جستجوی استاد راهنمای دانشگاهی

See Kiong Ng serves as Professor of Practice in the Department of Computer Science at the School of Computing, National University of Singapore (NUS), while concurrently holding leadership roles as Director of AI Technology at AI Singapore and Deputy Director of NUS's Institute of Data Science (IDS). His work focuses on translational data science research and developing integrated capabilities for Singapore's Smart Nation initiative through industry and public agency collaborations. His academic credentials include a B.S. in Applied Mathematics (Computer Science Track) from Carnegie Mellon University (1989), an M.S.E. in Computer & Information Science (Artificial Intelligence) from the University of Pennsylvania (1990), and a Ph.D. in Computer Science from Carnegie Mellon University (1998), supported by Singapore's National Computer Board overseas scholarship. Professor Ng's research bridges artificial intelligence with real-world applications across diverse domains. His primary interests span Data Mining, Machine Learning, Natural Language Processing, Smart Cities, and Computational Biology, with emphasis on extracting value from big data through interdisciplinary approaches. He actively pioneers applications in urban systems and bioinformatics, demonstrating data science's transformative potential beyond traditional boundaries. His publication record reveals consistent innovation in algorithm development for complex data challenges, with recent work focusing on taxonomy construction, single-cell genomics analysis, urban transportation systems, and imbalanced time series classification. These contributions demonstrate his commitment to solving practical problems through cutting-edge data science techniques. His major recognitions include: MTI Borderless Award (2014) as Green Growth Working Group project member Minister for National Development's R&D Award 2017 (Distinguished Award) for city-level analytics platform innovation A*STAR Borderless Award (2014) as Urban Systems Initiative team leader MTI Innovation Award (2013) for Strategic Technology Translation in Business Analytics Professor Ng has established significant research infrastructure including founding A*STAR's Data Analytics Department and leading the Urban Systems Initiative. His translational research model emphasizes industry partnerships and practical implementation, particularly in smart city development where he connects data science with urban planning challenges across Singapore's government agencies.

• Data Mining
• Artificial Intelligence
• Machine Learning
• +۴ مورد دیگر

Dr. Bimlesh Wadhwa is an Associate Professor in the Department of Computer Science at the National University of Singapore (NUS) and serves as Assistant Dean for Student Life at Tembusu College. She holds dual affiliations as a Residential Fellow at Tembusu College and an active member of the School of Computing's academic community. Her work bridges software engineering, human-computer interaction (HCI), and computing education. Dr. Wadhwa's research focuses on gender issues in HCI, software design quality, and digital well-being. She has pioneered initiatives like the Code for Community program to bring computing education to underserved groups. Her pedagogical contributions include developing courses on object-oriented design, software engineering principles, and interaction design. She actively engages with professional communities through roles such as Faculty Representative at the Singapore Computer Society Student Chapter and advisor to the Computing Club at NUS. Her recent work addresses pressing societal challenges like technology-facilitated sexual violence and integrates AI into educational contexts. She has organized major competitions including CodeXtreme and the Singapore Science and Engineering Fair, fostering innovation among students. Her interdisciplinary collaborations span healthcare applications, smart city technologies, and educational equity initiatives. Dr. Wadhwa’s scholarly contributions include over 80 publications in top venues such as FSE, CHI, and IEEE conferences. She has co-edited book chapters for Springer and Wiley on HCI and informatics, reflecting her commitment to advancing both technical and societal dimensions of computing. In addition to her academic roles, she leads MakerLab initiatives and contributes to national educational policies on computational thinking. Her work emphasizes bridging academia-industry gaps through projects like the GEAR mobile game-assisted rehabilitation system and cloud service brokerage frameworks.

• Software Engineering
• Human-Computer Interaction (HCI)
• Computing Education
• +۴ مورد دیگر

Bert DE REYCK is the Dean of the Lee Kong Chian School of Business at Singapore Management University (SMU) and holds the rank of Professor of Operations Management. He holds a PhD in Business Economics from the University of Leuven, Belgium, along with an MSc in Business Information Systems and a BSc in Business Engineering from the same institution. His career includes roles as Founding Director and Professor at UCL School of Management (2015–2021), Professor and Head of Department at University College London (2009–2015), and various visiting professorships at institutions like London Business School and the University of Ghent. He has held academic positions since 1998, including Assistant and Associate Professor roles at prestigious institutions such as the London Business School and Rotterdam School of Management. DE REYCK’s research focuses on Operations Management, Business Analytics, and Project Management, with notable contributions to AI applications, transportation systems, and strategic sourcing. His work bridges theoretical rigor and practical impact, addressing challenges in project valuation, contract design, and operations optimization. He has received numerous accolades, including INFORMS’ AAS Best Paper Award (2022), multiple Daniel H. Wagner Prize recognitions, and teaching awards from London Business School and UCL. His research has been supported by grants from organizations like Eurocontrol, NHS, and private sector firms such as Vungle and Noble Group. DE REYCK has led significant industry collaborations, including projects on airport operations optimization, pharmaceutical R&D valuation, and AI-driven advertising strategies. His advisory work spans sectors like aviation, healthcare, and transportation, emphasizing real-world problem-solving through analytics and decision science.

• Operations Management
• Business Analytics
• Project Management
• +۳ مورد دیگر

Dr. Sheena Ramazanu is an Assistant Professor in Nursing and Health Sciences at Hong Kong Metropolitan University, with additional affiliations as an Honorary Visiting Research Fellow at NUS Saw Swee Hock School of Public Health. Her work focuses on optimizing health capacities for underserved communities through culturally competent research and partnerships. Education: PhD (Hong Kong Polytechnic University), Master in Clinical Research (University of Manchester), Graduate Certificate in Teaching & Learning for Healthcare (NUS), First-Class Honours Bachelor of Nursing (University of Manchester), Diploma in Nursing (Nanyang Polytechnic) Her research emphasizes ethnic minority health equity , family-centered mental health interventions , and global health partnerships . Recent publications highlight prediabetes prevention in indigenous populations, stroke communication patterns, and international nursing research challenges. Dr. Ramazanu serves as Academic Editor for BMC Health Services Research and Public Health Challenges Journals. Key awards include the Ministry of Health Gold Medal, Hong Kong PhD Fellowship, and YSEALI Professional Fellows Program recognition.

• Public Health
• Nursing
• Health Promotion
• +۴ مورد دیگر

Yang You is a Presidential Young Professor at the National University of Singapore (NUS), affiliated with the Department of Computer Science under NUS Computing. He holds a PhD in Computer Science from UC Berkeley, advised by Prof. James Demmel. His research focuses on parallel/distributed algorithms, high-performance computing, and machine learning, particularly in scaling deep neural networks on distributed systems and supercomputers. Notably, his team achieved world records in ImageNet and BERT training speeds, with techniques adopted by tech giants like Google and NVIDIA. His optimizers (LARS/LAMB) are included in MLPerf benchmarks. Education - PhD in Computer Science, UC Berkeley - Outstanding Graduate of Tsinghua University (1st rank). Research Interests Yang You’s work spans machine learning system optimization, parallel computing, and distributed training infrastructure. He explores efficient algorithms for large-scale models, including techniques for reducing training time and improving scalability. His contributions emphasize practical implementations that bridge theory and industry applications, such as accelerating diffusion models and optimizing LLM inference. Awards & Honors Lotfi A. Zadeh Prize (2020) IPDPS 2015 Best Paper Award (0.8% acceptance) ICPP 2018 Best Paper Award (0.3% acceptance) ACM/IEEE George Michael HPC Fellowship Siebel Scholar (2020) Forbes 30 Under 30 Asia (2021) Advising & Labs He advises PhD students in cutting-edge research and leads the NUS AI Lab , focusing on advancing AI systems and high-performance computing. His lab collaborates with industry partners to deploy scalable machine learning solutions.

• Machine Learning
• High-Performance Computing
• Parallel/Distributed Systems
• +۳ 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.

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

Tural Khudiyev is an Assistant Professor at the Department of Materials Science and Nanotechnology , National University of Singapore (NUS), focusing on multimaterial electronic fibers for human-fabric interaction, soft robotics, and neural probes. He previously worked as a postdoctoral researcher at MIT's Research Laboratory of Electronics. B.Sc. in Nuclear Engineering, Hacettepe University Ph.D. in Materials Science and Nanotechnology, Bilkent University His research spans implantable and wearable electronics , stimuli-responsive drug delivery , and AI in healthcare , with a strong emphasis on scalable nanomanufacturing techniques. His publications in journals like Nature , Nature Nanotechnology , and Advanced Materials highlight innovations in thermally drawn fibers and soft bioelectronic interfaces . Key trends include flexible electronics , machine learning in textiles , and bio-integrated devices , with applications in neural engineering and power textiles . His work has been featured in media outlets such as Reuters and Business Insider . Selected as MIT’s top research story of 2021 #1 Most Read Article in Applied Optics (2015) Featured in Virtual Journal of Nanoscale Science & Technology Khudiyev's contributions to thermally drawn fibers and soft robotics demonstrate interdisciplinary collaboration between materials science, neuroscience, and wearable technology.

• Flexible Electronics
• Soft Robotics
• Bioelectronics
• +۳ مورد دیگر

Ye Zhisheng is the Dean’s Chair and Associate Professor in the Department of Industrial Systems Engineering & Management at the National University of Singapore (NUS). His research focuses on reliability engineering, inventory control, emergency response systems, and statistical modeling. He holds a PhD in Industrial and Systems Engineering from NUS, along with a BEng in Material Science and Engineering and a BEco in Economics from Tsinghua University. His work emphasizes practical applications in mission-critical systems, predictive maintenance, and data-driven decision-making. Current research initiatives include optimal maintenance policies for manufacturing systems, degradation analysis of bearings, and federated learning approaches for battery lifecycle prediction. He has pioneered methods for integrating physics-informed neural networks into prognostics and health management (PHM) systems. Key technical contributions span advanced statistical methodologies like sieve estimation for survival data, phase-type distributions modeling, and condition-based maintenance optimization. His interdisciplinary approach bridges operations research, mechanical engineering, and computer science to address complex reliability challenges. Recent projects include resilient consensus-based power grid management and contamination source identification frameworks. Notable collaborations involve developing intelligent cross-domain fault diagnosis systems using transformer networks and advancing the Internet of Federated Things (IoFT) for distributed data analytics. His work has been applied in aerospace, telecommunication infrastructure, and medical emergency response systems.

• Inventory Control
• Reliability Engineering
• Emergency Response Systems
• +۴ مورد دیگر

David Hsu is Provost's Chair Professor in the Department of Computer Science at the National University of Singapore (NUS) School of Computing, where he founded and directs the NUS Artificial Intelligence Laboratory (NUSAIL) and leads the Smart Systems Institute. His academic leadership includes chairing major conferences such as Robotics: Science & Systems (2015) and IEEE ICRA (2016), alongside editorial roles in IEEE Transactions on Robotics and the Journal of Artificial Intelligence Research. He earned a B.Sc. in Computer Science & Mathematics from the University of British Columbia and a Ph.D. in Computer Science from Stanford University. His research spans robotics, AI, and computational biology, with recent focus on robot planning under uncertainty and human-robot collaboration. Current work integrates machine learning with decision-theoretic planning to enable robust human-robot co-existence in unstructured environments. Analysis of his 2023-2025 publications reveals dominant trends in deformable object manipulation (e.g., clothes handling via semantic keypoints), open-world navigation using scene graphs, and LLM-driven multi-agent reasoning for complex tasks. Key innovations include perspective-aware visual grounding for human-centric interaction and functional object arrangement through compositional generative models, reflecting a strong emphasis on real-world applicability. His scientific contributions have earned prestigious recognition: IJCAI-JAIR Best Paper Prize (2022) for foundational AI research Robotics: Science & Systems Test of Time Award (2021) IEEE Fellowship (2018) for contributions to robotic planning RSS Best Systems Paper Award (2017) RoboCup Best Paper Award at IROS (2015) Humanitarian Robotics Award at ICRA (2015) As director of the Adaptive Computing Laboratory, Hsu drives research on fundamental computational frameworks for human-robot interaction. The lab's work on uncertainty-aware decision-making has secured significant research funding through grants from Singapore's National Research Foundation and industry partnerships with robotics firms. While specific student names aren't publicized, his leadership in the NUSAIL indicates extensive mentorship of doctoral candidates in AI and robotics.

• Robotics
• Artificial Intelligence
• Machine Learning
• +۲ مورد دیگر

LING Chun Kai is an Assistant Professor in the Department of Computer Science at the National University of Singapore (NUS), School of Computing. His research focuses on multiagent systems, computational game theory, and machine learning applications in adversarial real-world domains like cybersecurity and logistics. Educational background includes a PhD in Computer Science (2017-2023) from Carnegie Mellon University and a First Class BEng in Computer Engineering (2015) from NUS. Previously, he was a Postdoctoral Research Scientist at Columbia University. Current research interests span computational game theory, machine learning for multi-agent systems, equilibrium characterization in imperfect information settings, and applications in network security, logistics, and recreational games. Key methodological contributions include scalable algorithms for game solving, differentiable game solvers, and copula-based statistical modeling. Recent publications focus on attacker-defender graph games, language negotiation agents, and modeling games with incomplete information. Collaborations include researchers from Columbia University, Carnegie Mellon, and institutions working on GameSec, AAAI, Neurips, and ICML venues. Scientific Awards: IJCAI 2018 Distinguished Paper Award GameSec 2023 Best Paper Award GameSec 2024 Best Paper Award Singapore Teaching and Academic Research Talent Scheme (2024) Teaching includes courses on AI Planning and Decision Making (CS4246, CS5446) and Advanced Topics in Artificial Intelligence (CS6208).

• Artificial Intelligence
• Decision Making & Planning
• Machine Learning
• +۱۳ مورد دیگر

Suranga Chandima Nanayakkara is an Associate Professor in the Department of Computer Science at the National University of Singapore (NUS), leading the Centre for Holistic Inquiry into Lifelong Learning (CHILL) and the Smart Systems Institute (SSI). He holds roles such as AI+HCI Theme Lead at NUS+CNRS IPAL Lab and Residential Fellow at NUS College. His research focuses on assistive human-computer interfaces, emphasizing technologies that enhance perceptual and cognitive capabilities for individuals with sensory deficits. He earned his PhD and BEng from NUS, followed by postdoctoral work at MIT Media Lab. Notable projects include the Augmented Human Lab, iTILES for rehabilitation, and the FingerReader device for visually impaired shoppers. His work has garnered awards like the MIT TR35, TOYP, and INK Fellowship. Research interests include Intelligent Systems, Human Augmentation, and Design Science. He explores applications in assistive technologies, healthcare informatics, and educational tools. Over 15 publications highlight innovations in wearables, stress management, and multimodal interaction. Awards: 40+ accolades, including MIT TR35, TOYP, and multiple design awards for projects like Kiwrious and FingerReader. Grants: Led projects funded by institutions like NUS and Singapore’s innovation initiatives. Labs: Augmented Human Lab (founded 2011), focusing on humanizing technology through natural interfaces.

• Intelligent Systems
• Human Augmentation
• Human-Computer Interaction
• +۳ مورد دیگر

Professor He Bingsheng is a faculty member at the Department of Computer Science, School of Computing, National University of Singapore (NUS), where he also serves as Vice-Dean, Research. He holds a Ph.D. in Computer Science from the Hong Kong University of Science & Technology (2008) and dual bachelor’s degrees in Computer Science & Engineering and Business Administration from Shanghai Jiao Tong University (2003). Education: Ph.D. (HKUST, 2008), B.E./B.B.A. (SJTU, 2003) Prior roles: Microsoft Research Asia (2008-2010), Nanyang Technological University (NTU), Singapore His research focuses on Big Data management systems , particularly on cloud computing and emerging hardware architectures (GPU, FPGA, NVM). He has led projects like ThunderGP, a novel FPGA-accelerated graph processing framework achieving 419x speedup for Covid-19 prevalence estimation. His work spans parallel/distributed systems and graph algorithms , with publications in ACM SIGMOD, VLDB, SC, and IEEE Transactions. The selected articles highlight his contributions to GPU/FPGA optimization , LLM applications , and graph analytics . He has received multiple best paper/demo awards, including IEEE/ACM ICCAD (2017), IEEE IC2E (2016), and ACM SIGMOD (2008). As a PC chair and editorial board member for journals like IEEE TPDS and TCC, he actively shapes academic discourse. PhD Students: Chen Xinyu, Tan Hongshi Courses Taught: CS4225/5425 Big Data Systems for Data Science

• Big Data Systems
• Cloud Computing
• High Performance Computing
• +۴ مورد دیگر

Lizi Liao is an Assistant Professor at the School of Computing and Information Systems , Singapore Management University (SMU) , specializing in Artificial Intelligence and Conversational AI . Her research bridges Machine Learning , Natural Language Processing , and Multimodal Systems , focusing on proactive dialogue systems, multimodal conversational search, and task-oriented interactions. Education : PhD in Computer Science (2019) from the National University of Singapore (NUS) , advised by Professor Tat-Seng Chua . Research Interests center on principles of human conversational understanding and machine implementation, particularly in proactive conversational agents , multimodal dialogue systems , and target-driven conversation planning . Key applications include emotional support systems , intelligent shopping assistants , and learning companions . Recent Publications (2024-2025) highlight her work on LLM-based proactive dialogue , multimodal emotion recognition , and dynamic graph modeling , often integrating NLP , Multimedia , and Knowledge Graphs . Collaborative projects with her CoAgent Lab team emphasize human-AI interaction and ethical response generation . Scientific Awards : Google South Asia & Southeast Asia Research Award 2023 Lee Kong Chian Fellow Teaching includes Visual Analytics for Business Intelligence (undergraduate) and Text Analytics and Application (graduate). She also serves as Associate Editor for TOIS and TOMM , and organizes tutorials at ACL , SIGIR , and WSDM .

• Artificial Intelligence
• Data Science
• Machine Learning
• +۵ 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.

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

Dr. Alvin J. K. Chua is an Assistant Professor at the National University of Singapore (NUS) under the NUS Presidential Young Professorship. He holds a joint appointment in the Department of Mathematics and a courtesy appointment in the Department of Statistics and Data Science. His research focuses on gravitational-wave astronomy , particularly extreme mass ratio inspirals (EMRIs) as key sources for the LISA mission. He develops computational and statistical methods for modeling GW sources and analyzing detector data, with recent work on machine learning and Bayesian inference techniques. His selected publications highlight advancements in modeling beyond-vacuum-GR effects in EMRIs non-local parameter degeneracies rapid relativistic waveform generation neural networks for GW inference statistical sampling on manifolds These works span gravitational-wave astrophysics , computational relativity , and applied statistics . Scientific recognition includes the NUS Presidential Young Professorship. He collaborates with the LISA Consortium and the North American Nanohertz Observatory for Gravitational Waves (NANOGrav).

• Gravitational-Wave Astronomy
• General Relativity
• Machine Learning for Science
• +۳ مورد دیگر