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Lin WeisiView profile

Professor

• Artificial and Augmented Intelligence
• Computer Science and Engineering
• Electrical and Electronic Engineering
• +5 more

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

Tianyang HuView profile

Assistant Professor

• Statistical Machine Learning
• Representation Learning
• Deep Generative Modeling
• +7 more

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

LIU BoxiangView profile

Assistant Professor

• Genomics
• Bioinformatics
• Machine Learning
• +3 more

Asst Prof LIU Boxiang holds the position of Assistant Professor and NUS Presidential Young Professorship at the Department of Pharmacy and Pharmaceutical Sciences, National University of Singapore (NUS), within the Faculty of Science. His research focuses on integrating multi-omics approaches with computational methods to study complex diseases such as coronary artery disease and age-related macular degeneration. He specializes in developing statistical and machine learning tools for genomic analysis, including eQTL mapping and deep learning architectures for gene expression regulation. Education: BA in Biophysics (Illinois Wesleyan University), MS and PhD in Bioinformatics (Stanford University). He contributed to the GTEx consortium and is part of the Asian Immune Diversity Atlas (AIDA) initiative. His lab develops methods like ANTseq for ancestry determination and scPrediXcan for cell-type-specific transcriptome studies. Research Interests: Functional genomics, eQTL analysis, deep learning in biomedicine, and computational tools for omics data integration. His work bridges disciplines such as natural language processing and computer vision with biological questions. Scientific Awards: NUS Presidential Young Professorship (2021). His lab's innovations include ParaMed, a biomedical translation dataset, and LinearDesign for optimized mRNA stability. Advising and Grants: Leads the Liu Lab (boxiangliulab.com), focusing on single-cell genomics, mitochondrial dynamics, and computational biomedicine. Collaborates on projects like the RESET cohort study for cardiovascular disease prevention.

Nguyen Thanh SonView profile

Researcher

• Natural Language Processing
• Multimodal Deep Learning
• Knowledge Base Systems
• +3 more

Nguyen Thanh Son is a Research Scientist at the Artificial Intelligence Initiative under the Institute of High Performance Computing (IHPC), Agency for Science, Technology and Research (A*STAR), Singapore. He holds a PhD in Information Systems from the School of Information Systems, Singapore Management University (SMU), where he was advised by Associate Professor Hady Lauw. His research focuses on natural language processing, opinionated text mining, and multimodal deep learning. Previously, he completed a visiting PhD program at Carnegie Mellon University (CMU) and an internship at IBM Research Lab in Dublin, Ireland. He also earned a Bachelor of Information Systems from the University of Engineering and Technology (UET), Vietnam National University, Hanoi, with academic distinctions in research. Research Interests: His work spans natural language processing, emotion recognition, knowledge base systems, and agentic AI. He has contributed to advancements in large language models, multimodal encoding, and retrieval-augmented systems. Grants & Awards: He secured a Singapore Aerospace Programme grant (SGD 360,000) as PI and co-led an A*STAR grant (SGD 6 million). His accolades include the SMU Presidential Doctoral Fellowship and top research prizes during his undergraduate studies. Labs & Teams: Active in IHPC's AI initiatives and collaborated with CMU and IBM on projects like sentiment analysis and ontology building. His work bridges academic research and industrial applications in AI.

• Artificial Intelligence
• Data Science
• Machine Learning
• +9 more

Qianru Sun is an Associate Professor at the School of Computing and Information Systems, Singapore Management University (SMU), and a Lee Kong Chian Fellow. Her research focuses on artificial intelligence, machine learning, computer vision, and semantic segmentation, with a particular emphasis on few-shot learning, meta-learning, and domain adaptation in remote-sensing imagery. Recent publications highlight her work on visual chain-of-thought reasoning , 3D scene understanding via 2D models , and parameter-efficient fine-tuning of large models. Her research also extends to weakly-supervised semantic segmentation and cross-modal video retrieval . Scientific Awards : Lee Kong Chian Fellow (2021–2023, 2025–2027) Outstanding Service Award by MMAsia (2020) Outstanding Reviewer at NeurIPS'21 and ICLR'21 Students : PhD students: Luo Zilin, Tian Zichen, Ying Jiahao Master’s students: Bao Chunhui, LOH Yi Lin, MA Li

Saima HilalView profile

Assistant Professor

• Neurodegenerative diseases
• Neurovascular diseases
• Cardiovascular diseases
• +4 more

Saima Hilal is an Assistant Professor at the NUS Saw Swee Hock School of Public Health, Department of Pharmacology, with affiliations at the National University Health System's Memory Aging and Cognition Center and Erasmus University Medical Center, Rotterdam. Her research focuses on neurodegenerative and vascular diseases, leveraging neuroimaging, epidemiology, and biomarkers to address underdiagnosed conditions like dementia in Asian populations. Education: PhD in Medicine (2016, NUS), MPH (2013, NUS), MD (2006, Dow Medical College, Pakistan). Research interests include Alzheimer’s disease, cerebrovascular pathologies, and cardiovascular risk factors. Notable grants include a Bright Focus Foundation grant on cerebral microinfarcts and a Start-up grant on cardiovascular disease prevention. She has pioneered methods like WMH-DualTasker for neuroimaging analysis and developed predictive models for cognitive decline using retinal and plasma biomarkers. Awards : World Heart Federation Emerging Leaders Programme, Travel grants from Alzheimer’s Association and Vascular Behavioral Disorders Society. Teaching : Advanced Epidemiology, Public Health Aging, Non-Communicable Diseases. Her work bridges clinical and population-based studies, emphasizing multi-ethnic cohorts and machine learning applications. She leads initiatives like the DEBBIE-AD study on blood-brain barrier biomarkers and the SEACURE consensus for mild cognitive impairment management in Southeast Asia.

Lin QikaView profile

Research Fellow

• Natural Language Processing
• Artificial Intelligence in Healthcare
• Multi-modal Representation Learning
• +3 more

Lin Qika is a Research Fellow at the Saw Swee Hock School of Public Health, National University of Singapore (NUS). His research focuses on advancing natural language processing (NLP) and AI applications in healthcare, particularly leveraging large language models (LLMs) for robust healthcare solutions. He holds a PhD from Xi’an Jiaotong University (2023), an M.S. from Beijing Institute of Technology (2019), and a B.S. from the same institution (2016). His expertise spans multi-modal representation learning, neuro-symbolic systems, and logical reasoning applied to healthcare challenges. Notable research includes developing frameworks like TECHS for explainable extrapolation reasoning and integrating knowledge graphs with LLMs. His work emphasizes practical healthcare applications, such as depression detection and medical diagnostics. Lin Qika’s recent publications (2022–2025) explore cutting-edge topics like contrastive graph representations, knowledge graph completion, and adversarial attacks on knowledge embeddings. He actively contributes to conferences like ACL, SIGIR, and KDD, showcasing innovations in AI-driven healthcare and multimodal reasoning. No scientific awards or funded grants are explicitly mentioned in the provided information.

DENG YangView profile

Assistant Professor

• Natural Language Processing
• Information Retrieval
• Large Language Models
• +7 more

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

• Artificial Intelligence
• Data Science
• Data Mining
• +7 more

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 ChongView profile

Assistant Professor

• Combinatorics
• Commutative Algebra
• Artificial Intelligence
• +5 more

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.

Kok Lim LowView profile

Senior Lecturer

• Computer Graphics
• Computational Art
• Real-Time Rendering
• +2 more

Dr. Kok Lim Low serves as a Senior Lecturer in the Department of Computer Science at the School of Computing, National University of Singapore (NUS), where he has established himself as a leading researcher in computer graphics and computational art. With over two decades of academic service, he bridges technical innovation with creative applications while maintaining exceptional teaching standards. His educational foundation includes: Ph.D. in Computer Science from the University of North Carolina at Chapel Hill (2006) M.Sc. in Computer Science from the National University of Singapore (1997) B.Sc. (Honours) in Computer Science from the National University of Singapore (1996) Dr. Low's research centers on computational approaches to visual media, with three interconnected pillars: Computational Art explores algorithmic generation of artistic papercraft and pop-up books; Real-Time Rendering develops GPU-accelerated global illumination techniques; and Computational Photography enhances image aesthetics through depth adaptation and recomposition. His work consistently merges mathematical rigor with artistic sensibility, producing methods that automate creative processes while preserving aesthetic integrity. Analysis of his recent publications reveals an evolving trajectory from core graphics research toward computer science education innovation. While maintaining strong output in computational art (evident in his 2014-2015 pop-up design papers), his 2021-2023 work demonstrates significant contributions to CS1 pedagogy through educational tool development and curriculum design, reflecting his dual commitment to research and teaching excellence. His scientific recognition includes: Three Faculty Teaching Excellence Awards from NUS School of Computing (2014, 2016, 2017) Best Paper Award at Computer Graphics International Conference (2015) Honorable Mention at ACM CHI Conference (2011) As an educator, Dr. Low has advised Ph.D. and Master's students while serving on numerous thesis committees. He teaches foundational courses like Programming Methodology to freshmen alongside advanced topics including Graphics Rendering Techniques, demonstrating equal commitment to novice and advanced learners. His student mentorship extends to undergraduate research projects across the computing curriculum. Dr. Low operates within NUS Computing's collaborative research ecosystem, where his interdisciplinary work connects computer science with art and design disciplines. His laboratory contributions focus on developing practical computational tools that transform creative workflows while advancing theoretical understanding of visual media processing.

• Geographic Information Science
• Spatial Cognition
• Computational Methods
• +3 more

Chen-Chieh Feng is an Associate Professor in the Department of Geography at the National University of Singapore and part of the GIS Unit and Tropical Environmental Change Research Group. He holds a Ph.D. from the State University of New York at Buffalo and MSc/BSc degrees from National Taiwan University. His research explores spatial cognition, geographic information systems, and computational methods for analyzing human-environment interactions. Current projects include modeling urban mobility during pandemics, aging in social networks, and human-centered GIS designs for digital twins. Dr. Feng teaches courses in cartography, GIS applications, and spatial programming, focusing on experiential learning and foundational spatial literacy.

• Human Geography
• Development Studies
• Environmental Geography
• +9 more

Dr. W. Nathan Green is an Assistant Professor in the Department of Geography at the National University of Singapore (NUS). His research focuses on how development finance transforms environments and livelihoods in Southeast Asia, particularly in Cambodia and the Mekong Basin. He employs ethnographic methods to study political ecology, agrarian change, and the intersections of finance, debt, and social justice. His work critiques microfinance industries, impact investment, and the financialization of development, emphasizing their role in dispossession and environmental harm. Education: PhD (Geography), University of Wisconsin-Madison MA (Southeast Asian Studies), University of Wisconsin-Madison BA (Geography & Comparative History of Ideas), University of Washington Research Interests: Political ecology of agrarian finance and microfinance Debt-driven environmental change (e.g., deforestation) Impact of Chinese development finance and infrastructure Social reproduction and translocal precarity Critical agrarian studies and food regimes Teaching & Awards: Recipient of NUS Promising Research Award (2023) 2022 Faculty Teaching Excellence Award and 2023 Annual Teaching Excellence Award Focus on participatory learning, fieldwork, and global socio-environmental challenges Grants & Projects: Funded by Fulbright, Mellon Foundation, NASA, and Singapore Ministry of Education Current project: Impact investment for sustainable development in Southeast Asia Labs/Teams: Collaborates with interdisciplinary teams on projects involving Southeast Asian development finance and political ecology.

Ranjith VijayakumarView profile

Lecturer

• Psychology
• Quantitative Methods
• Evolutionary Psychology
• +5 more

Ranjith Vijayakumar is a Lecturer at the Department of Psychology, National University of Singapore. He holds a Ph.D. and M.Soc.Sci. from NUS, and his academic roles include advising students, coordinating student exchange programs, and non-graduating student support. Education: Ph.D. (NUS), M.Soc.Sci. (NUS) His research focuses on two primary areas: Applications of quantitative and machine learning methods to psychology research Integrating evolutionary and comparative psychology approaches with traditional cognitive, cultural, and social psychology frameworks His recent work explores the replicability of machine learning models in social sciences, methodological advancements in meta-analysis, and the impact of tactile feedback on social neuroscience phenomena. While no scientific awards are explicitly listed, his publications highlight interdisciplinary contributions spanning psychology, neuropsychology, and computational methods.

LOH Wai LamView profile

Associate Professor

• Subsea processing
• Multiphase flow
• Oil and gas production
• +5 more

Associate Professor LOH Wai Lam is affiliated with the Department of Mechanical Engineering at the National University of Singapore (NUS), part of the College of Design and Engineering. He coordinates the Offshore Oil & Gas Technology Specialisation and manages the Subsea Systems and Transportation Programme at the Centre of Offshore Research & Engineering (CORE). His qualifications include a PhD, MSc, and BEng from the University of Manchester, UK, with professional certifications as a Chartered Engineer (CEng) and memberships in the Royal Aeronautical Society (MRAeS) and the Society of Petroleum Engineers (SPE). His research focuses on subsea processing, multiphase flow systems, and oil/gas production optimization. Notable contributions include patented innovations in multiphase pumps, flow metering, and separation technologies. He has received prestigious awards such as the Royal Society Esso Energy Award (1998) and Hart’s Petroleum International Special Meritorious Award (1999) for engineering innovation. Before joining NUS in 2006, he spent 16 years in the UK working in R&D roles for Oil & Gas companies, leading multidisciplinary projects on production, processing, and transportation. His work emphasizes practical engineering solutions for industry challenges, blending academic research with industrial applications.