Research Challenges and Solutions for IOTT/CPS
Abstract: As the Internet of Things (IOT) matures and supports increasingly sophisticated applications, the research needs for IOT also expand considerably. This talk discusses several major research challenges for the future IOT where trillions of devices are connected to the Internet; call it the Internet of Trillions of Things (IOTT). Research topics covered include new systems of systems problems, the impact of massive scaling, and IOTT for healthcare. Smart cities are used to present examples of new system of system research issues and their solutions. Scaling and long time maintenance problems give rise to the need for runtime validation. Why this is important and how to accomplish this is presented. We use the Internet of Healthcare Things to identify the realisms that must be addressed in real home deployments. We also discuss the problems and solutions for using speech as a major sensing modality for smart healthcare based on an emo2vec (an extension to word2vec) and LSTMs. The list of topics is not meant to be comprehensive, but does address some of the main research issues in IOTT/CPS.
Brief Bio: Professor John A. Stankovic is the BP America Professor in the Computer Science Department at the University of Virginia. He served as Chair of the department for 8 years. He is a Fellow of both the IEEE and the ACM. He has been awarded an Honorary Doctorate from the University of York for his work on real-time systems. He won the IEEE Real-Time Systems Technical Committee's Award for Outstanding Technical Contributions and Leadership. He also received the IEEE Technical Committee on Distributed Processing's Distinguished Achievement Award (inaugural winner). He has seven Best Paper awards, including one for ACM SenSys 2006. Stankovic has an h-index of 115 and over 57,000 citations. In 2015 he was awarded the Univ. of Virginia Distinguished Scientist Award, and in 2010 the School of Engineering's Distinguished Faculty Award. He also received a Distinguished Faculty Award from the University of Massachusetts. He has given more than 40 Keynote talks at conferences and many Distinguished Lectures at major Universities. He also served on the National Academy's Computer Science Telecommunications Board. He was the Editor-in-Chief for the IEEE Transactions on Distributed and Parallel Systems and was founder and co-editor-in-chief for the Real-Time Systems Journal. His research interests are in real-time systems, wireless sensor networks, smart and connected health, cyber physical systems, and the Internet of Things. Prof. Stankovic received his PhD from Brown University.
Challenges and Practices of Large Scale Visual Intelligence in the Real-World
Abstract: Visual intelligence is one of the key aspects of Artificial Intelligence. Considerable technology progresses along this direction have been made in the past a few years. However, how to incubate the right technologies and convert them into real business values in the real-world remains a challenge. In this talk, we will analyze current challenges of visual intelligence in the real-world and try to summarize a few key points that help us successfully develop and apply technologies to solve real-world problems. In particular, we will introduce a few successful examples, including “City Brain”, “Luban (visual design)”, from the problem definition/discovery, to technology development, to product design, and to realizing business values.
Brief Bio: Xian-Sheng Hua is now a VP/Distinguished Engineer of Alibaba Group, leading the Artificial Intelligence Center of Alibaba Cloud and City Brain Lab of DAMO Academy. Dr. Hua is an IEEE Fellow and ACM Distinguished Scientist. He received his B.S. degree in 1996, and the Ph.D. degree in applied mathematics in 2001, both from Peking University, Beijing, China. He joined Microsoft Research Asia in 2001, as a Researcher. He was a Principal Research and Development Lead in Multimedia Search for the Microsoft search engine, Bing, from 2011 to 2013. He was a Senior Researcher with Microsoft Research Redmond Redmond from 2013 to 2015. He has authored or coauthored more than 200 research papers and has filed more than 90 patents. His research interests include big multimedia data search, advertising, understanding, and mining, as well as pattern recognition and machine learning. Dr. Hua served or is now serving as an Associate Editor for the IEEE Trans. on Multimedia and ACM Transactions on Intelligent Systems and Technology. He served as a Program Co-Chair for IEEE ICME 2013, ACM Multimedia 2012, and IEEE ICME 2012. He was one of the recipients of the 2008 MIT Technology Review TR35 Young Innovator Award for his outstanding contributions on video search. He was the recipient of the Best Paper Awards at ACM Multimedia 2007, and Best Paper Award of the IEEE Trans. on CSVT in 2014.Dr. Hua will be serving as general co-chair of ACM Multimedia 2020.