Monday, September 23, 2019 - 18:00-20:00

This panel discussion and networking will bring together early career engineers and scientists as well as senior graduate students for an opportunity to network with peers and meet with industry leaders. The panelists will share their career stories and experiences. They will talk about their motivations and the paths that led them to where they are now; the challenges they had to face and the ways of overcoming them; and the components of an effective career development plan for young professionals.

Dr. Ioannis Katsavounidis

Dr. Ioannis Katsavounidis is part of the Video Infrastructure team, leading technical efforts in improving video quality across all video products at Facebook. Before joining Facebook, he spent 3.5 years at Netflix, contributing to the development and popularization of VMAF, Netflix's video quality metric, as well as inventing the Dynamic Optimizer, a shot-based video quality optimization framework that brought significant bitrate savings across the whole streaming spectrum. Before that, he was a professor for 8 years at the University of Thesally's Electrical Engineering Department in Greece, teaching video compression, signal processing and information theory. He has over 100 publications and patents in the general field of video coding, but also high energy experimental physics. His research interests lie in video coding, video quality, adaptive streaming and hardware/software partitioning of multimedia processing.

As an AE of TIP (2018-), General Co-Chair of MMSP'20, TPC chair of MMSP'19, OC member of ICME'19, etc. He is also a TC member of IEEE MMSP and IDSP. He received his Ph.D. from Beijing University of Technology in 2001, and M.Eng/B.Eng from USTC in 1998/1995. He is a senior member of IEEE.

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Dr. Zicheng Liu

Zicheng Liu is a principal researcher manager at Microsoft AI&R Ambience Intelligence team managing the computer vision science group.

Zicheng Liu received his Ph.D. in computer science from Princeton University in 1996. He got his B.S. degree in mathematics from HuaZhong Normal University, Wuhan, China, in 1984, and his M.S. in Operations Research from the Institute of Applied Mathematics, Chinese Academy of Sciences, in 1989. Before joining Microsoft Research, he worked at Silicon Graphics, Inc. as a member of technical staff for two years, where he developed the trimmed NURBS tessellator shipped in both OpenGL and the OpenGL Optimizer.

Current research interests include human activity recognition, 3D face modeling and animation, and multimedia signal processing. He has worked on a variety of topics including Steiner trees, average case complexity, linked figure animation, and trimmed NURBS tessellation for large CAD model visualization.

Liu has served in the technical committee for many international conferences. He was a member of the Audio and Electroacoustics Committee of IEEE Signal Processing Society. He is the chair of the Multimedia Systems and Applications Technical Committee of IEEE CAS society. He is a steering committee member of IEEE Transactions on Multimedia. He is the Editor-in-Chief of Journal of Visual Communications and Image Representation, and an associate editor of Machine Vision and Applications.  He served as a guest editor of IEEE Transactions on Multimedia, and a guest editor of IEEE Multimedia Magazine. He is an affiliate professor in the department of Electrical Engineering, University of Washington. He was an IEEE distinguished lecturer from 2015-2016. He is a fellow of IEEE.

Dr. Gang Yu

Gang YU is the leader for the detection team in MEGVII. He graduated from Nanyang Technological University, Singapore, in 2014. He then joined MEGVII and his research interest focuses on computer vision and machine learning, including object detection, segmentation, skeleton, and human action analysis. Gang Yu has published more than twenty papers in the top conference like CVPR, ICCV, ECCV and AAAI.  Gang Yu obtained the winners of COCO2017 and COCO2018 detection challenge and Keypoint challenge.