جست‌وجوی استاد و پژوهشگر

Peichen Zhongمشاهده پروفایل

استادیار

• Materials Science
• Machine Learning
• Computational Modeling
• +۵ مورد دیگر

Dr. Peichen Zhong is an Assistant Professor in the Department of Materials Science and Engineering at the National University of Singapore (NUS). He leads the Applied Machine Learning and Materials Modeling (AM³) Group, focused on advancing computational methods for clean energy technologies. His research integrates machine learning with atomistic simulations to tackle challenges in battery materials, disordered materials, and sustainable energy systems. Education: B.S. in Physics from University of Science and Technology of China (2018); Ph.D. in Materials Science from UC Berkeley (2023, advised by Prof. Gerbrand Ceder); Postdoctoral training at Lawrence Berkeley National Lab and BIDMaP, co-advised by Persson, Cheng, and Krishnapriyan. Research Interests: Computational modeling of battery cathodes/electrolytes, AI-driven interatomic potentials, statistical mechanics in disordered materials, and generative models for scientific discovery. Key areas include Li/Na-ion batteries, solid-state reactions, and sustainable energy materials. Awards: BIDMaP Emerging Scholar Fellowship (UC Berkeley CDSS, 202?), 2023 Rising Stars in Materials Science (CMU/MIT/Stanford). Labs/Teams: The AM³ Group at NUS MSE focuses on interdisciplinary research combining theory, computation, and AI4Science. Current openings include PhD students and postdoctoral researchers.

Reza Shokriمشاهده پروفایل

دانشیار

• Data Privacy
• Trustworthy Machine Learning
• Security
• +۷ مورد دیگر

Reza Shokri is a Dean's Chair Associate Professor in the Department of Computer Science at the National University of Singapore (NUS), School of Computing. His research lies at the intersection of data privacy, security, and trustworthy machine learning, with a focus on quantifying privacy risks and developing robust, fair, and interpretable models. PhD in Computer Science, EPFL His research interests center on data privacy and trustworthy machine learning , particularly in the context of deep learning and federated systems. He investigates how machine learning models memorize training data, leading to privacy leakage, and designs frameworks to audit and mitigate such risks. His work bridges theoretical guarantees with practical applications, emphasizing the trade-offs among privacy, fairness, robustness, and utility. His recent publications (2023–2025) reveal a strong trend in analyzing privacy in large language models (LLMs), membership inference attacks, federated learning, and fairness. These works are published in top venues such as NeurIPS, ICML, ICLR, CCS, and FAccT, highlighting his leadership in both AI and security communities. Notable scientific awards include: Asian Young Scientist Fellowship (2023) Intel Outstanding Researcher Award (2023) Best Paper Award, ACM FAccT (2023) IEEE S&P Test-of-Time Award (2021) Caspar Bowden Award for Privacy Enhancing Technologies (2018) NUS Presidential Young Professorship (2019–2023) VMware Early Career Faculty Award (2021) He has advised numerous PhD and Master’s students, many of whom have contributed to high-impact publications. He has also received research grants from major industry partners including Meta, Google, Intel, and VMware. He leads the Data Privacy and Trustworthy Machine Learning Lab at NUS and has served on program committees for top conferences such as IEEE S&P, ACM CCS, and FAccT, including co-chairing roles at HotPETs and Shadow PC of IEEE S&P. He has delivered tutorials at ICML and CCS on privacy auditing in machine learning. His lab focuses on developing tools and frameworks—such as the ML Privacy Meter—for assessing and improving the privacy properties of machine learning models, with applications in regulatory compliance and secure AI deployment.

• Additive Manufacturing
• Aerospace Engineering
• Thermofluids
• +۱ مورد دیگر

Associate Professor Ng Bing Feng leads research in Additive Manufacturing, Aerospace Engineering, and Thermofluids at Nanyang Technological University's School of Mechanical & Aerospace Engineering. As Cluster Director for Smart & Sustainable Building Technologies at NTU's Energy Research Institute, he oversees projects spanning energy-efficient cooling technologies, advanced filtration systems, and bio-inspired materials. His interdisciplinary work integrates advanced manufacturing with environmental engineering, focusing on sustainable solutions for air quality management and thermal regulation. Current research explores radiative cooling technologies, acoustic agglomeration for emissions control, and crashworthy structures via biomimetic design. Professor Ng's publications demonstrate consistent innovation in multi-scale manufacturing and fluid dynamics, with growing emphasis on sustainable urban technologies. Methodologies combine experimental fluid dynamics with computational modeling and AI-driven design. Leadership Roles: Cluster Director, Energy Research Institute @ NTU Principal Investigator for multiple industry collaborations in sustainable materials Research Output: 42+ publications in high-impact journals Multiple patents in filtration technologies and cooling systems

Ian Yi Hanمشاهده پروفایل

استادیار

• Programme Evaluation
• Population Health
• Health Services Research
• +۴ مورد دیگر

Dr. Ian Yi Han is an Assistant Professor at the Saw Swee Hock School of Public Health, National University of Singapore (NUS), and Co-Director of the Center for Health Intervention and Policy Evaluation Research (HIPER). His research focuses on evaluating community-based health interventions, telehealth programs, and the impact of built environments on health behaviors. He holds a Ph.D. in Behavioral Nutrition from Columbia University, an M.A. in Psychology in Education, and a B.Sc. in Neural Science & Psychology from New York University. Key research areas include programme evaluation, population health, health services research, and dietary behaviors. He explores how interventions can improve patient experiences and population health outcomes, particularly through telemedicine and lifestyle modifications. His work has been published in journals like npj Digital Medicine, Metabolism, and the Journal of Nutrition Education and Behavior. Notable projects include studies on blood pressure telemonitoring, diabetes management during the pandemic, and supermarket intervention strategies for obesity prevention. Dr. Han has contributed to policy initiatives through roles such as Senior Research Fellow at the National University Health System and Lecturer at Columbia University. He advises on primary care research and collaborates on global health projects, emphasizing interdisciplinary solutions to public health challenges.

Foong Shaohuiمشاهده پروفایل

دانشیار

• Robotics
• Electronics
• Unmanned Aerial Vehicles (UAVs)
• +۹ مورد دیگر

Dr. Foong Shaohui is an Associate Professor and Associate Head at the Engineering Product Development (EPD) pillar of the Singapore University of Technology and Design (SUTD), with prior experience as a Visiting Assistant Professor at MIT's Mechanical Engineering department (2011). He leads the Aerial Innovation Research (AIR) Laboratory @ SUTD and actively collaborates with Singapore's Ministry of Defence (MINDEF) and medical institutions like National University Hospital (NUH) and Changi General Hospital (CGH). PhD, MS, and BS in Mechanical Engineering from Georgia Institute of Technology (2005-2010) Research Interests span multiple domains: Robotics & UAVs : Nature-inspired aerial craft design (Project MONOCO), hybrid flight dynamics, and transformable rotorcraft Medical Device Innovation : Magnetic localization systems for nasogastric tubes and ventriculostomy procedures Engineering Education : Design-Centric pedagogy and pre-university Aerial Craft Workshops Autonomous Systems : Deep tunnel sewer inspection drones (NRF/PUB funded) and soft robotics Scientific Contributions include patented magnetic localization technologies (licensed to Medergo Pte. Ltd.), over 20 peer-reviewed publications, and 5 granted patents. His work bridges aerospace engineering with biomedical applications through innovative mechatronic solutions. Best Application Paper Award at SCIS & ISIS (2014) Research Grants include projects funded by Singapore's National Research Foundation (NRF), Public Utilities Board (PUB), and National University Hospital partnerships. He mentors PhD/Master's students through interdisciplinary research in aerial robotics and medical device development.

• Numerical Modeling
• Computational Simulation
• Materials Science
• +۵ مورد دیگر

Assoc Prof Ng Teng Yong is an Associate Professor at the School of Mechanical & Aerospace Engineering (NTU), specializing in numerical modeling and simulation. With a background as Research Manager at A*STAR Institute of High Performance Computing, his work spans materials science, nanotechnology, and aerospace engineering. Current focus on graphene-based desalination membranes Expertise in molecular dynamics simulations Investigates nanoscale fluid mechanics and structural dynamics Recent publications highlight advancements in energy-efficient electrodialysis, smart robotics, and nonlinear vibration analysis. His interdisciplinary approach integrates computational methods with experimental validation in additive manufacturing and soft material mechanics.

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.

LU Wen Fengمشاهده پروفایل

دانشیار مدعو

• Additive Manufacturing
• Robotics
• Smart Manufacturing
• +۴ مورد دیگر

LU Wen Feng is an Adjunct Associate Professor in the Department of Mechanical Engineering at the National University of Singapore (NUS), affiliated with the College of Design and Engineering. His research focuses on advanced manufacturing technologies, including additive manufacturing, robotics, and AI-driven systems. He explores sustainable design methodologies, smart manufacturing innovations, and bioprinting applications. Key areas include optimizing material processes, enhancing mechanical properties of printed materials, and developing autonomous robotic solutions for industrial tasks. Contact: mpelwf@nus.edu.sg , located at E3-02-07. Research Interests : His work bridges AI and manufacturing, emphasizing Knowledge graph integration for additive manufacturing, Autonomous robotic systems in industrial settings, Bioprinting for tissue repair with smart bioinks, Topology optimization for lightweight and sustainable structures, Material characterization and process engineering for 3D-printed composites. Recent Article Trends : LU Wen Feng's 2025 articles highlight advancements in AI-augmented manufacturing systems (e.g., MaViLa, AutoMEX) and sustainable design workflows. His 2024 studies address material anisotropy, corrosion behavior, and topology optimization strategies for lattice structures. These trends reflect his interdisciplinary approach to solving challenges in additive manufacturing, robotics, and biomedical applications. Awards : No scientific awards explicitly mentioned. Advising & Grants : No current graduate students or grants listed. His research likely integrates industry-academia collaborations given the focus on applied manufacturing technologies. Labs/Teams : Not explicitly detailed, but his work suggests involvement in advanced manufacturing labs and AI-robotics teams at NUS.

Xiang Limingمشاهده پروفایل

دانشیار

• Survival Analysis
• Longitudinal/Clustered Data Analysis
• Mixture Modelling
• +۳ مورد دیگر

Assoc Prof Xiang Liming is an Associate Professor in the Division of Mathematical Sciences at Nanyang Technological University (NTU), Singapore, serving as Assistant Chair (Students). She holds editorial roles at *Computational Statistics & Data Analysis* and *Statistics in Medicine*. With a PhD in Statistics (City University of Hong Kong, 2002), her research focuses on survival analysis, longitudinal data analysis, and biostatistical methods. Notable contributions include methodologies for semi-competing risks, interval-censored data, and mixture models. Her work bridges statistical theory with biomedical applications, addressing challenges in clinical trials and public health. Awards include the 2009 IIE Transactions Best Paper Award and the Outstanding Research Thesis Award (2002–2003, CityU). Education: PhD in Statistics, City University of Hong Kong (2002) Postdoctoral Research: Hong Kong University of Science and Technology (2002–2003) and CityU (2003–2006) Research Interests: Survival analysis methodologies, including frailty models, cure models, and quantile regression for censored data. She develops robust statistical approaches for clustered/longitudinal data, addressing missingness and overdispersion. Applications span biomedical research, epidemiology, and quality management. Grants & Collaborations: Her grants include work on robotic-assisted stroke rehabilitation (2021) and LNG cold energy utilization systems (2017–2019). She collaborates with clinical teams on trials involving upper limb neurorehabilitation technologies. Labs & Teams: Leads statistical method development for multi-center clinical trials, particularly in biostatistics and survival analysis frameworks. Active in NTU’s School of Physical & Mathematical Sciences research initiatives.

• Composition
• Computer Music
• Algorithmic Composition
• +۳ مورد دیگر

Peter Ivan Edwards is an Associate Professor and Head of Composition at the Yong Siew Toh Conservatory of Music, National University of Singapore. He specializes in creating compositions that explore sound through energy, narrative, and perspective, often employing computer-assisted and algorithmic methods. His collaborative works emphasize experimental traditions with live performance improvisation and electronic signal processing. Education: Northwestern University University of California, San Diego Folkwang Hochschule (Essen, Germany) His research focuses on experimental music, interactive performance systems, and sound design. His works have been performed globally at festivals like Darmstadt Summer Courses, MATA Festival, and Wien Modern, featuring renowned ensembles such as Ensemble Interface and mmm… collective. Edwards also organizes international collaborations, including the Dian Red Kechil International Young Composers Residency and visits by ensembles like the TIMF Ensemble and Elision Ensemble. As a researcher, he has presented at IRCAM Forum Workshops, Orpheus Institut, and universities across Europe and Asia. His findings appear in journals like Perspectives of New Music and Experiments in Pedagogy . Edwards teaches composition, experimental music, and computer music, fostering student engagement through residencies and guest artist programs.

• Algebra
• Number Theory
• Coding Theory
• +۳ مورد دیگر

Assoc Prof Frederique Elise Oggier is an Associate Professor in the School of Physical and Mathematical Sciences, Division of Mathematical Sciences at Nanyang Technological University (NTU). She holds a PhD from the Swiss Federal Institute of Technology (EPFL) and has held visiting positions at Caltech and the Research Center for Information Security (Tokyo). Her research focuses on algebraic coding theory, lattice-based cryptography, and applications of number theory to secure and reliable communication systems. Education: Bachelor’s and Master’s in Mathematics from the University of Geneva PhD in Mathematics from EPFL Research Interests: Her work bridges abstract algebra with practical coding challenges, emphasizing lattice codes for wiretap channels, distributed storage systems, and security protocols. Specialized in algebraic structures like cyclic division algebras and modular lattices, her contributions advance both theoretical foundations and real-world implementations of secure communication systems. Publications: Her recent work addresses cutting-edge topics such as MDS codes, non-GRS code constructions, and lattice-based security in noisy channels. These contributions highlight her expertise in coding theory and its interdisciplinary applications. Grants/Advising: While specific grants are not detailed, her prolific publication record reflects sustained research activity. She advises on projects related to distributed storage and secure coding, though student names are not listed in the provided texts. Labs/Teams: Affiliated with NTU’s mathematical sciences division, she collaborates with global researchers on projects such as lattice coding for 5G/6G systems and cryptographic protocols leveraging algebraic number theory.

Leow Wee Khengمشاهده پروفایل

دانشیار

• Medical Image Analysis
• Computer Vision
• 3D Modeling
• +۵ مورد دیگر

Associate Professor Leow Wee Kheng is affiliated with the Department of Computer Science at the School of Computing, National University of Singapore . His career spans over three decades with expertise in medical image analysis , computer vision , and surgical simulation . Ph.D. in Computer Science, University of Texas at Austin (1994) M.Sc. in Computer Science, National University of Singapore (1989) B.Sc. in Computer Science, National University of Singapore (1985) His research focuses on medical image analysis for craniofacial surgery and stroke diagnosis, 3D modeling of anatomical structures, and computer vision techniques like robust PCA and texture analysis . Recent work includes knee joint motion modeling and forearm rotation simulation for clinical applications. Key trends in his 2017-2025 publications involve skull reconstruction algorithms , multi-objective optimization for digital media, subject-specific biomechanical modeling , and low-rank decomposition techniques in visual computing. Collaborations include institutions like Singapore General Hospital and National Taiwan University Hospital . Scientific Awards : CAIP 2017 Best Paper Award 2007 Andrew P. Sage Best Transactions Paper Award Faculty Teaching Excellence Award (AY2015/16) Annual Teaching Excellence Award (AY2015/16) He has mentored numerous students in medical imaging , computer vision , and biomedical modeling . Current and former advisees include Chen Ying , Vineta Lum Lai Fun , and Long Huizhong (Ph.D.).

• Transportation and Logistics
• Supply Chain Management
• Operations Research
• +۷ مورد دیگر

Prof. Keng Hock, Mark Goh is a Professor at the National University of Singapore (NUS) Business School, holding a joint appointment as Director (Industry Research) at The Logistics Institute-Asia Pacific (TLI-AP). He specializes in logistics, supply chain strategy, and operations research. He earned his PhD from the University of Adelaide on a fully funded scholarship and has held adjunct and visiting roles globally. His research focuses on supply chain risk management, healthcare logistics, and strategic decision-making, with over 400 publications in top journals. Notable contributions include work on multi-criteria supplier selection, supply chain resilience, and AI ethics in e-commerce. He has received the Supply Chain Educator Award and is recognized in global directories like *Who’s Who in Asia and the Pacific Nations*. Prof. Goh advises public and private sector organizations on logistics strategy and sits on industry committees such as the World Economic Forum’s Global Advisory Council on Logistics. His current projects emphasize syncretic value-driven logistics models and sustainable recycling frameworks. He leads collaborative research teams addressing global supply chain challenges through interdisciplinary approaches. His articles reflect cutting-edge advancements in AI-driven decision models, risk networks in construction, and data ownership strategies in digital platforms. These contributions underscore his role as a thought leader in logistics and operations research, blending academic rigor with real-world industry applications.

Jun Le Gohمشاهده پروفایل

استادیار

• Mathematical Logic
• Set Theory
• Lattices and Universal Algebra
• +۴ مورد دیگر

Dr. Jun Le Goh is an Assistant Professor in the Department of Mathematics at the National University of Singapore (NUS). His research focuses on mathematical logic, set theory, computational complexity, computability theory, and combinatorics. He holds a Bachelor of Science (Honors, Class 1) from NUS (2013) and a Ph.D. in Mathematics from Cornell University (2019). His work bridges foundational areas of mathematics with computability theory, particularly in reverse mathematics and Weihrauch reducibility. Notable contributions include analyzing the complexity of Halin's infinite ray theorems, studying descending sequences in ill-founded linear orders, and exploring enumeration oracles in PA relativization. His research often intersects with proof theory, recursion theory, and algorithmic information theory. Dr. Goh collaborates with institutions globally, publishing in journals like the Journal of Mathematical Logic, Annals of Pure and Applied Logic, and Computability. His preprints and conference proceedings further highlight his engagement with cutting-edge topics in computability and logic.

Li Huaمشاهده پروفایل

استاد

• Multiphysics Modeling
• Soft Matter
• Machine Learning
• +۵ مورد دیگر

Professor Li Hua is a faculty member at the School of Mechanical & Aerospace Engineering, Nanyang Technological University (NTU), Singapore. He holds a Ph.D. in Mechanical Engineering from the National University of Singapore (1999) and has been recognized as a Fellow of the American Society of Mechanical Engineers (ASME) since 2019. His academic journey includes postdoctoral research at the University of Illinois at Urbana-Champaign (2000-2001), a visiting scientist role at Johns Hopkins University (2005), and research scientist positions at A*STAR’s Institute of High Performance Computing (2001-2006). Research Interests: Professor Li specializes in multiphysics modeling of soft matters (e.g., smart hydrogels in BioMEMS and biological cell microscale dynamics), machine learning-based prediction for 3D printing process-microstructure-property correlation, numerical computational methodologies (meshless and multiscale algorithms), sustainable energy simulations (building efficiency and fuel cells), and structural dynamics of high-speed rotating shells and composites. His work bridges computational mechanics, materials science, and biomedical applications. Publications & Collaborations: With over 200 peer-reviewed journal articles, he has authored/co-authored monographs such as Smart Hydrogel Modelling (Springer) and Rotating Shell Dynamics (Elsevier). His research is funded by agencies like NRF, EDB, SMI, and industry partners including Rolls-Royce, Emerson, and ABB. Scientific Awards: Fellow of ASME (2019) ICCM Investigator Award (2018) SMI Top Project Winner (2015) IBM & IHPC Silver Award (2003) Advising & Grants: He has advised Ph.D. students like Meng Zhang (awarded Best Student Paper at ICMFM XIX, 2018) and secured grants for computational BioMEMS, sustainable buildings, and advanced manufacturing projects. His industrial collaborations span aerospace, maritime, and energy sectors. Labs & Teams: Professor Li leads a research group at NTU, focusing on interdisciplinary projects with institutions like Imperial College, Technische Universität Dresden, and Johns Hopkins University. He contributes to academic governance as an NTU Senator and active member of professional societies.