جست‌وجوی استاد و پژوهشگر

Sobah Abbas PETERSENمشاهده پروفایل

دانشیار

• Sustainable Urban Development
• Enterprise Modelling
• Enterprise Architecture
• +۴ مورد دیگر

Sobah Abbas Petersen is an Associate Professor at the Department of Computer Science, Norwegian University of Science and Technology (NTNU), and a Senior Research Scientist at SINTEF Digital, Norway. Her research focuses on Sustainable Cities, Enterprise Modelling, Technology Enhanced Learning, and the nexus of energy, built environments, health, and digital technologies. She emphasizes co-design processes, gamification, and citizen engagement to drive sustainable transitions. Education : PhD, Department of Computer Science, NTNU (2003) MSc, Department of Artificial Intelligence, University of Edinburgh (1992) BEng (Hons), Department of Electrical and Electronic Engineering, University of Salford (1989) Her teaching includes Master’s courses on Enterprise Architecture and Smart Sustainable Cities, recognized by an 'Excellent Teaching Practitioner' award at NTNU. Current projects explore smart urban futures, citizen behavior change through technology, and digital innovation ecosystems. Selected Research Themes : Enterprise Modelling for healthcare and innovation Data-driven approaches for urban sustainability Technology adoption in smart cities Inclusive urban design through interpretive flexibility She has collaborated with NGOs, public authorities, and industries across multidisciplinary projects. In 2024, she served as a Visiting Researcher at LKYCIC, Singapore.

Rudy Setionoمشاهده پروفایل

دانشیار

• Data Science
• Business Analytics
• Intelligent Systems
• +۴ مورد دیگر

Rudy Setiono is an Associate Professor and Assistant Dean of Graduate Studies at the School of Computing, National University of Singapore (NUS). He has been with NUS since August 1990, following the completion of his Ph.D. in Computer Science from the University of Wisconsin-Madison. Previously, he served as Vice Dean (Undergraduate Affairs) from November 2001 to July 2005 at the School of Computing. B.Sc. in Computer Science from Eastern Michigan University (1984) M.Sc. in Computer Science from University of Wisconsin-Madison (1986) Ph.D. in Computer Science from University of Wisconsin-Madison (1990) Professor Setiono's research focuses on neural networks, particularly in rule extraction, neural network construction and pruning, and applications in optimization. His work spans theoretical foundations to practical implementations in credit scoring, poverty analysis, and business intelligence. He has made significant contributions to making neural networks more interpretable through rule extraction techniques, bridging the gap between black-box models and transparent decision systems. His recent publications show a strong trend toward practical applications of neural network rule extraction in credit scoring, poverty analysis, and document processing. The research demonstrates consistent evolution from theoretical neural network construction to real-world applications across finance, social sciences, and business analytics, with an emphasis on model interpretability and practical implementation. Senior Member of IEEE Associate Editor of IEEE Transactions on Neural Networks (2000-2005) Professor Setiono has supervised numerous research projects and taught courses including BT4103 Business Analytics Capstone Project, BT4240 Machine Learning for Predictive Data Analytics, IS5152 Data-Driven Decision Making, and IS4240 Business Intelligence Systems. His work has been published in reputable journals including IEEE Transactions on Neural Networks, IEEE Transactions on Data and Knowledge Engineering, and Neurocomputing.

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.

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.

Liu Yangمشاهده پروفایل

استاد

• Cybersecurity
• Software Engineering
• Artificial Intelligence
• +۳ مورد دیگر

Prof. Liu Yang is a full Professor and University Leadership Forum Chair at the School of Computer Science and Engineering, Nanyang Technological University (NTU). He holds the President’s Chair in Computer Science and Engineering and serves as Executive Director of the Cyber Research Programme Office and Cyber Security Research Centre @ NTU. His research focuses on Cybersecurity, Software Engineering, and Artificial Intelligence, with contributions in formal verification, program analysis, and deep learning systems. He leads projects like the Securify initiative and develops tools such as the Process Analysis Toolkit (PAT) for system verification. Education: Ph.D. (2010) and Bachelor of Computing Science (2005) from National University of Singapore. Research Interests: Cybersecurity (malware analysis, vulnerability detection), Software Engineering (formal verification, program analysis), AI (security, robustness, explainability), and Automotive Security. His work bridges formal methods, program analysis, and machine learning to address challenges in secure systems and autonomous systems. Notable Achievements: Over 6000 citations (2020), H-index 38, awards include Nanyang Assistant Professor (2013), NRF Investigatorship (2020), and ACM Distinguished Speaker. His research spans journals like IEEE Transactions on Software Engineering and conferences such as NeurIPS, CVPR, and ICSE. Grants and Leadership: Principal Investigator of grants totaling over 5M SGD, including projects on vulnerability detection, formal verification, and cybersecurity. Organizes international conferences like ASE, ICSE, and FM, and serves on editorial boards such as IEEE Access. Labs/Teams: Leads the Cyber Security Research Centre @ NTU and collaborates on projects like the HP-NTU Digital Manufacturing Corp Lab and the National Satellite of Excellence in Singapore.

Tian Haoمشاهده پروفایل

مدرس

• Embodied intelligent learning in robots
• Simulation and planning of dexterous grasping
• Human-robot interaction
• +۳ مورد دیگر

Tian Hao is a Lecturer at the School of Big Data and Computer Science , Guizhou Normal University . He received his B.Eng. and Ph.D. in Engineering from the School of Software Engineering at East China Normal University in 2014 and 2020, respectively. During his doctoral studies, he was jointly trained at the University of Maryland under the China Scholarship Council program. From 2020 to 2022, he was a postdoctoral fellow in the Department of Computer Science and Technology at the University of Hong Kong . Prior to joining Guizhou Normal University in June 2024, he served as a Senior Engineer and Team Leader at Huawei HiSilicon's Turing Robotics division. Education: 2010–2014: B.Eng., School of Software Engineering, East China Normal University 2014–2020: Ph.D. in Engineering, School of Software Engineering, East China Normal University 2018–2019: Joint Doctoral Training, University of Maryland, USA 2020–2022: Postdoctoral Fellow, Department of Computer Science and Technology, University of Hong Kong Research Interests: Tian Hao's research spans embodied intelligent learning in robots , dexterous grasping simulation and planning , human-robot interaction , and virtual/augmented reality (VR/AR) . His work integrates machine learning, computer graphics, and robotics to enable robots to manipulate complex objects in cluttered or virtual environments. Publications & Trends: His publications (2016-2023) consistently focus on robotic grasping and manipulation , virtual hand interaction , and real-time simulation . Notable venues include IEEE Transactions on Robotics , IEEE VR , and ICRA , reflecting an emphasis on high-impact robotics and graphics venues. Scientific Awards: No specific awards are listed in the provided text. Grants & Projects: Research on 3D Design and Dexterous Robot Sewing Technology for Personalized Garment Manufacturing (NSFC-RGC, 2017-2020) Visual model and environment construction based on multi-source data and its dynamic simulation (NSFC, 2016-2020) Quadruped robot dog autonomous inspection solution based on Ascend AI platform (Huawei HiSilicon) Ascend-based balloon robot platform (Huawei HiSilicon) Labs & Teams: He lectures at the Robot Operating System (ROS) Summer School in China and serves as a reviewer for premier IEEE journals and conferences, indicating active engagement in the robotics and VR communities.

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.

• Machine Learning
• Data Mining
• Computer Vision
• +۷ مورد دیگر

Guansong PANG is a full-time Assistant Professor at the School of Computing and Information Systems , Singapore Management University (SMU) , where he leads the Machine Learning & Applications (MaLA) Lab . He holds a PhD from University of Technology Sydney (2019) and has previously served as a Research Fellow at the Australian Institute for Machine Learning , University of Adelaide. Research Interests : His work centers on machine learning and data mining , particularly focusing on anomaly detection , open-world learning , and foundation models for graphs, time series, and tabular data. He investigates security and safety in foundation models , including hallucination mitigation and AI-generated content detection , with applications spanning network intrusion detection , fraud detection , industrial defect detection , and biometric anti-spoofing . Recent Awards : Lee Kong Chian Fellowship (2024-2026) World's Top 2% Scientists (2022-2024) DSAA 2023 Best Paper Award (Applications Track) Most Influential KDD 2023 Paper Professional Roles : Area Chair for NeurIPS, ICLR, ICML, CVPR, KDD, PAKDD, IJCAI, and AAAI; Associate Editor for IEEE Transactions on Neural Networks and Learning Systems and Pattern Recognition ; Editorial Board member for IEEE Intelligent Systems and International Journal of Data Science and Analytics .

Yi'En Chengمشاهده پروفایل

مدرس

• Human geography
• Sociology of education
• Education policy
• +۱۲ مورد دیگر

Dr. Yi'En Cheng is Lecturer at NUS College of the National University of Singapore with a courtesy joint appointment in the Department of Geography. He concurrently serves as an Associate of Asia Research Institute's (ARI) Asian Migration Cluster. Previously, he was Research Fellow at ARI (2019-2022) and Postdoctoral Fellow at Yale-NUS College (2017-2019). Cheng completed his Doctor of Philosophy at the University of Oxford as recipient of the Oxford Clarendon and St Peter's Diggle Scholarships. He earned his Master of Social Sciences (2012) and Bachelor of Social Sciences with major in Geography and minor in Gender Studies (2010), both from NUS. He serves on editorial boards of Global Networks and Children's Geographies . His research focuses on three intersecting strands: international student and youth mobilities, youth citizenship and politics, and education and globalization. Cheng examines how global changes affect young people's education, citizenship, and mobility experiences, particularly how education provides resources for young people to navigate social hierarchies and mobility regimes. His work has expanded to include rural and peri-urban contexts in China-Southeast Asia connections, especially regarding student mobility flows between southern China and northern Vietnam. Cheng's publications span internationally peer-reviewed journals, books, and blogs, with notable works including the edited volume 19 Letters to Coronavirus and research on visual methods in overseas field-based learning. His work often employs innovative methodologies including photovoice and mobile research approaches. Member, Editorial Board, Global Networks Member, Editorial Board, Children's Geographies Recipient, Oxford Clarendon Scholarship Recipient, St Peter's Diggle Scholarship Cheng teaches Global Experience (GEx) Mekong Delta and Impact Experience (IEx) in Vietnam under the Global Pathways programme, as well as contributing to classroom teaching in 'Understanding the Social World: Singapore and Beyond.' His teaching philosophy emphasizes challenging students' assumptions about the world and building upon their existing knowledge. He currently leads two major research projects: 'Belt and Road Initiative and Student Mobilities in China-Southeast Asia' (MOE Tier 2 grant) and 'Visual Methods in Overseas Field-Based Learning.' His research lab focuses on international student migrations and educational mobilities, with geographic expansion beyond global cities to rural, peri-urban, and fringe cities. Through field engagements in GEx/IEx programs, Cheng has developed research on Chinese transnationalisms along the Belt and Road, Chinese/Southeast Asian student mobilities, and education-migration brokerage.

Sam Conrad Joyceمشاهده پروفایل

دانشیار

• Architectural Design
• Design Computation
• Generative AI
• +۷ مورد دیگر

Sam Conrad Joyce is an Associate Professor at Singapore University of Technology and Design (SUTD), holding a joint appointment in the Architecture and Sustainable Design pillar. He serves as the PhD Programme Coordinator and leads the Spatial AI Studio under the Design and Artificial Intelligence (DAI ASD) initiative. Joyce heads the Meta Design Lab, focusing on the integration of computation, design, and urban systems to enhance collaborative human-machine workflows in architecture and master planning. His research emphasizes generative design, big data analytics, machine learning, and web-based visualization to augment design processes. Before joining SUTD, Joyce worked at Foster + Partners (2008–2015) and Buro Happold (2009–2011), contributing to high-profile projects such as the Apple Campus and the Louvre Abu Dhabi. His doctoral work at the Universities of Bath and Bristol explored data-rich systems for design space exploration and decision-making, integrating distributed computing, optimization, and visualization. Key research interests include design optimization, spatial big data analytics, AI-driven design collaboration, and web-based tools. Joyce has led projects funded by entities like URA-SUTD, Singapore Aviation, and Changi General Hospital. His work bridges academia and practice, emphasizing practical applications of computational methods in architecture and urban design. He has taught globally, including at the Architectural Association (London) and Chalmers University (Sweden), and collaborates on initiatives like the Venice Biennale and Smart Geometry conferences. His research outputs span design computation, AI integration, and urban analytics, reflecting a commitment to advancing innovative, data-informed design practices.

Alan Cheng Holunمشاهده پروفایل

مدرس ارشد

• Computational Geometry
• Parametric Surfaces
• Computer Graphics
• +۲ مورد دیگر

Alan Cheng Holun is a Senior Lecturer in the Department of Computer Science at the National University of Singapore, specializing in computational geometry, computer graphics, and bio-geometric modeling. He received his Ph.D. in Computing Science from the University of Illinois at Urbana-Champagne in 2002 under Herbert Edelsbrunner. Education: B.Sc. (Computing Science, Chinese University of Hong Kong) M.Phil. (Computing Science, Hong Kong University of Science and Technology) Ph.D. (Computing Science, University of Illinois at Urbana-Champaign) Research Interests: Computational Geometry Parametric Surfaces Computer Graphics Visualization Bio-geometric Modeling Courses Taught: CS1010E Programming Methodology CS2040C Data Structures and Algorithms CS3241 Computer Graphics IT5001 Software Development Fundamentals Scientific Contributions: Focus on skin surface meshing, molecular modeling, and mesh deformation algorithms Developed dynamic skin triangulation methods with applications in bio-geometry Pioneering work in quality mesh generation for molecular structures Published extensively in conferences like IEEE Visualization, SODA, and ISAAC Awards: Best Teaching Assistant Award (HKUST, 1996) Collaborations: Former visiting scholar at Duke University's BioGeometry Center Contact: Email: hcheng@comp.nus.edu.sg Office: AS6-05-03, NUS Consultation Hours: Thursday 2:00-4:00pm

• Artificial Intelligence
• Data Science
• Machine Learning
• +۷ مورد دیگر

Wang Zhaoxia is an Associate Professor of Computer Science (Practice) at the School of Computing and Information Systems, Singapore Management University. Her expertise lies in Artificial Intelligence, Data Science, and Machine Learning with a focus on Natural Language Processing (NLP), Sentiment Analysis, and Knowledge Graphs. She holds a PhD from Nankai University (2004). Research Interests: Her work spans AI-driven solutions for sentiment analysis, maritime risk management, audio-to-music conversion, and social media analytics. Recent projects include leveraging Large Language Models (LLMs) for tasks like logical reasoning, translation optimization, and risk assessment. Publications: Recent work highlights include developing metrics for LLM performance (RAP), emotion analysis in images, and automated music transcription. Her research demonstrates cross-disciplinary applications of AI in fields like finance (ICO success prediction) and health (disease surveillance). Awards: No awards explicitly listed Advising: Supervises 3 PhD/Master students including HUANG Donghao and Nicole Anne Hui Ying TEO Contact: zxwang@smu.edu.sg | +65 68261347

• Transnational Migration
• Ageing Studies
• Gender Studies
• +۴ مورد دیگر

Menusha De Silva is a Lecturer in Geography at the National University of Singapore, specializing in transnational migration, ageing, and feminist pedagogy. Her research examines how migration patterns shape eldercare dynamics within transnational families, with particular focus on Sri Lankan diaspora communities. She investigates the intersections of migration, gender, and citizenship across the lifecourse. Research Focus: De Silva's work explores older migrants' negotiations of transnational citizenship, the transformation of care expectations in Asian societies, and the development of 'care pentagons' in transnational families. Her pedagogical research applies feminist frameworks to community-based learning and blended education environments. Publications: Her scholarly output (2011-2025) demonstrates consistent focus on migration, ageing, and care through diverse formats including journal articles, book chapters, and policy-oriented publications. Recent work shows increasing engagement with pedagogical theory and educational geographies.

Agnieszka Chalasمشاهده پروفایل

استادیار

• Arts integration
• Museum Education
• Teacher Education
• +۳ مورد دیگر

Agnieszka Chalas is an Assistant Professor of Art Education at the National Institute of Education (NIE) in Singapore, within the Visual & Performing Arts department. She holds a Doctor of Philosophy and previously served as Assistant Professor of Museum Studies at the University of Toronto and held sessional lecturer roles at Queen's University and the Ontario Institute for Studies in Education (OISE). Her research focuses on arts integration, museum education, teacher education, and program evaluation in the arts. Education: Doctor of Philosophy (2014–2019), Queen's University MEd in Art Education (2004–2006), Concordia University BEd in Art Education (2001–2002), University of British Columbia Research Interests: Dr. Chalas explores arts integration as a curricular approach, issues-based art education, museum learning environments, and evaluation methodologies in cultural institutions. Her work emphasizes connecting formal and informal learning spaces through innovative pedagogical frameworks. Recent projects include historical reconciliation through visual essays and collaborative museum-school partnerships. Awards & Recognition: Emerging Scholar Award (2024) Finalist, Governor General’s History Award (2019) SSHRC Doctoral Fellowship ($80k/4yrs, 2014) Storytellers Challenge Prize ($3k, 2018) Professional Contributions: She has advised on curriculum design for teacher education programs and contributed to museum evaluation frameworks. Her work bridges artistic practice with educational theory, advocating for inclusive and culturally responsive pedagogies.

• Empirical Legal Studies
• Law and Economics
• Law and Technology
• +۶ مورد دیگر

Jerrold SOH is an Assistant Professor of Law at the Yong Pung How School of Law, Singapore Management University (SMU), serving concurrently as Deputy Director of the Research Programme in Computational Law at the Centre for Digital Law. He holds an LL.M. from Harvard University and dual first-class honors degrees in Law (LL.B.) and Economics (B.Soc.Sci.) from the National University of Singapore (NUS). His academic journey includes roles as Deputy Director at the Centre for Computational Law (2021–2024) and Lecturer of Law at SMU (2018–2020). SOH’s research focuses on empirical legal studies, law and technology intersections, and computational methods in jurisprudence. He investigates topics such as judicial citation patterns, algorithmic accountability, AI-driven legal systems, and tort liability for automated vehicles. His work often bridges legal theory with data science, exemplified by projects like legal text formalization, network analysis of case law, and blockchain applications in property law. SOH has published widely in journals like the Asian Journal of Comparative Law , Frontiers in Physics , and American Business Law Journal , with recent work addressing AI legal implications, blockchain land transfers, and antitrust regulation. He is a Chief Data Scientist at Lex Quanta Pte Ltd and has received honors such as the SMU START Overseas Postgraduate Scholarship and multiple Dean’s Lists at NUS. His professional contributions span computational law infrastructure development, legal innovation advocacy, and educational initiatives in technology law. Current research priorities include AI ethics in legal contexts, control-centric liability frameworks, and empirical analyses of judicial decision-making processes.