Organizer Details
Kuan-Chuan Peng
Mitsubishi Electric Research Laboratories (MERL)
Bio:
Dr. Kuan-Chuan Peng is a Research Scientist at Mitsubishi Electric Research Labs (MERL). Before joining MERL, he was a Staff Scientist at Siemens Corporate Technology. He received his Ph.D. degree in Electrical and Computer Engineering from Cornell University in 2016. He received his Bachelor's degree in Electrical Engineering and an M.S. degree in Computer Science from National Taiwan University in 2009 and 2012 respectively. His research interests include incremental learning, developing practical solutions given biased or scarce data, and fundamental computer vision and machine learning problems. His works have appeared in PAMI, CVPR, ICCV, ECCV, etc. He co-organized the following workshops: (1) 2022 Workshop on Artificial Intelligence with Biased or Scarce Data in conjunction with AAAI 2022. (2) 2020 and 2021 Workshop on Fair, Data-Efficient and Trusted Computer Vision in conjunction with CVPR in 2020 and 2021. (3) 2020 and 2021 Workshop on Vision Applications and Solutions to Biased or Scarce Data in conjunction with WACV in 2020 and 2021. (4) 2018 and 2019 Workshop on Vision with Biased or Scarce Data in conjunction with CVPR in 2018 and 2019.
Ziyan Wu
UII America, Inc.
Bio:
Dr. Ziyan Wu is a Principal Expert Scientist at UII America, Inc. in Cambridge, MA. He received a Ph.D. degree in Computer and Systems Engineering from Rensselaer Polytechnic Institute, Troy in 2014. He received a B.S. degree and an M.S. degree in Measurement Technology and Instruments, both from Beihang University in China in 2006 and 2009. He was affiliated with the DHS Center of Excellence on Explosives Detection, Mitigation and Response (ALERT). His research interests include 3D object recognition, scene understanding, video surveillance, deep learning and augmented reality. He co-organized the following events: (1) 2022 Workshop on Artificial Intelligence with Biased or Scarce Data in conjunction with AAAI 2022. (2) 2020 and 2021 Workshop on Fair, Data-Efficient and Trusted Computer Vision in conjunction with CVPR in 2020 and 2021. (3) The 2018 and 2019 Workshop on Vision with Biased or Scarce Data in conjunction with CVPR in 2018 and 2019. (4) The CVPR Industry EXPO Spotlight in 2017. (5) The VIEW workshop in conjunction with CVPR 2016.