Organizers

Amir 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/

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/

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. 

Xinyin Ma is currently a Ph.D. candidate at National University of Singapore, working under the supervision of Prof. Xinchao Wang. Her research focuses on efficient generative models, including the inference acceleration of diffusion models and large language models. Her contributions include DeepCache and LLM-Pruner. She was awarded the prestigious Google PhD Fellowship in 2024.

Webpage: https://horseee.github.io/

Lanqing Guo is a postdoc research fellow supervised by Prof. Zhangyang (Atlas) Wang at The University of Texas at Austin. She obtained her Ph.D. degree from Nanyang Technological University with Best Thesis Award in 2024 under the supervision of Prof. Bihan Wen. Her current interests focus on high-quality, high-fidelity vision and multi-modal data generation.  

Webpage: https://guolanqing.github.io/

Rahim Entezari is a Research Scientist at Stability.ai. His research focuses on generative text-to-image and text-to-video models, with a particular interest in enhancing the reasoning capabilities of text-to-video generation. He received his PhD with distinction from TU Graz and was honored with the Best Paper Award at ICML 2024 for Stable Diffusion 3 paper.   

Webpage: https://rahimentezari.github.io/

Tao Hu is a Tao Hu is a post-doctoral research fellow at ommer-lab, working with Bjorn Ommer. His research focuses on scalable, flexible, and efficient generative models. He received his Ph.D. in computer science from the University of Amsterdam in 2023 under the supervision of Cees Snoek. His doctoral research was selected for the CVPR 2023 Doctoral Consortium. He co-organizes the ECCV 2024 Workshop on Audio-Visual Generative Learning. He serves as Area Chair for both the CVPR AI4CC Workshop. He is also an outstanding reviewer for NeurIPS 2024.

Webpage: https://taohu.me/

Qinghao Hu is a postdoctoral associate working with Song Han at Massachusetts Institute of Technology. He obtained his Ph.D. degree from Nanyang Technological University in 2023, advised by Tianwei Zhang and Yonggang Wen. His research focuses on building efficient machine learning systems. His work received the Distinguished Paper Award at ASPLOS. He is also a recipient of the Google PhD Fellowship and has been recognized as one of the ML and Systems Rising Stars.

 Webpage: tonyhao.xyz