University of Singapore (2004). Dr. Suhendra's research integrates Software Assurance, Cybersecurity, Security and Privacy, and Embedded Systems domains. Her work bridges theoretical foundations with practical applications, particularly in national cybersecurity ecosystem development, smart grid security protocols, denial-of-service mitigation techniques, and real-time embedded system optimization. This interdisciplinary approach enables innovative solutions for critical infrastructure protection and time-predictable software execution in multi-core environments. Her 14 selected publications (2004-2020) demonstrate an evolving research trajectory from foundational embedded systems timing analysis to applied cybersecurity solutions. Early work focused on memory optimization for predictable execution in multi-core embedded systems, which naturally transitioned into cybersecurity applications for smart grids, cloud environments, and national infrastructure. This progression highlights her ability to translate low-level system expertise into high-impact security frameworks for complex real-world systems. Scientific recognition includes: Microsoft Research Asia Fellowship (2006) Valedictorian at NUS School of Computing Ph.D. Commencement (2010) While specific graduate student advising details aren't provided, her leadership as SGCSC Executive Director involved extensive mentorship across academic-industry partnerships. She has also contributed significantly to the research community through roles including Conference Chair for ESEC/FSE 2022 and Workshops Committee Member for ICSE 2024. Dr. Suhendra established the Singapore Cybersecurity Consortium as a national platform for collaborative R&D during her directorship (2016-2022). Though no personal laboratory is specified, her research leadership manifests through cross-institutional teams focused on cybersecurity innovation, particularly in critical infrastructure protection and embedded systems security where she maintains active publication records.

Abhik Roychoudhuryمشاهده پروفایل

استاد

• Software Testing
• Program Analysis
• Program Repair
• +۴ مورد دیگر

Abhik Roychoudhury is a Provost's Chair Professor of Computer Science at the National University of Singapore (NUS), leading the Trustworthy and Secure Software (TSS) research group since 2001. His work focuses on automated program repair, software testing, security, and agentic AI. He is a Senior Advisor at SonarSource following the acquisition of his startup AutoCodeRover. He holds an ACM Fellowship and has received the ICSE Most Influential Paper Award for program repair research. Education: M.S. and Ph.D. in Computer Science from State University of New York at Stony Brook (1997-2000). Research interests include program analysis, software security, and AI-driven software engineering. His team has pioneered techniques like SemFix and Angelix for program repair, and AFLNet for protocol fuzzing. He has served as editor-in-chief of ACM TOSEM and conference chair for ICSE and FSE. Awards include the NUS Outstanding Graduate Mentor Award (inaugural recipient) and IEEE New Directions Award. His work bridges academia and industry, with contributions to projects like the DesCartes initiative for critical urban systems. Key collaborations include Microsoft on API repair and IBM on AI research centers. His recent focus includes agentic AI for software engineering, reflected in AutoCodeRover's acquisition by SonarSource.

Akshay Narayanمشاهده پروفایل

مدرس ارشد

• Artificial Intelligence
• AI Planning
• Reinforcement Learning
• +۶ مورد دیگر

Akshay Narayan is a Senior Lecturer (Educator Track) at the School of Computing, National University of Singapore (NUS), where he teaches senior undergraduate and graduate-level courses in AI Planning and Decision Making, as well as introductory and intermediate-level Software Engineering courses. Education: Ph.D. in Computer Science from National University of Singapore (completed in 2020) M.Tech. in Information Technology from International Institute of Information Technology Bangalore, India B.E. in Computer Science & Engineering from Visveswaraya Technological University, India Research Interests: Dr. Narayan's research spans multiple domains within computer science with a primary focus on artificial intelligence and its applications. His current research centers on transfer learning in reinforcement learning, multi-agent decision making, and AI planning. He has also made significant contributions to cloud computing research, particularly in areas such as smart metering, chargeback systems, power-aware cloud metering, and workload analysis for virtual machine sizing. His work bridges theoretical foundations with practical applications, addressing real-world challenges in computing systems. He has recently expanded his research to include technology in education, exploring how AI can be integrated into teaching and learning processes. Publication Trends: Dr. Narayan's publication record demonstrates a clear evolution from foundational work in cloud computing to more recent explorations in reinforcement learning and AI education. His early work focused on practical applications in cloud systems, including smart metering and QoS monitoring. More recently, his research has shifted toward AI planning, decision making, and the educational applications of AI. This progression shows his ability to adapt to emerging fields while maintaining a strong foundation in systems research. Awards and Recognition: Teaching and Mentoring: Dr. Narayan teaches a variety of courses at NUS including CS2113 Software Engineering & Object-Oriented Programming, CS3219 Software Engineering Principles and Patterns, CS3268 Responsible AI: From Algorithms to Impact, and IT5100F Industry Readiness: Data Analytics and AI in Practice. He has also taught CS4246/CS5446 AI Planning and Decision Making. His teaching approach integrates his research expertise with practical applications, providing students with both theoretical foundations and hands-on experience. He has taught these courses across multiple academic years from AY-2013/14 through AY-2020/21. Research Groups and Collaborations: Dr. Narayan has collaborated with researchers across multiple institutions, including work with Prof. Tze Yun Leong at NUS (his PhD advisor), Shrisha Rao, Zhuoru Li, and others. His research has often involved interdisciplinary collaborations that bridge theoretical computer science with practical system implementations.

• Software Engineering
• Software Security
• Foundations of Program Analysis
• +۹ مورد دیگر

Marcel Böhme is a faculty member at the Max Planck Institute for Security and Privacy (MPI-SP) , leading the Software Security research group. His work focuses on foundational advancements in fuzzing , statistical program analysis, and scalable vulnerability discovery. Education: PhD from National University of Singapore (NUS) Research interests span: Statistical and causal frameworks for software testing Efficiency/Scalability of automated testing Fundamental limits of vulnerability detection Practical fuzzing technology (e.g., Entropic in LibFuzzer) Recent publications highlight trends in: Machine learning for security analysis Privacy-preserving statistical methods Future-proof security frameworks Protocol fuzzing with large language models Scientific accolades include: ERC Consolidator Grant (2024) NUS Outstanding Young Alumni Award (2022) ARC DECRA (2019) Multiple ACM Distinguished Paper Awards He serves as: Spokesperson for Research Group Leaders at Max Planck Society Guest Editor-in-Chief for ACM TOSEM PC Chair for ASE'25 and ISSTA'26

• 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.