Dr. Hui Lei
CTO, Watson Health Cloud, IBM
Title: Smarter Pervasive Computing
Date: March 14, 2017
The pervasive computing discipline has evolved substantially since its inception. A lot of progress has been made in scaling pervasive computing, which has led to new, societal-scale capabilities such as mobile crowdsensing and the Internet of Things. Pervasive computing applications have also expanded from smart appliances and smart environments in the early days to systems of much broader scope such as smart cities and smart transportation. Going forward, an important direction is to enable a significantly heightened level of smartness in pervasive computing systems, by leveraging developments in big data and cognitive computing. Specifically, with its exponentially increasing volume, velocity and variety, big data is hailed as the world's new natural resource, and is driving fundamental changes in technology, business, and society. The biggest value of big data lies in the deep, actionable insights that can be derived from integrating all sources and modalities of data, across pervasive sensors and enterprise information systems. Such insights can then be exploited for business innovations and competitive advantages. Cognitive computing is a key enabling technology for turning big data into insights. Different from traditional programmable systems, cognitive systems are able to understand human knowledge, reason with a purpose, and learn and improve over time. Pervasive applications that integrate big data across the board and are cognitive are thus more insightful and can offer an unprecedented level of intelligence. In this talk, I will discuss the implications of big data and cognitive computing on pervasive computing. I will draw upon our experience at IBM Watson Health, and discuss how big data and cognitive computing can come together with pervasive computing to enable innovative health solutions that address many clinical, societal, and economic issues. I will present use cases, highlight the challenges, describe our approaches, and relate to client experiences.
Hui Lei is CTO of IBM Watson Health Cloud, an IBM Distinguished Engineer, and an IBM Master Inventor. Previously he was Senior Manager, Cloud Platform Technologies at the IBM T. J. Watson Research Center, and led IBM’s worldwide research strategies in cloud infrastructure services and cloud managed services. His technical interests include mobile and pervasive computing, cloud computing, big data, and enterprise computing. His technical vision and creative contributions have influenced many commercial software products and services, and have resulted in over 70 patents. He is a Fellow of the IEEE, Editor-in-Chief of the IEEE Transactions on Cloud Computing, and Chair of the IEEE Computer Society Technical Committee on Business Informatics and Systems. He has taken part in many international conferences as a steering committee chair, general chair, technical program chair, or keynote speaker. He received his PhD in Computer Science from Columbia University.
Dr. John Krumm
Title: Curious True Facts About People and Location
Date: March 15, 2017
We are all people who have a definite location, but our intuitions about people and their locations are not always correct. Fortunately, researchers have been looking at how people behave with respect to location, and they have discovered surprising facts that do not necessarily match our assumptions. For example, as technologists, we tend to assume that people have strong concerns about their location privacy. But is this really true? As another example, researchers have tried to show that the same models of location behavior apply to both people and animals. Does this survive scrutiny? And if people exhibit complex behavior in terms of location, does this mean it is difficult to predict where they will go in the future? Not necessarily. The last few decades have seen principled answers to these and other questions, with research driven by growing demand for mobile computing, increasing availability of location data, and expanding problems in transportation. In this talk I will present several ways that our intuition about people and location does not match reality.
John Krumm graduated from Carnegie Mellon University in 1993 with a PhD in robotics and a thesis on texture analysis in images. He worked at the Robotics Center of Sandia National Laboratories in Albuquerque, New Mexico for the next four years. His main projects there were computer vision for object recognition for use in robots and vehicles. He has been at Microsoft Research in Redmond, Washington, USA since 1997, and is currently a principal researcher. His research focuses on understanding peoples' location and how to use that information to benefit the user. He holds 56 U.S. patents. Dr. Krumm was a PC chair for UbiComp 2007, ACM SIGSPATIAL 2013, and ACM SIGSPATIAL 2014, served on the editorial board of IEEE Pervasive Computing Magazine and as a coeditor in chief for the Journal of Location Based Services. He currently serves on the editorial board of the Journal of Location Based Services and as an associate editor for ACM Transactions on Spatial Algorithms and Systems.