جست‌وجوی استاد و پژوهشگر

Roland YAP Hock Chuanمشاهده پروفایل

دانشیار

• Artificial Intelligence
• Constraints
• Data Analytics
• +۴ مورد دیگر

Roland YAP Hock Chuan serves as an Associate Professor in the Department of Computer Science at the School of Computing, National University of Singapore (NUS), and previously held the role of assistant director at The Logistics Institute Asia Pacific (TLI-AP). His academic foundation was built at Monash University, Australia, where he earned comprehensive qualifications in Computer Science. Education: Ph.D. in Computer Science, Monash University, Australia M.Sc. in Computer Science, Monash University, Australia B.Sc. (Honours) in Computer Science, Monash University, Australia Research Focus: Renowned for pioneering the CLP(R) system that revolutionized Constraint Programming, Prof. Yap's work now spans artificial intelligence, security, programming languages, and social networks. His research bridges theoretical rigor with real-world applications, particularly in data analytics and knowledge compilation for industrial systems. Publication Evolution: His scholarly output reveals a strategic progression from foundational constraint logic programming (1990s) to cutting-edge security mechanisms and AI-driven solutions (2010s). Recent works demonstrate expertise in robust search algorithms, memory protection systems, and social network defense strategies, reflecting continuous adaptation to emerging computational challenges. Scientific Recognition: Best student paper award at SCA 2011 for social network research Best student runner-up paper at CIKM 2009 1995 Australian Computer Science Ph.D. Prize (1996) Praxa Computer Prize for theoretical computing achievements (1985) Academic Leadership: Prof. Yap directs the Tier 1 research project 'Investigating Product Configuration as Knowledge Compilation,' developing accelerated industrial solvers through innovative KC integration. His teaching portfolio includes advanced security courses (CS4239/5439/6231), shaping next-generation cybersecurity expertise. Mentoring excellence is evidenced by multiple student award-winning publications in top-tier conferences. Collaborative Infrastructure: Through his leadership role at TLI-AP, he contributes to NUS's interdisciplinary logistics research ecosystem, connecting computer science with supply chain innovation and operational optimization challenges.

YANG Yaxiمشاهده پروفایل

پژوهشگر ارشد

• Secure Computation
• Applied Cryptography
• Privacy Preserving Data Processing
• +۳ مورد دیگر

Dr. YANG Yaxi is a Research Fellow at iTrust, Singapore University of Technology and Design (SUTD), Singapore. She specializes in secure computation, applied cryptography, and privacy-preserving data processing. Her work emphasizes cryptographic techniques for real-world data challenges, including genomic data security, query optimization, and protecting against malicious actors. She holds a B.Sc. (2017) and Ph.D. (2023) in Information Security from Jinan University, Guangzhou, China. Her research interests focus on developing systems that ensure data privacy while maintaining computational efficiency, such as privacy-preserving queries, secure multi-party computation, and protocols for large-scale databases. Her recent articles explore advancements in technologies like oblivious PRFs, range-constrained intersection queries, and certificate-based encryption. These contributions highlight her commitment to enhancing security in outsourced environments and biomedical applications. Dr. Yang collaborates within the iTrust research group at SUTD, which specializes in trustworthy computing and information security. Her work addresses cutting-edge issues in privacy-preserving data processing and secure collaborative systems.

• 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.

DENG Yangمشاهده پروفایل

استادیار

• Natural Language Processing
• Information Retrieval
• Large Language Models
• +۷ مورد دیگر

Dr. Yang Deng is a tenure-track Assistant Professor at the School of Computing and Information Systems, Singapore Management University, and a Lee Kong Chian Fellow. Previously, he was a Postdoctoral Research Fellow at NExT++ (National University of Singapore). His research focuses on Natural Language Processing, Information Retrieval, and Large Language Models, with special interests in Proactive Conversational AI, Trustworthiness of LLMs, and Human-Centered Information Seeking. He has published over 40 papers in top-tier venues including ACL, EMNLP, WWW, and SIGIR. PhD from The Chinese University of Hong Kong (2023) Research Advisor to CHEANG Chi Seng Research Domains: Natural Language Processing Information Retrieval Large Language Models Human-Agent Interaction Digital Transformation Trustworthy AI Scientific Recognition: Lee Kong Chian Fellowship Google South Asia & Southeast Asia Research Awards 2024 EMNLP 2024 Outstanding Area Chair NeurIPS 2024 Best Reviewer

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.

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.

Conghui HUمشاهده پروفایل

مدرس

• Artificial Intelligence
• Machine Learning
• Computer Science
• +۴ مورد دیگر

Conghui HU is a Lecturer (Educator Track) at the School of Computing, National University of Singapore. Currently teaching courses such as CS1010A Programming Methodology and CS2109S Introduction to AI and Machine Learning. Research Interests Artificial Intelligence and Machine Learning Computer Vision with focus on sketch-based methods Cross-domain Image Retrieval Video Processing and Segmentation Point Cloud Analysis and 3D Vision Publications Trends Recent research outputs emphasize sketch-based video segmentation, cross-modal audio-visual analysis, and domain-generalized image retrieval. Key methodologies include deep learning, unsupervised feature representation, and differentiable particle filters, with applications in video object segmentation, point cloud segmentation, and audio-visual conditioned prediction.

Kyriakos Mouratidisمشاهده پروفایل

استاد

• Spatial Databases
• Continuous Query Processing
• Preference-based Queries
• +۲ مورد دیگر

Kyriakos Mouratidis is a Professor of Computer Science at Singapore Management University's School of Computing and Information Systems. His research focuses on spatial and spatiotemporal databases, particularly continuous query processing, preference-based queries, and optimization in road networks. He develops algorithms for nearest neighbor monitoring, spatial cloaking, and top-k query processing under capacity constraints. Recent work integrates skyline queries with top-k methods to handle preference-based queries with controllable output size. Dr. Mouratidis has received the Distinguished Associate Editor Award (SIGMOD 2024), Lee Kong Chian Research Fellowship, and serves as Associate Editor for GeoInformatica and SIGMOD Record. He directs the MAIS program and teaches data management courses.

PANG Hwee Hwaمشاهده پروفایل

استاد

• Artificial Intelligence and Data Science
• Data Management & Mining
• Information Systems & Technology
• +۴ مورد دیگر

PANG Hwee Hwa is a Professor and Dean of the School of Computing and Information Systems at Singapore Management University (SMU). He holds a PhD in Computer Science from the University of Wisconsin-Madison (1994). His research focuses on Artificial Intelligence, Data Science, Cybersecurity, and Privacy-Preserving Technologies , with contributions to secure computation, encrypted databases, and trustworthy digital systems. Professional roles include leadership in national initiatives such as the Singapore National Research Foundation’s Global Young Scientist Summit (2014–2015) and board memberships in SkillsFuture Singapore (2016–2018). He has extensive experience in academic administration and has advised numerous projects in data privacy and system security. His work spans 100+ peer-reviewed publications across databases, security, and information systems. Key contributions include query authentication frameworks, steganographic file systems, and privacy-preserving search techniques. Current research priorities include digital transformation and trustworthiness in emerging technologies.

Siyu Huangمشاهده پروفایل

استادیار

• Computer Vision
• Deep Learning
• Generative Models
• +۳ مورد دیگر

Siyu Huang is an Assistant Professor in the School of Computing at Clemson University, leading the Vision and Learning Lab (ViL). His research focuses on 2D/3D vision, generative models, and data-efficient learning with applications in biomedical and AI-driven systems. Huang holds a Ph.D. from Zhejiang University (2014–2019), a visiting scholar position at Carnegie Mellon University (2018–2019), and prior industry experience at Baidu Research and Harvard University's Visual Computing Group. He teaches advanced courses like Machine Learning-based Image Synthesis and Applied Computer Vision. Education: Ph.D., Information Science & Electronic Engineering, Zhejiang University (2014–2019) Visiting Scholar, Carnegie Mellon University (2018–2019) Bachelor's, Zhejiang University (2010–2014) Research Interests: Generative AI, 3D reconstruction, biomedical image analysis, and scalable unpaired translation. His work bridges vision and generative models for small-data scenarios. Publications: Over 30+ peer-reviewed papers in top venues like CVPR, ICCV, ICLR, and TPAMI, focusing on generative models, active learning, and medical imaging. Awards: Includes Baidu Research’s Outstanding Research Award (2020), ACM MM Travel Award (2018), and multiple scholarships from China’s Ministry of Education. Lab & Team: The ViL lab emphasizes interdisciplinary research, with current students focusing on 3D vision and generative models. Collaborations include Harvard, NTU, and industry partnerships.

Yunshi Lanمشاهده پروفایل

دانشیار

• Knowledge Bases
• Question Answering
• Information Extraction
• +۶ مورد دیگر

Yunshi Lan is an Associate Professor at the School of Data Science and Engineering, East China Normal University (ECNU). He holds a Ph.D. from Singapore Management University (SMU) and a Bachelor's degree from Southwest University (SWU). His research focuses on knowledge bases, question answering systems, deep learning, and large language models. He has led multiple grants, including projects from the National Science Foundation of China and the Shanghai Pujiang Talent Program. Lan has published extensively in top venues like ACL, EMNLP, and AAAI, with notable contributions to visual question answering, grammatical error correction, and educational NLP. He serves on program committees for ACL, EMNLP, and AAAI, and has given invited talks on large language models and knowledge-based systems. His teaching includes undergraduate and graduate courses on deep learning, emphasizing practical applications and LLM integration. Lan mentors a vibrant research group, with students contributing to impactful projects like MWPToolkit and FlaCGEC datasets. Education: Ph.D., SMU (201X); B.Sc., SWU (201X). Key grants include 'Knowledge Base Question Answering System in Interactive Environments' (NSFC, 2023-2025) and 'Intelligent Low Carbon Oriented Theories for Cross-Border Electric Power Trading' (NSFC, 2024-2028). Awards include the First Prize in the Financial GraphRAG Competition (2024) and the Shanghai Pujiang Talent Program (2022). His research highlights include benchmarking Visual Chinese GEC, developing TreeEval for LLM evaluation, and creating educational NLP tools like 中介语智能批改 for CFL learning.

Bryan HOOI Kuen-Yewمشاهده پروفایل

استادیار

• Machine Learning
• Graph Algorithms
• Anomaly Detection
• +۷ مورد دیگر

Bryan HOOI Kuen-Yew is an Assistant Professor in the Department of Computer Science at the National University of Singapore (NUS), affiliated with the School of Computing and the Institute of Data Science. His research focuses on enhancing the reliability and applicability of machine learning systems, particularly in trustworthiness, graph learning, and real-world applications such as cybersecurity and biomedical informatics. He holds a PhD in Machine Learning from Carnegie Mellon University (2019), and dual MSc (Computer Science) and BSc (Mathematics) degrees from Stanford University (2014). His work has been recognized with awards including the KDD 2016 Best Paper Award (Research Track) and the ECML-PKDD 2018 Runner-Up Best Student Data Mining Paper Award. Research Interests: Trustworthy AI: Mitigating hallucinations, biases, and distribution shifts in large language models. Graph Algorithms: Developing robust methods for graph mining, anomaly detection, and fraud detection in dynamic networks. Multimodal Learning: Leveraging vision-language models and knowledge graphs for improved reasoning and security. Biomedical Applications: Applying AI to healthcare challenges, including drug design and medical data analysis. Selected Awards: ECML-PKDD 2018 Runner-Up Best Student Data Mining Paper Award KDD 2016 Best Paper Award (Research Track) NUS Computing Teaching Excellence Award (2024) Advising and Grants: Actively supervises PhD and master’s students, with research supported by grants focusing on AI security, graph learning, and trustworthy systems. Collaborates on projects such as PhishAgent (multimodal phishing detection) and UniGraph (cross-domain graph foundation models).

Robert H Dengمشاهده پروفایل

استاد

• Applied cryptography
• Data security and privacy
• Mobile and wireless security
• +۵ مورد دیگر

Professor Robert H. Deng is a distinguished academic and researcher at Singapore Management University's School of Computing and Information Systems, where he serves as Professor of Computer Science and Deputy Dean for Faculty & Research. With a PhD from Illinois Institute of Technology (1985), he has established himself as a leading authority in cybersecurity, data privacy, and applied cryptography. His research interests span applied cryptography, data security and privacy, mobile and wireless network security, trusted computing, and system security. Professor Deng has published extensively in top-tier security venues, with over 600 publications listed in DBLP. His work bridges theoretical foundations with practical applications, particularly in the domains of IoT security, blockchain systems, and privacy-preserving technologies. Professor Deng has received numerous prestigious awards, including the National Day Award (Public Administration Medal Silver) in 2020, the AXA Chair Professor of Cybersecurity (2017-2025), and the Lee Kuan Yew Fellow for Research Excellence at SMU in 2006. His recent publications demonstrate continued leadership in emerging areas like post-quantum cryptography, federated learning security, and hardware-assisted security systems. His research group has produced significant work on secure authentication protocols, privacy-preserving data analytics, and robust cryptographic systems for real-world applications. National Day Award, Public Administration Medal (Silver), 2020 AXA Chair Professor of Cybersecurity, AXA Research Fund, 2017-2025 Distinguished & Best Paper Awards at NDSS, ESORICS, IEEE ICPADS, etc. Asia-Pacific Information Security Leadership Achievements (ISLA), 2010 Lee Kuan Yew Fellow for Research Excellence, SMU, 2006 University Outstanding Researcher, National University of Singapore, 1999 As a research advisor, Professor Deng has mentored numerous students including SUN Bing. His active participation in the research community is evidenced by recent keynotes at major conferences including DSPP 2024 on post-quantum cryptography and ASIACCS 2024 on client-side encryption. His research group maintains strong industry connections and receives significant funding for cutting-edge security research.

Cong Gaoمشاهده پروفایل

استاد

• Data Science
• Geospatial data management
• Spatio-temporal data mining
• +۷ مورد دیگر

Cong Gao is a Professor and Head of the Division of Data Science at Nanyang Technological University's College of Computing & Data Science. He also holds a courtesy appointment with the School of Physical & Mathematical Sciences. Previously, he served as an Assistant Professor at Aalborg University, Denmark, and worked as a researcher at Microsoft Research Asia. He co-directs the Singtel Cognitive and Artificial Intelligence Lab for Enterprises@NTU (SCALE@NTU). His educational background includes: Ph.D. in Computer Science from National University of Singapore (2004) Master of Engineering from Tianjin University, China (1999) Bachelor of Engineering from Tianjin University, China (1996) Professor Gao's research focuses on Data Science, with particular expertise in geospatial data management, spatio-temporal data mining, recommendation systems, and social media data analysis. His work has significantly impacted areas like spatial-textual indexing, point of interest recommendation, and mining social networks. He has published extensively in top venues including VLDB, SIGMOD, ICDE, KDD, and WSDM, with over 14,000 citations and an H-index of 61. His recent publications demonstrate strong trends in applying machine learning to database systems, with particular focus on spatial and trajectory data management. Key research directions include learned indexing techniques, trajectory data analysis, and integrating large language models with database systems for improved query optimization. Professor Gao has received notable scientific recognition including: Best paper runner-up award at WSDM'22 Best paper award runner-up at WSDM 2020 He has advised numerous students who have become significant contributors in their own right, including Xin Cao, Lisi Chen, Kaiyu Feng, and Kaiqi Zhao. His research has been supported by substantial grants from Ministry of Education, NRF, IAF, Singtel/NCS, Roll-Royce, Alibaba, and Microsoft, including a S$42.4 million funding over 5 years for the SCALE@NTU lab. Professor Gao leads the Data Management Research Group (DANTE) and co-directs the Singtel Cognitive and Artificial Intelligence Lab for Enterprises@NTU (SCALE@NTU), which develops market-leading AI and data science technologies.

• Auction Theory
• Mechanism Design
• Game Theory
• +۳ مورد دیگر

Dr. Yingkai Li is an Assistant Professor in the Department of Economics at the National University of Singapore (NUS). His research focuses on the intersection of economic theory and computer science, particularly in mechanism design, auction theory, and information economics. He has co-authored over 50 publications in top conferences and journals such as the ACM Conference on Economics and Computation (EC), IEEE Transactions on Information Theory, and the Journal of Economic Theory. Key research areas include algorithmic information disclosure in auctions, dynamic information acquisition incentives, robust persuasion mechanisms, and fair resource allocation with externalities. His work often combines theoretical analysis with computational methods, addressing challenges in optimal revenue design, strategic behavior modeling, and algorithmic fairness. Selected recent contributions include developing polynomial-time approximation schemes for optimal auction design with information structures (EC 2024), analyzing contracts for agents with misspecified beliefs (2024), and designing mechanisms robust to aftermarket effects (2023). His research has been supported by collaborations with leading institutions and frequent publications in interdisciplinary venues.