Organizers
Qualcomm
Amirhossein Habibian is a research scientist at Qualcomm AI Research. His research is focused on computational efficiency of computer vision models to process high resolution images and videos. He received his PhD on learning multimodal video representations from the University of Amsterdam in 2016. During his studies, he received the Best Paper Award at ACM Multimedia 2014, the Best Paper Award at ASCI 2015, and top performer in the TRECVID video search challenge in 2014 and 2015.
Webpage: https://habibian.github.io/
Qualcomm
Fatih Porikli is an IEEE Fellow and Senior Director at Qualcomm AI Research. He was a full tenured Professor in the Research School of Engineering, Australian National University (ANU), Canberra. He served as the Vice President of San Diego Device Hardware Competency Center, Futurewei, San Diego. He was the Chief Scientist of Autonomous Vehicles at Futurewei, Santa Clara. Until 2017, he was the Computer Vision Research Group Leader at Data61/CSIRO, Australia. He was a Distinguished Research Scientist at Mitsubishi Electric Research Laboratories (MERL), Cambridge.
Webpage: https://www.porikli.com/
Qualcomm
Auke Wiggers is a research scientist at Qualcomm AI Research in Amsterdam. He has worked on neural codecs for various media, and enabling deployment of these codecs to power-constrained devices. His current focus is on generative models for downstream applications. He joined Qualcomm in 2017 through the acquisition of deep learning startup Scyfer.
Northeastern University
Yun Raymond Fu is COE Distinguished Professor at Northeastern University, Boston. He has authored more than 500 scientific publications as well as over 40 patented inventions. He received 7 Prestigious Young Investigator Awards from NAE, ONR, ARO, IEEE, INNS, UIUC, Grainger Foundation; 12 Best Paper Awards from IEEE, ACM, IAPR, SPIE, SIAM. He is Member of Academia Europaea (MAE), Member of European Academy of Sciences and Arts, Fellow of National Academy of Inventors (NAI), Fellow of AAAS, IEEE, IAPR, OSA, SPIE, and AAIA. He received the 2024 IEEE Edward J. McCluskey Technical Achievement Award for "innovative and impactful contributions to representation learning, computer vision, face, and gesture recognition".
Webpage: http://www1.ece.neu.edu/~yunfu/
Chuo-Ling Chang leads On-Device ML Infrastructure in Google Core ML, instrumental in bringing machine learning capabilities to mobile, embedded devices, and the web, enhancing user experiences across various Google products such as Meet, YouTube, Photos, Camera, and Lens. He also leads Google's MediaPipe open source project, actively engaging with and contributing to the open-source research and developer communities. Before his tenure at Google, he played pivotal roles in various startup companies, spearheading research and development in multimedia processing and interactive streaming systems. He holds a Ph.D. degree from the Information Systems Laboratory at Stanford University, California.
University of Texas at Dallas
Yapeng Tian is an assistant professor in the Computer Science Department of UT Dallas and lead the Computer Vision and Multimodal Computing (CVMC) Lab. Before coming to UTD, Yapeng finished his PhD at University of Rochester, advised by Chenliang Xu, his master degree at Tsinghua University working with Wenming Yang, and B.E degree at Xidian University. He was a visiting student at SIAT advised by Yu Qiao. He did internships at Adobe Research with Dingzeyu Li and Meta with Alexander Richard.
Webpage: https://www.yapengtian.com/
Tsinghua University
Wenming Yang is an Associate Professor in Shenzhen International Graduate School/Department of Electronic Engineering, Tsinghua University. His research interests include image processing, computer vision, pattern recognition, deep learning and artificial intelligence applications. He has published more than 10 invention patents and more than 100 academic papers on top-tier international journals and conferences such as IEEE/CVF ICCV, CVPR, ECCV, ACM MM, AAAI, ICML, ICLR, and MICCAI, etc.