Green AI Workshop

Dr. Yonggang Wen is a Professor and President’s Chair in Computer Science and Engineering at Nanyang Technological University (NTU), Singapore. He also serves as the Associate Vice President (Capability Building) at NTU Singapore. Previously he served as the Associate Dean (Research) at College of Engineering (2018-2023), the acting Director for Nanyang Technopreneurship Center (NTC) (2017-2019) and the Assistant Chair (Innovation) at the School of Computer Science and Engineering (2016-2018), at NTU Singapore. He received his PhD degree in Electrical Engineering and Computer Science (minor in Western Literature) from Massachusetts Institute of Technology (MIT), Cambridge, USA, in 2008. Dr. Wen has published over 300 papers in top journals and prestigious conferences. His systems research has gained global recognitions. His work in Multi-Screen Cloud Social TV has been featured by global media (more than 1600 news articles from over 29 countries) and received ASEAN ICT Award 2013 (Gold Medal). His work on Cognitive Digital Twin for Data Centre, has won the 2015 Data Centre Dynamics Awards – APAC (the ‘Oscar’ award of data centre industry), 2016 ASEAN ICT Awards (Gold Medal), 2020 IEEE TCCPS Industrial Technical Excellence Award, 2021 W.Media APAC Cloud and Datacenter Technology Leader Award, and 2022 Singapore Computer Society Digital Achiever Tech Leader Award.  He was the winner of 2019 Nanyang Research Award and the sole winner of 2016 Nanyang Awards for Innovation and Entrepreneurship, both of which are the highest recognition at NTU. He is a co-recipient of multiple Best Paper Awards from top journals, including 2019 IEEE TCSVT and 2015 IEEE Multimedia, and at international conferences, including 2016 IEEE Globecom, 2016 IEEE Infocom MuSIC Workshop, 2015 EAI Chinacom, 2014 IEEE WCSP, 2013 IEEE Globecom and 2012 IEEE EUC. He is the Editor in Chief of IEEE Transactions on Multimedia (TMM), serves or has served on editorial boards for multiple IEEE and ACM transactions, and was elected as the Chair for IEEE ComSoc Multimedia Communication Technical Committee (2014-2016). His research interests include cloud computing, green data center, big data analytics, multimedia network and mobile computing. He is a Fellow of IEEE and Singapore Academy of Engineering, and an ACM Distinguished Member.

Lee Gim Hee is currently an Associate Professor at the Department of Computer Science at the National University of Singapore (NUS), where he heads the Computer Vision and Robotic Perception (CVRP) Laboratory. He is also affiliated with the NUS Graduate School for Integrative Sciences and Engineering (NGS), and the NUS Institute of Data Science (IDS). Prior to NUS, he was a researcher at Mitsubishi Electric Research Laboratories (MERL), USA. He did his PhD in Computer Science at ETH Zurich under the supervision of Prof. Marc Pollefeys, and received his B.Eng with first class honors and M.Eng degrees from the Department of Mechanical Engineering at NUS. Before his PhD, he worked at DSO National Laboratories in Singapore as a Member of Technical Staff. He is currently an associate editor of IJCV. He has served or will serve as an Area Chair for BMVC, 3DV, CVPR, ICCV, WACV, ECCV, ICLR, IJCAI and NeurIPS, and was or will be part of the organizing committee as one of the Program Chairs for 3DV 2022 and the Demo Chair for CVPR 2023.

Dr. Geng Xue is a research staff member specializing in model compression, with a solid background in machine learning and computer science. Her primary focus is on developing techniques to optimize and compress deep learning models. Dr. Xue's expertise lies in implementing cutting-edge methods such as pruning, quantization, and knowledge distillation. These methods effectively reduce the size and computational complexity of large-scale models. Her research aims to strike a delicate balance between model size and performance, enabling efficient deployment on devices with limited resources.

Currently, Dr. Xue holds the position of I2R Principal Investigator for the AME-programmatic program "hardware-software co-optimization for deep learning." Additionally, she serves as a Co-Investigator for Work Package 4 in the MTC programmatic fund, focusing on "Towards Realistic Deep Learning for 3D Vision." Through her work, Dr. Xue contributes to advancements in model compression and deep learning, working towards more practical and efficient solutions. Her expertise and involvement in various programs make her a valuable asset in the field of machine learning research.

Weng-Fai Wong received the BSc degree from the National University of Singapore, in 1988, and the DrEngSc degree from University of Tsukuba, Japan, in 1993. He is currently an associate professor at the Department of Computer Science, National University of Singapore. His research interests include computer architecture, compilers, and high-performance computing. He is a senior member of the IEEE.

Alex Jinpeng Wang is currently a second-year PHD Student in National University of Singapore (NUS) and supervised by Prof. Mike Zheng Shou.  His research interests are in Multi-modality Learning and Data-centric AI. Now he mainly focus on very large-scale vision-language pre-training (VLP) and dataset compression.

Jian Feng received his PhD degree in Physics from Massachusetts Institute of Technology in 2018. He is currently a research scientist with the Institute of High Performance Computing, A*STAR, Singapore. His current research interests include near-term quantum algorithms, quantum optimization, quantum many-body systems, as well as quantum machine learning.

Dr. Liangli Zhen is a research scientist and group manager at the Institute of High Performance Computing (IHPC), Agency for Science, Technology and Research (A*STAR), Singapore. He leads the Efficient AI research group to improve data efficiency and computation efficiency in machine learning. His research interests include representation learning, neural architecture search, and evolutionary multi-objective optimisation.

Dr. Wang Bo is an Assistant Professor at Singapore University of Technology and Design. Her research interests focus on accelerating edge AI applications in the domain of VLSI Circuits and Systems spanning Integrated Circuits, Computer Architecture and Design Automation. She has authored and co-authored many papers in energy-efficient computing architectures and circuits. She also served as an editorial board or TPC member for various journals and conferences. 

Dr. Wang received her Ph.D. degree from Nanyang Technological University in 2015. Prior to joining SUTD, she was a research fellow, working with Prof. Peh Li-Shiuan at the National University of Singapore and a staff engineer at MediaTek Singapore. She was the recipient of IEEE Circuits & Systems Seoul Chapter Award. She is an IEEE senior member.

Joey Zhou is currently a principal scientist II, Investigator and group manager with A*STAR Centre for Frontier AI Research (CFAR), Singapore. He is also holding an adj. Assoc. Prof. at National University of Singapore (NUS). Before working at CFAR, he was a senior research engineer with SONY US Research Center in San Jose, USA.  Dr. Zhou received a Ph.D. degree in computer science from Nanyang Technological University (NTU), Singapore. His current interests mainly focus on improving the efficiency and robustness of machine learning algorithms. On these areas, he has published more than 100 papers and received the Best Student Paper Nomination at European Conference on Computer Vision (ECCV'16), Best Paper Award at International Joint Conference on Artificial Intelligence (IJCAI) workshops, and Best Poster Award and runner-up prize at International Conference on Computer Vision (ICCV’19) on HANDS workshop and its competition, respectively.

Dr. Zhou regularly organizes workshops/tutorials at top-tier international conferences like CVPR, IJCAI, ICDCS, etc. He is serving as an Associate Editor for IEEE Transactions on Emerging Topics in Computational Intelligence (TETCI) and IEEE Access, IET Image Processing, and Area Chairs in top machine learning conferences like ICLR, ICML, NeurIPS etc.      

In addition to academic achievements, a lot of his developed AI algorithms have been successfully translated in the real-world applications. For example, his developed object detection method is integrated into AI-assist prohibited item X-ray machines with more than 95% detection rate which are deployed in Singapore military training base.