Learning to Appreciate: Transforming Multimedia Communications via Deep Video Analytics
Speaker: Dr. Yonggang Wen
Time: Oct 22, 2018
Abstract: Media-rich applications will continue to dominate mobile data traffic with an exponential growth, as predicted by Cisco Video Index. The improved quality of experience (QoE) for the video consumers plays an important role in shaping this growth. However, most of the existing approaches in improving video QoE are system-centric and model-based, in that they tend to derive insights from system parameters (e.g., bandwidth, buffer time, etc) and propose various mathematical models to predict QoE scores (e.g., mean opinion score, etc). In this talk, we will share our latest work in developing a unified and scalable framework to transform multimedia communications via deep video analytics. Specifically, our framework consists two main components. One is a deep-learning based QoE prediction algorithm, by combining multi-modal data inputs to provide a more accurate assessment of QoE in real-time manner. The other is a model-free QoE optimization paradigm built upon deep reinforcement learning algorithm. Our preliminary results verify the effectiveness of our proposed framework. We believe that the hybrid approach of multimedia communications and computing would fundamentally transform how we optimization multimedia communications system design and operations.
Bio: Dr. Yonggang Wen is an Associate Professor with School of Computer Science and Engineering (SCSE) at Nanyang Technological University (NTU), Singapore. He also serves as the Associate Dean (research) at the College of Engineering, and the Director of Nanyang Technopreneurship Centre at NTU. He received his PhD degree in Electrical Engineering and Computer Science (minor in Western Literature) from Massachusetts Institute of Technology (MIT), Cambridge, USA, in 2007. Previously he has worked in Cisco to lead product development in content delivery network, which had a revenue impact of 3 Billion US dollars globally.
Dr. Wen has worked extensively in learning-based system prototyping and performance optimization for large-scale networked computer systems. In particular, his work in Multi-Screen Cloud Social TV has been featured by global media (more than 1600 news articles from over 29 countries) and received 2013 ASEAN ICT Awards (Gold Medal). His work on Cloud3DView, as the only academia entry, has won 2016 ASEAN ICT Awards (Gold Medal) and 2015 Datacentre Dynamics Awards 2015 – APAC (‘Oscar’ award of data centre industry). He is a co-recipient of 2015 IEEE Multimedia Best Paper Award, and a co-recipient of Best Paper Awards at 2016 IEEE Globecom, 2016 IEEE Infocom MuSIC Workshop, 2015 EAI/ICST Chinacom, 2014 IEEE WCSP, 2013 IEEE Globecom and 2012 IEEE EUC. He received 2016 IEEE ComSoc MMTC Distinguished Leadership Award. He serves on editorial boards for ACM Transactions Multimedia Computing, Communications and Applications, IEEE Transactions on Circuits and Systems for Video Technology, IEEE Wireless Communication Magazine, IEEE Communications Survey & Tutorials, IEEE Transactions on Multimedia, IEEE Transactions on Signal and Information Processing over Networks, IEEE Access Journal and Elsevier Ad Hoc Networks, and was elected as the Chair for IEEE ComSoc Multimedia Communication Technical Committee (2014-2016). His research interests include cloud computing, green data centre, distributed machine learning, big data analytics, multimedia network and mobile computing.