Biography [detail]

Ming-Hsuan Yang is a Professor in Electrical Engineering and Computer Science at University of California, Merced. He received the PhD degree in computer science from the University of Illinois at Urbana-Champaign in 2000. He studied Computer Science and Power Mechanical Engineering at the National Tsing-Hua University, Taiwan; Computer Science and Brain Theory at the University of Southern California; and Artificial Intelligence and Operations Research at the University of Texas at Austin. He was a Senior Research Scientist at the Honda Research Institute (formerly Honda Fundamental Research Labs) working on vision problems related to humanoid robots. In 1999, he received the Ray Ozzie fellowship for his research work. His research interests include computer vision, pattern recognition, artificial intelligence, robotics, and machine learning.

Yang serves as a Program Chair of IEEE International Conference on Computer Vision (ICCV) in 2019, Program Chair of Asian Conference on Computer Vision (ACCV) in 2014, and General Chair of ACCV 2016. He currently serves as an Associate Editor-in-Chief of IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), and Associate Editor of International Journal of Computer Vision (IJCV). He served as a Editor-in-Chief of CVIU from 2022 to 2023; Associate Editor-in-Chief of CVIU from 2016 to 2022; Associate Editor of CVIU from 2012 to 2016; Associate Editor of PAMI from 2007 to 2011; Associate Editor of Image and Vision Computing (IVC) from 2009 to 2022; and Associate Editor of Journal of Artificial Intelligence (JAIR) from 2015 to 2020.

He serves as a Senior Area Chair or Area Chair for several conferences including IEEE Conference on Computer Vision and Pattern Recognition (CVPR) in 2008, 2009, 2014, 2018, 2021, 2022, and 2023; IEEE International Conference on Computer Vision (ICCV) in 2011, 2015, 2017, 2021, and 2023; European Conference on Computer Vision (ECCV) in 2014, 2016, 2018, 2020, 2022, and 2024; Asian Conference on Computer (ACCV) in 2009, 2010, 2012, 2020, 2022, and 2024; British Machine Vision Conference (BMVC) 2018, 2019, 2020, 2021, 2022, and 2023; Neural Information Processing Systems (NeurIPS) 2021, 2022, 2023, and 2024; International Conference on Learning Representations (ICLR) 2022, 2023, and 2024; International Conference on Machine Learning (ICML) 2023 and 2024; AAAI National Conference on Artificial Intelligence (AAAI) in 2020, 2011, 2022, 2023, and 2024; International Joint Conference on Artificial Intelligence (IJCAI) 2019, 2020, 2021, 2022, 2023, and 2024 ; IEEE International Conference on Automatic Face and Gesture Recognition (FG) in 2011 and 2013; IEEE Winter Conference on Applications and Computer Vision (WACV) in 2014, 2016, 2018, and 2022.

Yang received several paper awards including the Best Paper at ICML 2024; Longuet-Higgins Prize at CVPR 2023; Best Paper Honorable Mentio at CVPR 2018; Best Student Paper Honorable Mention at ACCV 2018; Best Paper Honorable Mention at ACM UIST 2017; and Best Paper at iThings 2014. He is one of the Highly Cited Researchers by Clarivate Analytics in 2018-2023.

Yang received the Google Faculty Award in 2009, and the Distinguished Early Career Research Award from the UC Merced Senate in 2011. Yang is a recipient of the Faculty Early Career Development (CAREER) award from the National Science Foundation in 2012. In 2015, Yang received the Distinguished Research Award from UC Merced Senate. He is a Fellow of the IEEE and ACM.

Biography [detail]

Siwei Lyu is a SUNY Empire Innovation Professor at the Department of Computer Science and Engineering, the Director of the UB Media Forensic Lab (UB MDFL), and the founding Co-Director of the Center for Information Integrity (CII) at the University at Buffalo, State University of New York, USA.

Before joining UB, Dr. Lyu served as an Assistant Professor (2008-2014), tenured Associate Professor (2014-2019), and Full Professor (2019-2020) at the Department of Computer Science at the University at Albany, State University of New York. He is the Founding Director of UAlbany's Computer Vision and Machine Learning Lab (CVML). From 2005 to 2008, he worked as a Post-Doctoral Research Associate at the Howard Hughes Medical Institute and the Center for Neural Science at New York University. In 2001, he was an Assistant Researcher at Microsoft Research Asia. Dr. Lyu earned his Ph.D. in Computer Science from Dartmouth College in 2005 and both his M.S. (2000) and B.S. (1997) degrees in Computer Science and Information Science, respectively, from Peking University, China.

Dr. Lyu's research interests include media forensics, computer vision, and machine learning. He has published over 190 refereed journal and conference papers. His research projects are funded by NSF, DARPA, and the US Department of Homeland Security. Dr. Lyu has received numerous awards, such as the IEEE Signal Processing Society Best Paper Award (2011), the National Science Foundation CAREER Award (2010), SUNY Albany's Presidential Award for Excellence in Research and Creative Activities (2017), SUNY Chancellor's Award for Excellence in Research and Creative Activities (2018), Google Faculty Research Award (2019), and IEEE Region 1 Technological Innovation (Academic) Award (2021).

Dr. Lyu has served on the IEEE Signal Processing Society's Information Forensics and Security Technical Committee and held editorial positions with several prestigious journals. Dr. Lyu holds prestigious memberships and distinctions, including being a Fellow of IEEE, IAPR, and AAIA. He is also a Distinguished Member of ACM, a Senior Member of the Sigma Xi Society, and a Member of the Omicron Delta Kappa society.

Biography [detail]

Yu-Chiang Frank Wang received his B.S. degree in Electrical Engineering from National Taiwan University in 2001. He received his M.S. and Ph.D. degrees in Electrical and Computer Engineering from Carnegie Mellon University in 2004 and 2009, respectively. In 2009, Dr. Wang joined the Research Center for Information Technology Innovation (CITI) of Academia Sinica, leading the Multimedia and Machine Learning Lab. Dr. Wang joined the Department of Electrical Engineering at National Taiwan University as an Associate Professor in 2017, and was promoted to Professor in 2019. Since 2022, Dr. Wang joins NVIDIA, where he serves as the Research Director in Deep Learning & Computer Vision and leads NVIDIA Research Taiwan. With continuing research focuses on computer vision and machine learning, Dr. Wang's recent research topics include deep learning for vision & language, transfer learning, and 3D vision. Dr. Wang serves as organizing committee members and area chairs of multiple international conferences such as CVPR, ICCV, ECCV, and ACCV. Several of his papers are nominated for the best paper awards, including IEEE ICIP, ICME, AVSS and MVA. Dr. Wang is twice selected as the Outstanding Young Researcher by the Ministry of Science and Technology of Taiwan (2013-2015 and 2017-2019), as well as the Technological Research Innovation Award from the College of EECS at NTU. In 2022, Dr. Wang receives the Y. Z. Hsu Scientific Paper Award in Artificial Intelligence from the Far Eastern Y. Z. Hsu Science & Technology Memorial Foundation. In 2023, Dr. Wang is recognized as the Outstanding Young Scholar by the Foundation for the Advancement of Outstanding Scholarship.