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Anand BhojanView profile

Associate Professor

• Distributed Computing
• Wireless Networks
• IoT
• +13 more

Anand Bhojan is an Associate Professor (Educator Track) at the Department of Computer Science, School of Computing, National University of Singapore (NUS). He is a member of the Communication and Internet Research Lab and serves on the Graduate Studies Committee. Dr. Bhojan is also the founder of Anuflora Systems and Virtual and Augmented Reality Labs (www.varlabs.org), and serves as Associate Editor of Computers and Electrical Engineering Journal, Elsevier, and Vice President of International Researchers Club, Singapore. Dr. Bhojan earned his Ph.D. in Computer Science & Engineering from NUS in 2011, where his thesis was nominated for the Best PhD Thesis Award. He also holds a Professional Master's in Computer Applications from Bharathidasan University (1999), a Bachelor's degree in Computing with Gold Medal (University topper) from Bharathiar University (1994), and a Postgraduate Certificate in Teaching Higher Education from University of Sheffield, UK (2003). His research spans multiple domains including Distributed Computing and Wireless Networks (IoT, Security, Blockchain), Artificial Intelligence (Generative AI, FinTech), and Entertainment Computing with focus on Games, VR/AR/Metaverse technologies. Dr. Bhojan leads the Metaverse Foundry research group which focuses on content generation for games & XR simulations across multiple domains including entertainment, healthcare, and architecture, while also experimenting with innovative teaching methods for entertainment media technologies. Dr. Bhojan's recent research has pioneered hybrid rendering techniques that strategically combine ray tracing and rasterization to create more realistic video game graphics without compromising performance. His work addresses critical challenges in real-time rendering, particularly in depth of field and motion blur effects, with the goal of making Hollywood-quality graphics accessible on a wider range of hardware. Earlier work focused on energy efficiency in mobile gaming, including power management techniques and latency optimization for cloud gaming. Among his notable achievements: 2012 Nominated for Best PhD Thesis Award (Wang Gungwu Medal & Prize), NUS 2011 Dean's Graduate Research Achievement Award (PhD), SoC, NUS 2006 Best R&D Project award from TOTE Board, Singapore 1995 Gold medal for first Rank (out of 4000) in Computing, Bharathiar University Dr. Bhojan has served as Organizing Chair and Program Chair for multiple international conferences and has delivered keynote talks at IEEE/ACM International Conferences. He teaches courses including Computer Networks Practice, Game Development, Interaction Design for Virtual and Augmented Reality, and Game Development Project. He leads the Metaverse Foundry research group and the Virtual and Augmented Reality Labs, where undergraduate and graduate students have won multiple research and innovation awards. His research bridges entertainment, education, and emerging technologies with practical applications in making immersive experiences more accessible across different hardware capabilities while maintaining energy efficiency.

Zhiyong HuangView profile

Associate Professor

• Data Analytics
• Machine Learning
• Computer Vision
• +6 more

Zhiyong Huang is an Associate Professor at the National University of Singapore (NUS) School of Computing. He holds multiple leadership roles, including Deputy Director of the NUS Business Analytics Centre, Director of the Computing Translational Research & Development (C-TReND) Centre, and Assistant Dean (Industry Relations). He is also a Senior Principal Investigator at the NUS Chongqing Research Institute. Education: PhD in Computer Science from École Polytechnique Fédérale de Lausanne (EPFL), MEng and BEng in Computer Engineering from Tsinghua University. Leadership: Senior Member of ACM and IEEE, Pioneer Member of ACM SIGGRAPH, and Chair of the Singapore ACM SIGGRAPH Chapter. Research Interests: His work spans Data Analytics, Machine Learning, Computer Vision, Human-Robot Interaction, and Computer Graphics. Key projects include the NUS Digital Twin initiative and secure data analytics pipelines. Article Trends: Recent publications focus on time series generation, cryptocurrency benchmarks, medical image registration, and phishing detection. These works integrate machine learning, computer vision, and multimodal systems. Scientific Awards: Finalist, World Technology Summit & Awards (Entertainment, 2010) Bronze, National Science and Technology Progress Award (1992) Tsinghua 12.9 Distinguished Young Teacher Award (1989) Grants & Service: Extensive involvement in Singapore's IT Standards Committee, review panels for EDB SIIRD projects, and editorial roles. He has served as PC co-chair, local chair, and reviewer for numerous conferences and journals.

Tulika MitraView profile

Professor

• Hardware-Software Co-design
• Real-Time Embedded Systems
• Energy-Efficient Computing
• +7 more

Professor Tulika Mitra is the Dean of the School of Computing and Vice Provost (Special Projects) at the National University of Singapore (NUS). She holds the Provost’s Chair Professor in the Department of Computer Science and has been instrumental in shaping academic policies and strategic initiatives at NUS since joining in 2001. PhD in Computer Science, Stony Brook University (2000) M.E. in Computer Science, Indian Institute of Science (1997) B.E. in Computer Science, Jadavpur University (1995) Her research focuses on hardware-software co-design for energy-efficient computing systems, particularly in real-time embedded systems, heterogeneous architectures, and AI accelerators. She leads major research programs such as the NRF Competitive Research Programme on Low-Power Edge Accelerators and the MOE Tier-3 Programme on Green AI , collaborating with industry leaders like ARM, AMD, and Meta. Her recent publications highlight innovations in CGRA optimization , sparse attention mechanisms , photonic-digital hybrid architectures , and low-power ML inference . These works often integrate compiler techniques, architectural design, and real-time constraints for edge computing applications. Scientific Awards : ESWEEK Test-of-Time Award (2022), ACM SIGDA Distinguished Service Award, IEEE CEDA Outstanding Service Recognition Award, Teaching Excellence Award (2006), and multiple best paper recognitions. Education Leadership : Spearheaded the Computer Engineering (CEG) Programme at NUS, a joint initiative between Engineering and Computing. As a mentor , she has supervised over 25 PhD students , many now in prominent academic or industrial roles. Her research group eCO Lab focuses on embedded computing challenges, while her grant collaborations include projects on 5G base stations, reconfigurable architectures, and IoT-optimized SoCs.

Yang YouView profile

Professor

• Machine Learning
• High-Performance Computing
• Parallel/Distributed Systems
• +3 more

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.

David HsuView profile

Professor

• Robotics
• Artificial Intelligence
• Machine Learning
• +2 more

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.

Prasanna Karthik VAIRAMView profile

Lecturer

• Security
• Systems
• Networking
• +1 more

Prasanna Karthik VAIRAM is a Lecturer at the National University of Singapore , affiliated with the Department of Computer Science . His research focuses on Security, Systems, and Networking within computer science. Ph.D. in Computer Science and Engineering from Indian Institute of Technology Madras M.Tech in Computer Science and Engineering from Indian Institute of Technology Bombay (2011) B.Tech in Computer Science from Anna University (2009) He previously worked at Intel, Bangalore (2011–2014) on functional modeling of graphics processors. Courses taught include CS4238 (Computer Security Practice), IT5007 (Software Engineering), and TCX3232 (Network and Cloud Security). Scientific Awards: Teaching Excellence Award (2024) - NUS Computing

Lu ShijianView profile

Associate Professor

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

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.

Steven HalimView profile

Associate Professor

• Algorithms & Theory
• Combinatorial Algorithms
• Graph Theory & Algorithms
• +13 more

Steven Halim is an Associate Professor (Educator Track) in the Department of Computer Science at the School of Computing, National University of Singapore (NUS). He has been a full-time educator since 2007, teaching a wide range of courses including Data Structures and Algorithms, Competitive Programming, and Design and Analysis of Algorithms. He currently serves as the Director of the Centre for Nurturing Computing Excellence (CeNCE) and is a Fellow of the NUS Teaching Academy. Ph.D. in Computer Science, National University of Singapore B.Sc. in Computer Science, National University of Singapore His research and teaching interests focus on algorithms, competitive programming, visualization, and optimization. He is renowned for creating VisuAlgo , an interactive online platform that visualizes data structures and algorithms, used by students and educators worldwide. He is also the co-author of the widely acclaimed book "Competitive Programming" , now in its fourth edition, which is a key resource for programming contest preparation. His recent scholarly work centers on pedagogical innovations in computer science education, particularly algorithm visualization and competitive programming methodologies. Earlier publications from his PhD work focused on stochastic local search, metaheuristics, and algorithm tuning through visualization. The articles span topics from educational technology to combinatorial optimization, reflecting a transition from research in algorithm engineering to leadership in computing education. Commendation Medal (Pingat Kepujian), National Day Awards 2018 NUS Annual Teaching Excellence Award (ATEA) 2014/15, 2017/18, 2018/19 (with Honour Roll) Faculty Teaching Excellence Award (FTEA) 2011/12, 2012/13, 2014/15 (with Honour Roll) Best Teaching Assistant Award 2007/08 Steven Halim has advised numerous students through his courses and competitive programming teams. He has served as the head coach for NUS ICPC teams since 2008 and team leader for Singapore IOI teams since 2009, leading them to multiple international medals. He has also held leadership roles in major international competitions, including Deputy Director for IOI 2020 and 2021, and Regional Contest Director for ICPC Asia Singapore 2015 and 2018. He was a Resident Fellow at NUS Sheares Hall for nine years, deeply engaging with student life. He leads the Centre for Nurturing Computing Excellence (CeNCE), where he manages programming competition activities for both NUS and Singapore national teams. His work integrates education, competition, and mentorship, creating a synergistic environment that has significantly elevated Singapore's performance in international informatics olympiads.

Zhao NaView profile

Assistant Professor

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

Dr. Zhao Na is a tenure-track Assistant Professor at the Singapore University of Technology and Design (SUTD), affiliated with the Institute of Sustainable Technology and Design (ISTD). She holds a Ph.D. in Computer Science from the National University of Singapore (NUS), where her thesis on 3D point cloud semantics earned the IMDA Excellence Prize. Her research bridges computer vision and machine learning, focusing on scene understanding, data-efficient learning, and domain generalization. Education: Ph.D. in Computer Science (NUS, 2021); Prior roles include Research Fellow at NUS. Research interests emphasize 3D scene analysis, object detection, semantic segmentation, and robust learning under noisy or limited data. Her work addresses challenges in multi-modal learning, continual learning, and open-world scenarios. Recent projects include geometry-semantics synergy in neural fields and cross-modal augmentation for visual grounding. Publications span top-tier venues like CVPR, ECCV, and ICCV, with a focus on 3D vision and AI. Key contributions include the PCTeacher framework for semi-supervised segmentation and Static-Dynamic Co-Teaching for incremental learning. Scientific Awards: IMDA Excellence Prize (2021). Active grants include a DSO Research Grant (2023–2026) and A*STAR MTC Grant (2023–2026). She leads the SUTD-ZJU Thematic Grant on 3D scene understanding (2022–2024). Laboratory/Team: Research group at ISTD/SUTD focuses on advancing AI-driven 3D perception and scene understanding systems.

Leow Wee KhengView profile

Associate Professor

• Medical Image Analysis
• Computer Vision
• 3D Modeling
• +5 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.).

TAN Tiow SengView profile

Associate Professor

• Computational Geometry
• GPU Computing
• Algorithm Design
• +2 more

TAN Tiow Seng is an Associate Professor at the School of Computing, National University of Singapore . He holds a Ph.D. in Computer Science from the University of Illinois Urbana-Champaign (1993), an M.Sc. in Computer Science from NUS (1988), and a B.Sc. in Mathematics & Computer Science from NUS (1984). Research Interests : Design of geometric algorithms for GPU acceleration Applications in interactive graphics, visualization, and game development Development of robust GPU software for geometric computation Selected Publications demonstrate expertise in Delaunay triangulation, Voronoi diagrams, convex hulls, and GPU-based distance transforms. His team pioneered GPU-accelerated mesh refinement techniques and parallel recurrence optimization. Scientific Awards : NUS/SOC Teaching Excellence Award (1999, 2004, 2022) C. W. Gear Outstanding Graduate Student Award (UIUC, 1992) National University Overseas Graduate Scholarship (1988–1992) Data Processing Managers’ Association Award (1984) Industry Contributions : Holds five US/Singapore patents Chairman/co-founder of G Element Pte Ltd , a graphics/visualization company Served as expert panel member for Media Development Authority (MDA) funding evaluations

Zhaozheng ChenView profile

Researcher

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

Zhaozheng Chen is a Research Scientist at Singapore Management University (SMU), affiliated with the School of Computing and Information Systems (SCIS) and the Department of Computer Science. He holds a Ph.D. in Computer Science from SMU (2020–2023) and a B.Sc. in Computer Science and Technology from Shandong University (2015–2019). His research focuses on computer vision and machine learning, with particular emphasis on weakly-supervised learning, semantic segmentation, and deep learning applications in multi-task frameworks. **Education**: Ph.D. in Computer Science, Singapore Management University (Jan 2020 – Dec 2023; Advisor: Prof. Qianru Sun) B.Sc. in Computer Science and Technology, Shandong University (Sep 2015 – Jun 2019; Advisor: Prof. Liqiang Nie) **Research Interests**: Zhaozheng’s work spans computer vision, machine learning, and deep learning, with recent contributions to weakly-supervised semantic segmentation, class activation maps, and multi-task learning for urban perception. He also explores applications in virtual try-on systems and text classification. **Awards**: He has been awarded the SMU Presidential Doctoral Fellowship (2022/2023 and 2023/2024), the SCIS Dean’s List (2023), and national scholarships for academic excellence. Notably, he secured a Bronze Medal in the ACM-ICPC Asia Regional Contest and a Meritorious Winner title in the Mathematical Contest in Modeling. **Teaching & Work Experience**: He served as a Teaching Assistant for CS 701 (Deep Learning and Vision) at SMU (2021–2022). Prior to his Ph.D., he interned at YouTu Lab, Tencent (Oct 2018 – Jan 2019), working under Dr. Xiaoyong Shen. Currently, he advises under Prof. Qianru Sun’s research group and contributes to open-source projects like ReCAM and LPCAM on GitHub. **Professional Services**: He actively reviews for top conferences including BMVC, ICCV, ECCV, IJCAI, CVPR, and journals such as IJCV, IEEE TPAMI, and ACM TOMM.

• Image and Video Processing
• Multimedia Analysis
• Computer Vision
• +5 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.

• Statistics
• Epidemiology
• Genetics
• +7 more

Maria De Iorio is a Professor at the Yong Loo Lin School of Medicine and holds a joint appointment at the Faculty of Science , both at the National University of Singapore. Her work bridges statistics, epidemiology, and clinical sciences through advanced Bayesian modeling and computational methods. Key research areas: Statistics, Epidemiology, Genetics, Clinical sciences, Medical biochemistry Primary affiliations: Paediatrics department (YLLSoM) and interdisciplinary projects in Science faculty Recent publications focus on extreme value theory, digital numismatics, metabolomic simulations, and maternal-child health Her statistical innovations include: Repulsive mixture models for interpretable clustering Bayesian semi-parametric approaches for longitudinal studies Novel prior distributions for graphical models Application domains span: Pediatric oncology (ALL treatment response modeling) Metabolic syndrome analysis (obesity, diabetes, bone health) Digital humanities (coin distribution patterns, ceramic artifact analysis) Financial forecasting (discrete survival methods for invoice prediction)

Kok Lim LowView profile

Senior Lecturer

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

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