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Lu Shijian is an Associate Professor (tenured) at the School of Computer Science and Engineering , Nanyang Technological University (NTU) , Singapore. He holds a PhD in Electrical and Computer Engineering from the National University of Singapore and leads the Visual Intelligence Lab (VILab) , focusing on humanlike visual perception, understanding, and creation. University: Nanyang Technological University School: School of Computer Science and Engineering Academic Rank: Associate Professor (tenured) Email: Shijian.Lu@ntu.edu.sg Office: N4-02C-101, NTU, Singapore His research spans computer vision, deep learning, image and video analytics, visual intelligence, and machine learning , with key topics including scene text detection, unsupervised domain adaptation, image synthesis, satellite image analytics, and facial expression recognition. His work integrates supervised, semi-supervised, and self-supervised learning across 2D images, 3D point clouds, and multi-spectral data. The recent publications highlight a strong trend in domain adaptation, generative modeling, 3D vision, and multimodal AI . His lab produces high-impact work accepted at top venues like CVPR, ICCV, ECCV, NeurIPS, and TPAMI, with applications in autonomous systems, image editing, and robust AI. Top winner of ICFHR2014 Competition on Word Recognition from Historical Documents Top winner of ICDAR 2013 Robust Reading Competition (scene text segmentation) Top winner of ICDAR 2013 Document Image Binarization Contest (DIBCO 2013) Top winner of H-DIBCO 2010 – Handwritten Document Image Binarization Competition Top winner of ICDAR 2009 Document Image Binarization Contest (DIBCO 2009) Lu advises several PhD students and serves as an Associate Editor for Pattern Recognition and Neurocomputing . He has held leadership roles in top conferences as Senior Program Committee member (IJCAI, AAAI) and Area Chair (ICDAR, WACV). His lab, the Visual Intelligence Lab , is actively recruiting PhD students and conducting cutting-edge research in visual intelligence, with recent work on 3D Gaussian splatting, backdoor attacks, and vision-language models.

• Computer Vision
• Deep Learning
• Image and Video Analytics
• +14 more

Rajesh Krishna BALAN is a Full-Time Professor at the School of Computing and Information Systems (SCIS) at Singapore Management University (SMU) . His research focuses on Human-Machine Collaborative Systems , Pervasive Sensing , and Health & Wellbeing technologies. Based in Singapore, he leverages mobile computing to address urban sustainability and quality-of-life challenges. PhD from Carnegie Mellon University (2006) Specializes in WiFi sensing , VR/AR , and health monitoring Advises PhD students in areas like urban mobility , empathetic design , and cyber-physical systems Beyond academia, BALAN's work bridges ubiquitous computing and public health , with applications in ageing populations , mental health analytics , and smart city optimization . His recent publications highlight cross-disciplinary approaches to sleep analysis , group behavior modeling , and contactless physiological sensing . BALAN actively contributes to educational technology through projects like Technology-Enhanced Learning frameworks. He is also a mentor in collaborative research areas including biomedical informatics and lifestyle monitoring , with a focus on mobile GPU optimization and low-power systems .

• Human-Machine Collaborative Systems
• Pervasive Sensing & Systems
• Learning & Work
• +9 more

Cheung Ngai-Man is an Associate Professor and Associate Head of Pillar (Education) at Singapore University of Technology and Design (SUTD), part of the Information Systems Technology and Design (ISTD) pillar. He holds a Ph.D. in Electrical Engineering from the University of Southern California (2008) and has held research positions at Stanford University, Texas Instruments, IBM, and others. His research focuses on image and signal processing, computer vision, machine learning, and artificial intelligence. Education: Ph.D., Electrical Engineering, University of Southern California (2008); Postdoctoral research at Stanford University (2009–2011). Research Interests: Develops algorithms for multimedia data processing, explores interdisciplinary applications of signal processing and AI, and addresses challenges in computer vision and generative models. Recent work includes fairness in generative models, few-shot image generation, and adversarial robustness. Publications: Over 100+ peer-reviewed papers in top venues (CVPR, NeurIPS, IEEE TIP, TPAMI) focusing on computer vision, generative models, and AI security. Notable 2023 work includes studies on label-only model inversion attacks and fairness metrics in generative systems. Awards: Best Paper Finalist (CVPR 2019), SAIL Award Finalist (WAIC 2019), Outstanding Associate Editor (IEEE T-MM), Croucher Foundation Fellowship. Students: Supervised postdocs (Hossein Nejati, Fang Lu), research assistants (Mohammad Rostami), and visiting students (Ma Rui). Labs/Teams: Leads research groups in AI, computer vision, and multimedia systems at SUTD. Has spun off AI initiatives for wound care and contributed to Singapore’s National AI Strategy.

• Artificial Intelligence
• Augmented Intelligence
• Data Science
• +4 more

Min Lee is a Full-time Assistant Professor of Computer Science at Singapore Management University's School of Computing and Information Systems (SCIS). Holding a PhD from Carnegie Mellon University (2021), Lee specializes in Artificial Intelligence with a focus on Human-AI Collaborative Systems and their applications in healthcare. Their research bridges technical innovation with human-centric design, emphasizing trustworthiness, explainability, and accessibility in AI systems. Research interests include decision-making optimization, human-machine collaboration, and AI-driven solutions for healthcare challenges such as stroke rehabilitation, elderly care monitoring, and clinical decision support. Lee has pioneered low-cost AI/robotic solutions for post-stroke rehabilitation exercises, integrating socially assistive robotics with real-time feedback mechanisms. Recent work highlights AI's role in enabling trustworthy clinical decision-making through explainable AI (XAI) techniques like counterfactual explanations and gradient-based methods. Their systems address ethical concerns in predictive healthcare and advocate for stakeholder-inclusive design processes. Awards and grants: No specific awards mentioned in the profile, though research has been supported through collaborative projects with clinical partners and iterative user evaluations involving therapists and patients. Advising focuses on multidisciplinary projects spanning AI, healthcare, and human-computer interaction. Current advisees include BHOSALE Rimmon Saloman, TRAN Truong Thuy, and YANG Xinlin. Lee collaborates closely with clinical stakeholders to translate technical advancements into practical healthcare solutions, emphasizing iterative design and real-world applicability. Labs/teams: Active in SCIS's AI and Data Science initiatives, leading projects on intelligent decision support systems, socially assistive robotics for rehabilitation, and human-centered AI ethics frameworks.

• Artificial Intelligence and Data Science
• Decision Making & Optimization
• Machine Learning & Intelligence
• +8 more

Angela Yao is a Dean's Chair Associate Professor and Assistant Dean of Research at the National University of Singapore's School of Computing, Department of Computer Science. She leads the Computer Vision and Machine Learning Group and specializes in visual perception of people, focusing on both high-level semantics of human actions and lower-level physical modeling. Her research interests span Computer Vision , Machine Learning , and Artificial Intelligence , with specific expertise in human action recognition, 3D human modeling, video understanding, and small data AI. Dr. Yao's work bridges theoretical advances with practical applications, particularly in activity anticipation and human-computer interaction. Dr. Yao's publication trends reveal a strong focus on zero-shot learning for activity anticipation, 3D human modeling, and techniques for working with limited training data. Her research has evolved from foundational work in 3D pose estimation to more recent innovations in diffusion models and cross-modal learning, demonstrating consistent contributions to advancing computer vision capabilities. NRF Fellowship for Artificial Intelligence (2019) German Pattern Recognition (DAGM) Award (2018) Dr. Yao has successfully mentored PhD students including Fadime Sener and secured significant research funding including the NRF Fellowship. Her research group focuses on developing AI systems capable of understanding and anticipating human activities with applications in robotics and human-computer interaction. She teaches CS4243 Computer Vision and Pattern Recognition and leads the Computer Vision and Machine Learning Group at NUS Computing.

• Computer Vision
• Machine Learning
• Artificial Intelligence
• +3 more

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.).

• Medical Image Analysis
• Computer Vision
• 3D Modeling
• +5 more

Prof Kot Chichung, Alex is a Professor at the School of Electrical & Electronic Engineering and currently serves as Associate Dean of the College of Engineering at Nanyang Technological University (NTU), Singapore. He has been affiliated with NTU since 1991, previously leading the Division of Information Engineering and holding roles as Associate Chair/Vice Dean for Research. His expertise spans signal processing, biometrics, and information security. Editorial Roles: Associate Editor for IEEE Transactions on Signal Processing, EURASIP Journal of Applied Signal Processing, and IEEE Transactions on Multimedia. Professional Service: IEEE Distinguished Lecturer, former General Co-Chair of the 2004 IEEE International Conference on Image Processing (ICIP). Research focuses on communication signal processing, image forensics, and multimedia security. His work intersects with Info-Communication Technology and Interactive Digital Media, contributing to advancements in data and video analytics. He actively engages in IEEE technical committees and has held leadership roles within the organization. Awards: Fellow of the IEEE and Institution of Engineers Singapore (IES). Grants & Funding: Current grants not explicitly listed, but extensive publication record indicates active research funding. Prof Kot mentors students and researchers in his field while overseeing interdisciplinary initiatives as Associate Dean in the College of Engineering.

• Signal Processing
• Biometrics
• Image Forensics
• +5 more

Heyuan Shi is an Associate Professor at the School of Electronic Information, Central South University since 2023. He earned his B.S. (2015) and Ph.D. (2020) from Central South University and Tsinghua University respectively. His research focuses on software quality assurance with emphasis on kernel fuzz testing , open source software security , and AI application security . Presided over 10+ projects including NSFC General Program (No.62472448) and National Key R&D Sub-Project Published 30+ CCF-A/B papers across software security, machine learning, and quantum testing Supervised 15+ graduate students in software quality assurance areas His recent 2024-2025 publications demonstrate expertise in: LLM-enhanced patch classification Quantum neural network verification Hypergraph adversarial attacks RTOS fuzzing techniques Scientific recognition includes: 2024 Beijing Science & Technology Progress Award (First Prize) Hunan Province Xiaohe Sci-Tech Talent (2023) China Association for Science & Technology Young Talent (2025-2027) Active in academic service as PC member for FM2024 and reviewer for IEEE Transactions journals. Leads industry collaborations with Alibaba and Beijing Institute of Aerospace Metrology.

• Software Quality Assurance
• Kernel Fuzz Testing
• Operating System Security
• +3 more

Dr. Terence Sim Mong Cheng is an Associate Professor at the Department of Computer Science within the School of Computing, National University of Singapore . He serves as Vice Dean for Admissions and previously held Vice Dean roles for Communications and Second Vice President of the International Association for Pattern Recognition. His academic journey includes degrees from MIT, Stanford, and Carnegie Mellon University. Ph.D. in Electrical & Computer Engineering (Carnegie Mellon University) M.S. in Computer Science (Stanford University) S.B. in Computer Science & Engineering (MIT) His research focuses on Biometrics and Visual Computing , spanning Deepfake synthesis/detection , Facial image analysis , Continuous authentication , and Multimodal biometrics . He integrates machine learning with physics-based modeling to address complex challenges in these domains. Recent publications highlight advancements in deepfake detection (2023), multi-task learning (2022), and gait-based authentication (2020-2022). These works intersect biometrics, privacy, and machine learning. Face and Gesture 2017 : Test of Time Award Computer Analysis of Images and Patterns 2017 : Best Paper Award NUS Faculty Teaching Excellence Award (2003, 2005) Temasek Young Investigator Award (2005) Dr. Sim has taught diverse courses including Biometrics Authentication , Computer Vision , and Discrete Structures . He provides biometric consultancy in areas like technical assessments and feasibility studies .

• Biometrics
• Computer Vision
• Machine Learning
• +3 more

Professor Li Leida is a National Young Talent and doctoral supervisor at Xidian University's School of Artificial Intelligence. His research focuses on computer vision, image/video quality assessment, computational aesthetics, and visual sentiment analysis. He leads the Brain-like Visual Perception and Evaluation Laboratory and collaborates with industry partners like OPPO, Huawei, and Tencent. He has published over 90 papers in top venues like TPAMI and CVPR, with 6 highly cited papers and 8,400+ citations. He serves as deputy editor-in-chief of IEEE Transactions on Image Processing and is a senior member of IEEE/CCF/CSIG. Education & Academic Roles: PhD Supervisor/Master Supervisor Member of OPPO Computational Imaging Expert Committee Area Chair for ACM Multimedia 2025 Research Interests: Dr. Li's work bridges theoretical computer vision with practical applications in imaging quality, aesthetic evaluation, and sentiment analysis. His team develops benchmarks like AesBench for large model evaluation. Recent advancements include scanned image enhancement algorithms and personalized aesthetic datasets like PARA. Industry Impact: OPPO ColorOS integration Live broadcast camera technologies DXOMARK Portrait Quality Assessment Challenge winner (2024) Awards & Recognition: First Prize in Shaanxi Natural Science (2021) 2022 OPPO Industry Collaboration Award Stanford's Top 2% Global Scientists (2023-2024) Grants & Labs: Secured 5 National Natural Science Foundation projects. Active in lab collaborations with companies like DJI and Huawei's imaging teams.

• Computer Vision
• Image and Video Quality Assessment
• Computational Aesthetics
• +3 more

Sanka Rasnayaka is a Lecturer at the School of Computing, National University of Singapore , where he has worked since 2022. He previously served as a full-time Teaching Assistant and PhD candidate at the same institution. PhD in Computer Science (2021), National University of Singapore B.Sc. Engineering (Honours) in Computer Science and Engineering (2016), University of Moratuwa, Sri Lanka Research interests focus on Artificial Intelligence and Computer Vision , specifically in biometrics, privacy, and human perception. Current projects explore: Biometrics & Continuous Authentication (gait, keystroke dynamics) Large Language Models for Software Engineering Physics-Informed Generative AI for flood modeling Recent publications demonstrate expertise in: Biometric authentication systems Privacy-preserving AI Transformer architectures for behavioral analysis Generative AI in environmental modeling Teaching includes foundational courses like CS1101S Programming Methodology (co-teaching since 2022) and CS2040 Data Structures and Algorithms (AY2410). He also developed workshops on Generative AI, LLMs, and Computer Vision. Projects supervised: CRISP Platform for classroom management Live Annotation Tool for educators AI Pal for customized LLM assistants Scientific awards include multiple Teaching Excellence Awards (2024-2025) and scholarships from NUS (2017-2021).

• Artificial Intelligence
• Machine Learning
• Computer Vision
• +6 more

Prof. Tan Yap Peng is a Professor and Chair of the School of Electrical & Electronic Engineering at Nanyang Technological University (NTU), Singapore. He holds the President's Chair in Electrical and Electronic Engineering and serves as Associate Vice President (Lifelong Learning – Postgraduate Programmes by Coursework). His research focuses on multimedia analysis, computer vision, machine learning, and data analytics. He earned his B.S. from National Taiwan University and M.A./Ph.D. from Princeton University. He has led major initiatives including the INFINITUS Infocomm Research Centre and contributed to IEEE technical committees. His over 200 publications span image/video processing, neural network robustness, and cross-modal systems. Awards include IEEE Fellow status. Education: B.S. Electrical Engineering (NTU), M.A./Ph.D. (Princeton) Research interests emphasize interactive digital media, content-based analysis, and AI-driven solutions for visual and signal processing. His work addresses challenges in adversarial attacks, video generation, and low-light image enhancement. He has held editorial roles at IEEE Transactions and EURASIP journals. Conference leadership includes chairs for ICME and ICIP. His contributions bridge academia and industry through collaborative research networks.

• Image and Video Processing
• Multimedia Analysis
• Computer Vision
• +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.

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

Jiang Kan is a Lecturer at the Department of Computer Science, National University of Singapore. He earned his Ph.D. in Computer Science from NUS in 2023, following an MComp (2017) and B.Sc. (1994) from NUS and Shanghai Jiao Tong University respectively. His teaching portfolio includes courses like Introduction to Computing , Introduction to Programming , Database Systems and Management , and Systems Programming . Education: Ph.D., Computer Science, National University of Singapore, 2023 M.Comp., National University of Singapore, 2017 B.Sc., Shanghai Jiao Tong University, 1994 Research Focus: Jiang Kan specializes in sports analytics, integrating computer vision and probabilistic modeling to analyze sports strategies, player dynamics, and broadcasting data. His work includes tennis and soccer strategy analysis , event recognition in sports videos , and injury prediction models . Publication Trends: Recent articles (2023-2025) explore hybrid approaches combining deep learning with probabilistic model checking for sports analytics. Key contributions include automated court detection , fine-grained event analysis , and dynamic team strategy modeling in tennis and soccer. Teaching: He teaches foundational and advanced courses in programming, computer organization, software engineering, and databases to both full-time and part-time students.

• Computer Science
• Artificial Intelligence
• Sports Analytics
• +4 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

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