جستجوی استاد راهنمای دانشگاهی

Kian-Lee Tanمشاهده پروفایل

استاد

• Query Processing
• Big Data Analytics
• Database Systems
• +۵ مورد دیگر

Kian-Lee Tan is a Tan Sri Runme Shaw Senior Professor and Professor of Computer Science at the School of Computing, National University of Singapore (NUS). He holds a Ph.D. (1994), M.S. (1992), and B.Sc. (1st Class Honours) from NUS. His academic career spans decades of contributions to database systems and data analytics. Ph.D. in Computer Science, National University of Singapore (1994) M.S. in Computer Science, National University of Singapore (1992) B.Sc. in Computer Science (1st Class Honours), National University of Singapore As a leading researcher in database systems, Tan focuses on query processing and optimization in multiprocessor/distributed systems, database performance, security, and multimedia information retrieval. His work extends to computational biology applications like genome databases and real-time influence analysis on social streams. His recent publications highlight trends in GPU-accelerated graph analytics, trajectory pattern mining, and computational journalism. These works emphasize parallel processing, performance optimization, and social/media data analysis. IEEE Technical Achievement Award (2013) President Science Awards, Singapore (2011) NUS Graduate School Excellent Mentor Award (2010/2011) Outstanding University Researchers Award (1997/1998) Tan has supervised numerous research projects and mentored students contributing to database systems. He secured significant grants including a US$1 million Ripple Foundation grant (2024) for financial technology education. His editorial roles include ACM Transactions on Database Systems and IEEE Transactions on Knowledge and Data Engineering. He leads the FinTech Lab at NUS Computing and has served on the VLDB Endowment Board (2012-2017). His work bridges database foundations with emerging applications in AI, fintech, and computational journalism.

Yang Youمشاهده پروفایل

استاد

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

Lin Weisiمشاهده پروفایل

استاد

• Artificial and Augmented Intelligence
• Computer Science and Engineering
• Electrical and Electronic Engineering
• +۵ مورد دیگر

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.

CHANG Ee Chienمشاهده پروفایل

دانشیار

• Information Security
• Cloud Security
• Adversarial Machine Learning
• +۶ مورد دیگر

CHANG Ee-Chien is an Associate Professor in the Department of Computer Science at the School of Computing, National University of Singapore (NUS). He serves as the Lead Principal Investigator of the National Cybersecurity R&D Laboratory (NCL) and previously served as Deputy Director of the Center for Technology, Robotics, Artificial Intelligence and the Law (TRAIL) from 2019 to 2022. He also chaired the Joint Academic Committee for the Bachelor of Computing in Information Security program from 2016 until April 2023. Dr. Chang received his Ph.D. in Computer Science from New York University in 1998, following his M.Sc. and B.Sc. in Mathematics from the National University of Singapore in 1993 and 1991 respectively. He completed postdoctoral work with DIMACS at Rutgers University and NEC Labs America. His research focuses on information security, multimedia security, and their intersection. His work spans from foundational research in cryptographic techniques for noisy data and image watermarking to contemporary challenges in data privacy, cloud security, and adversarial machine learning. Dr. Chang has published extensively in top-tier security and computer science venues including CCS, EUROCRYPT, USENIX Security, and ACM Multimedia. Analysis of his recent publications reveals a strong emphasis on practical security solutions using hardware features like Trusted Execution Environments, innovative approaches to watermarking using generative models, and addressing emerging threats in machine learning systems. His work bridges theoretical cryptography with real-world security challenges, particularly in cloud infrastructure and privacy-preserving technologies. Active leadership in National Cybersecurity R&D Laboratory Extensive service on program committees for major security conferences Consultancy roles with Huawei, i-Sprint, and Singapore Accreditation Council Media commentary on cybersecurity issues for major Singaporean outlets Dr. Chang has mentored numerous research fellows and students who have gone on to academic and industry positions worldwide. His educational contributions include developing cybersecurity curriculum and innovative teaching methods such as penetration testing using real-world university applications. He has taught core security courses including CS2107 Introduction to Information Security continuously since 2014.

Koteswar Rao Jerripothulaمشاهده پروفایل

استادیار

• Computer Vision
• Artificial Intelligence
• Machine Learning
• +۳ مورد دیگر

Dr. Koteswar Rao Jerripothula is an Assistant Professor in the Department of Electrical Engineering at the Indian Institute of Technology Kanpur (IIT Kanpur), specializing in the SPCOM stream. Previously, he served as an Assistant Professor at Indraprastha Institute of Information Technology Delhi (IIIT-Delhi). He holds a PhD from Nanyang Technological University (Singapore) and a BTech from IIT Roorkee. His research focuses on Computer Vision, Artificial Intelligence, and Multimedia Signal Processing, with applications in healthcare informatics and federated learning. Education: PhD (2017), Nanyang Technological University BTech (2012), Indian Institute of Technology Roorkee Research Interests: Computer Vision and Image Processing Multimedia Computing and Systems Artificial Intelligence and Machine Learning Computational Health and Biomedical AI His Visual Intelligence and Multimedia Signals (VIMS) Lab explores topics like co-saliency detection, federated learning, and light-weight biometrics. The lab seeks students with strong coding and communication skills. Contact: vims.iitk@gmail.com.

Kai Fong Ernest Chongمشاهده پروفایل

استادیار

• Combinatorics
• Commutative Algebra
• Artificial Intelligence
• +۵ مورد دیگر

Kai Fong Ernest Chong is an Assistant Professor in the Information Systems Technology and Design (ISTD) pillar at Singapore University of Technology and Design (SUTD). He also served as an adjunct assistant professor at Nanyang Technological University's Division of Mathematical Sciences. His research focuses on combinatorics, commutative algebra, and artificial intelligence, particularly in algebraic machine reasoning and robust AI systems. He leads SUTD's thrust on the fundamentals of AI systems and has secured over SGD 8.3 million in research grants as principal investigator (PI) or co-investigator (Co-I). Ernest holds a PhD in Mathematics from Cornell University (2015) under Edward Swartz. He has extensive teaching experience, including courses on algorithms, discrete mathematics, and probability. His work includes pioneering algebraic machine reasoning, connecting commutative algebra to AI, and developing frameworks for federated learning and robustness against data noise. Notable achievements include a 2023 breakthrough in algebraic machine reasoning surpassing human performance in IQ test tasks and a 2003 National Science Talent Search Grand Prize for his work on twin primes. He supervises numerous PhD, master’s, and postdoctoral researchers and actively collaborates with industry partners through projects like ASTRALIS and Alpha-DRACONIS.

Zhang Tianweiمشاهده پروفایل

دانشیار

• Generative AI Safety
• Deep learning security
• Robotics and autonomous driving security
• +۲ مورد دیگر

Associate Professor at Nanyang Technological University's College of Computing and Data Science, serving as Deputy Director of the Cyber Security Research Centre @ NTU (CYSREN) and Associate Director of the NTU Centre Computational Technologies for Finance (CCTF). His research focuses on building trustworthy, efficient, and intelligent systems with emphasis on security and privacy across AI, robotics, and cloud infrastructures. Educational background: Bachelor of Physics, Peking University, 2011 Ph.D. in Electrical Engineering, Princeton University, 2017 Research spans five core domains: Generative AI Safety (vulnerability identification, safety testing, misuse detection), Deep learning security (adversarial examples, backdoor attacks, privacy protection), Robotics security (perception system attacks, safety testing), Machine learning optimization (workload scheduling, acceleration), and Computer architecture security (side-channel defenses, cloud security). His work bridges theoretical security with practical system implementations across diverse applications. Recent publications (2024-2026) reveal intense focus on securing generative AI systems, particularly text-to-image models and large language models, with significant contributions to red teaming methodologies, backdoor attack mitigation, and multimodal security. Emerging trends show expanding research into autonomous vehicle security and privacy-preserving machine learning with cryptographic techniques. Key awards include: Distinguished Artifact Award (CCS 2024) Stamatis Vassiliadis Best Paper Award Nominee (FPL 2024) Outstanding Paper Award (ACL 2024) Distinguished Artifact Award (Usenix Security 2024) Actively supervises PhD students and research staff while leading multiple high-impact grants: Ongoing: NRF CREATE Quantum Security (2025-2029), Continental NTU Corp Lab Automotive HPC (2025-2028), CRPO EV Charging Security (2025-2027) Completed: MoE AcRF Tier2 IP Protection (2022-2025), NTU S-Lab Efficient GPU Scheduler (2020-2025) Leads research within CYSREN and TAICeN (Trustworthy AI Centre NTU), directing interdisciplinary teams that investigate security threats across AI deployment stacks while developing practical defenses for real-world systems.

Chua Tat Sengمشاهده پروفایل

استاد

• Multimedia Information Retrieval
• Social Media Analytics
• Unstructured Multimodal Data Analytics
• +۴ مورد دیگر

Professor Chua Tat Seng is a distinguished academic at the National University of Singapore's School of Computing, serving as KITHCT Chair Professor and Director of the NUS-Tsinghua Extreme Search Center (NExT). He also holds Distinguished Visiting Professorships at Tsinghua and Zhejiang Universities in China. PhD in Computer Science (University of Leeds, 1983) Founding Dean of School of Computing (1998-2000) Co-founded ViSenze and 6Estates technology startups His research focuses on unstructured multimodal data analytics, with particular emphasis on multimedia information retrieval, social media analytics, recommendation systems, and trustworthy AI. He has pioneered work in computational wellness and fintech applications, establishing the Lab for Media Search and leading NExT++ research initiatives. Over 300 publications in leading venues (CVPR, SIGIR, WWW, AAAI) Recipient of ACM SIGMM Technical Achievement Award (2015) Supervised 37 PhD students since 2004 Editorial leadership in ACM Transactions and IEEE Multimedia Recent work explores multimodal LLMs, knowledge editing techniques (AlphaEdit), and 3D generation frameworks, reflecting his commitment to advancing web intelligence and user empowerment.

OOI Wei Tsangمشاهده پروفایل

دانشیار

• Interactive Media Streaming
• Computer Networking and Distributed Systems
• Multimedia Middleware and Applications
• +۱۰ مورد دیگر

Associate Professor OOI Wei Tsang is affiliated with the National University of Singapore's School of Computing, Department of Computer Science. He co-directs the Image & Pervasive Access Lab (IPAL) and holds a PhD in Computer Science from Cornell University (2001) and a B.Sc. in Computer & Information Sciences from NUS (1996). Current Positions: Associate Professor at NUS School of Computing Education: PhD (Cornell), B.Sc. (NUS) Labs: Co-director, IPAL Lab His research focuses on interactive multimedia systems, particularly volumetric video streaming, cloud gaming, augmented reality, and human-AI collaboration. He has pioneered queuing theory-based approaches for DASH rate adaptation and developed assistive drone technologies for visually impaired individuals through the DroneBuddy project. Recent publications demonstrate expertise in streaming optimization, wearable health monitoring, and conversational AI. His work has been recognized with multiple teaching awards and competitive research accolades including the DASH-IF Excellence in DASH Award (Runner Up). He teaches CS2030S Programming Methodology II and has supervised students contributing to video streaming startups like Atlastream.

Robert H Dengمشاهده پروفایل

استاد

• Applied cryptography
• Data security and privacy
• Mobile and wireless security
• +۵ مورد دیگر

Professor Robert H. Deng is a distinguished academic and researcher at Singapore Management University's School of Computing and Information Systems, where he serves as Professor of Computer Science and Deputy Dean for Faculty & Research. With a PhD from Illinois Institute of Technology (1985), he has established himself as a leading authority in cybersecurity, data privacy, and applied cryptography. His research interests span applied cryptography, data security and privacy, mobile and wireless network security, trusted computing, and system security. Professor Deng has published extensively in top-tier security venues, with over 600 publications listed in DBLP. His work bridges theoretical foundations with practical applications, particularly in the domains of IoT security, blockchain systems, and privacy-preserving technologies. Professor Deng has received numerous prestigious awards, including the National Day Award (Public Administration Medal Silver) in 2020, the AXA Chair Professor of Cybersecurity (2017-2025), and the Lee Kuan Yew Fellow for Research Excellence at SMU in 2006. His recent publications demonstrate continued leadership in emerging areas like post-quantum cryptography, federated learning security, and hardware-assisted security systems. His research group has produced significant work on secure authentication protocols, privacy-preserving data analytics, and robust cryptographic systems for real-world applications. National Day Award, Public Administration Medal (Silver), 2020 AXA Chair Professor of Cybersecurity, AXA Research Fund, 2017-2025 Distinguished & Best Paper Awards at NDSS, ESORICS, IEEE ICPADS, etc. Asia-Pacific Information Security Leadership Achievements (ISLA), 2010 Lee Kuan Yew Fellow for Research Excellence, SMU, 2006 University Outstanding Researcher, National University of Singapore, 1999 As a research advisor, Professor Deng has mentored numerous students including SUN Bing. His active participation in the research community is evidenced by recent keynotes at major conferences including DSPP 2024 on post-quantum cryptography and ASIACCS 2024 on client-side encryption. His research group maintains strong industry connections and receives significant funding for cutting-edge security research.

Jun Luoمشاهده پروفایل

دانشیار

• Mobile and Pervasive Computing
• Wireless Networking
• Machine Learning
• +۱۲ مورد دیگر

Jun Luo is an Associate Professor in the School of Computer Science and Engineering at Nanyang Technological University (NTU), Singapore. He earned his PhD in Computer Science from EPFL under the supervision of Prof. Jean-Pierre Hubaux and completed postdoctoral research at the University of Waterloo. He joined NTU in 2008 as an Assistant Professor and was promoted to Associate Professor in 2014. He served as Deputy Director of the Centre for Multimedia and Network Technology from 2010 to 2013. Education: PhD in Computer Science, Swiss Federal Institute of Technology in Lausanne (EPFL), 2006 MS in Electrical Engineering, Tsinghua University, 2000 BS in Electrical Engineering, Tsinghua University, 1997 Research Interests: Jun Luo's research focuses on mobile and pervasive computing, wireless networking, machine learning, and applied operations research. His primary research thrusts include: Contact-free Sensing Driven by Deep Learning : Leveraging RF, acoustic, and visible light signals for human activity recognition, respiration monitoring, and localization without wearable devices. Visible Light Communication and Sensing : Exploring LED-camera systems for data transmission, occupancy inference, and indoor broadcasting. Indoor and Outdoor Localization and Tracking : Developing systems using WiFi, geomagnetism, and crowdsourced data for precise positioning. Machine Learning for Mobile Networking : Applying deep learning and optimization to improve wireless network performance, mobile crowdsensing, and resource allocation. Publication Trends: His recent publications (2021–2023) demonstrate a strong focus on deep learning-enhanced sensing using RF and acoustic signals, particularly for health monitoring (e.g., respiration, heartbeat), multi-person tracking, and privacy-preserving techniques. He frequently collaborates with researchers in signal processing, computer vision, and networking, publishing in top venues like IEEE Transactions on Mobile Computing, MobiCom, and INFOCOM. His work emphasizes practical deployment on commodity devices and integration of sensing with communication systems. Scientific Recognition: IEEE Fellow Advising and Grants: Dr. Luo has advised numerous PhD and Master's students, as evidenced by the extensive list of student co-authors across his publications. He has led significant research projects in wireless sensor networks, mobile computing, and IoT systems, likely supported by competitive grants from Singaporean and international funding agencies. His role as Deputy Director of a research center indicates leadership in managing research teams and collaborative efforts. Labs and Teams: He leads a research group focused on mobile and distributed computing, deep learning, and computer vision. His team actively publishes in top-tier conferences and journals, working on projects involving RF sensing, acoustic platforms, visible light communication, and privacy-aware systems. The group collaborates with researchers both within NTU and internationally, particularly in Canada and China.

• Distributed Systems
• Operating Systems
• Data Center Networks
• +۳ مورد دیگر

Jialin Li is the Sung Kah Kay Assistant Professor at the School of Computing , National University of Singapore (NUS). They earned a PhD from the University of Washington under the advisement of Dan Ports and a bachelor's degree from the University of Michigan . Their research focuses on distributed systems and operating systems, particularly on co-designing systems with data center networks, data plane operating systems, and decentralized infrastructure. Research Interests : Distributed systems, network ordering, consensus algorithms, in-network processing, decentralized infrastructure, and programmable hardware. Awards : OSDI '14 Jay Lepreau Best Paper Award, NSDI '15 Best Paper Award. Students : Mentors PostDocs (Chaoyi Ruan), Graduate Students (Inho Choi, Yunfan Li, Ziji Shi, etc.), and Undergraduate Students (Mohsen Ghasemi, Akshaye Shenoi, etc.). Service : Conference Organizer (APSys '25 Program Co-Chair), Technical Committee for EuroSys, SOSP, NSDI, and others.

Natarajan Prabhuمشاهده پروفایل

مدرس ارشد

• Artificial Intelligence
• Machine Learning
• Computer Vision
• +۷ مورد دیگر

Natarajan Prabhu is a Senior Lecturer on the Educator Track at the Department of Computer Science, National University of Singapore (NUS), Faculty of Computing. He also serves as the Director of the Center for Computing for Social Good and Philanthropy, highlighting his leadership in technology for societal impact. Education: Ph.D. in Computer Science, National University of Singapore M.E. in Computer Science (Gold Medalist, University First Rank) B.Tech. in Information Technology His research focuses on Artificial Intelligence, Machine Learning, Computer Vision, and Multimedia Systems , particularly in multi-camera surveillance, fairness in observation, decision-theoretic coordination, and active perception . His work bridges intelligent systems with ethical considerations in automated surveillance. He teaches foundational courses such as CS2100 (Computer Organisation), CS2103/CS2103T (Software Engineering), and IT1244 (Artificial Intelligence: Technology and Impact). The analysis of his publications reveals a strong thematic focus between 2008 and 2015 on intelligent, decision-theoretic approaches to multi-camera surveillance, emphasizing fairness, scalability, and real-time coordination. His early work on whiteboard documentation also reflects interest in practical, human-centered computing applications. Scientific Awards: Annual Teaching Excellence Award (ATEA) - 2023 Annual Teaching Excellence Award (ATEA) - 2024 Faculty Teaching Excellence Award (FTEA) - 2023 Faculty Teaching Excellence Award (FTEA) - 2024 Natarajan Prabhu is a dedicated educator and researcher with significant contributions to teaching excellence and ethically informed AI systems. His leadership in the Center for Computing for Social Good indicates active engagement in grants and initiatives promoting technology for philanthropy. While specific grants are not listed, his directorship implies oversight of funded projects and research teams. He has mentored research at the doctoral level, as seen in his PhD forum publications. He leads the Center for Computing for Social Good and Philanthropy , which likely involves interdisciplinary teams working on AI for social impact, ethical computing, and community-driven technology solutions.

Tsuhan Chenمشاهده پروفایل

استاد

• Artificial Intelligence
• Computer Vision
• Pattern Recognition
• +۳ مورد دیگر

Tsuhan Chen is a Distinguished Professor and Deputy President (Research and Technology) at the National University of Singapore (NUS), serving as Chief Scientist of AI Singapore and Co-Chair of the SIA-NUS Digital Aviation Corporate Laboratory. Previously, he served as Dean of the College of Engineering at Nanyang Technological University and held professorships at Cornell University and Carnegie Mellon University. Education: Ph.D. in Electrical Engineering, California Institute of Technology M.S. in Electrical Engineering, California Institute of Technology B.Sc. in Electrical Engineering, National Taiwan University A globally recognized expert in pattern recognition, computer vision, and machine learning, Prof. Chen's research centers on media artificial intelligence including computer vision, pattern recognition, multimedia coding/retrieval, and biometric authentication. His work has produced over 300 technical publications and nearly 30 US patents. His recent publications reveal dominant themes in computer vision and multimedia processing, with significant contributions to image captioning, semantic segmentation, emotion recognition, and medical imaging through advanced techniques like deep learning, tensor regularization, and multimodal fusion. Scientific Awards: Charles Wilts Prize (1993) NSF CAREER Award (2000-2003) Benjamin Richard Teare Teaching Award (2006) Eta Kappa Nu Award (2007) Michael Tien Teaching Award (2014) Robert M Janowiak Award (2017) Fellow of IEEE Fellow of Institute of Engineers, Singapore Prof. Chen has secured substantial research funding including the NSF CAREER Award and directed the Advanced Multimedia Processing Laboratory at Cornell. He currently leads national AI initiatives through AI Singapore and has championed interdisciplinary research programs aligned with Singapore's RIE2020 strategy.

Roger Zimmermannمشاهده پروفایل

استاد

• Multimedia and Distributed Systems
• Multimedia and Mobile Networking
• Spatio-temporal Data Management
• +۸ مورد دیگر

Roger Zimmermann is a Full Professor at the School of Computing, National University of Singapore (NUS), where he is also a Co-PI at the Grab-NUS AI Lab and leads the Location AI project. He previously served as Deputy Director of the NUS Smart Systems Institute (SSI) and Co-Director of the Centre of Social Media Innovations for Communities (COSMIC), both funded by Singapore’s National Research Foundation (NRF). Before joining NUS, he was a Research Area Director and Research Assistant Professor at the University of Southern California (USC). Ph.D. in Computer Science, University of Southern California (1998) M.S. in Computer Science, University of Southern California (1994) His research focuses on multimedia systems , spatio-temporal data management , streaming media architectures (especially DASH), machine learning applications , AR/VR , and location-based services . He leads the Media Management Research Lab (MMRL) at NUS, which conducts cutting-edge work in distributed multimedia and intelligent systems. His work combines theoretical depth with real-world applications in urban computing, smart mobility, and immersive media. The recent publications reflect a strong trend toward multimodal learning , spatio-temporal AI , adaptive streaming , and urban intelligence . His team explores zero-shot learning, 3D scene understanding, traffic forecasting, and open-vocabulary audio-visual segmentation, often leveraging foundational models and deep neural architectures. There is a clear emphasis on real-time, scalable systems for smart cities and immersive experiences. Dr. Zimmermann has received numerous accolades, including: DASH-IF Excellence in DASH Award (multiple years) Best Paper Awards at ACM SIGSPATIAL, IEEE ICME, and ACM MMSys Silver Award at ACM MMSys 2020 Grand Challenge IEEE Communications Society Best Editor Award (2017) ACM Distinguished Member (2017) Top 1% Publons Reviewer in Computer Science (2018) He has advised numerous students and led major research initiatives funded by MOE, NRF, A*STAR, NSF, and industry partners like Seagate, Intel, and HP. He has served as General Chair for IEEE MIPR 2023, ACM Multimedia 2020, and IEEE ISM 2015, and as TPC Co-Chair for several top-tier conferences. His editorial roles include Associate Editor for IEEE Transactions on Multimedia (TMM), ACM TOMM, and IEEE OJ-COMS. He leads the Media Management Research Lab (MMRL) , which focuses on intelligent multimedia systems, spatiotemporal data mining, and immersive media technologies. The lab develops scalable solutions for real-world challenges in urban computing, smart transportation, and interactive media.