KEYNOTEs
Keynote by Dinesh Verma
IBM Fellow, Distributed AI
IBM T. J. Watson Research Center
IBM Fellow, Distributed AI
IBM T. J. Watson Research Center
Biography: Dinesh C. Verma is an IBM Fellow leading the area of Distributed AI at IBM T J Watson Research Center, Yorktown Heights, New York. This area is responsible for creating new technologies that intersect the domain of Artificial Intelligence, Internet of Things, and Distributed Systems & Networks. He received his Doctorate in Computer Science from University of California at Berkeley in 1992, the Bachelors' in Computer Science from Indian Institute of Technology, Kanpur, India in 1987, and Masters in Management of Technology from Polytechnic University, Brooklyn, NY in 1998. He holds over 150 patents, and has authored over 125 papers and 10 books in the field of computer science. He has served in various program committees, IEEE technical committees, editorial boards and led international multi-institutional research alliances. He is a Fellow of the IEEE, and a Fellow of the UK Royal Academy of Engineering.
Abstract: Distributed AI for Intelligence at the Edge
Creating intelligence at many devices in an ubiquitous environment requires that different devices be enabled with attributes like learning from the environment, and be able to take decisions independently. In this talk, we will examine the different issues that are involved with creating such type of distributed environments where all elements learn from their environments, and examine a few instances where the concept of distributed AI can be applied in enterprise, military and smarter-city contexts.
Abstract: Distributed AI for Intelligence at the Edge
Creating intelligence at many devices in an ubiquitous environment requires that different devices be enabled with attributes like learning from the environment, and be able to take decisions independently. In this talk, we will examine the different issues that are involved with creating such type of distributed environments where all elements learn from their environments, and examine a few instances where the concept of distributed AI can be applied in enterprise, military and smarter-city contexts.
Keynote by Wendy Nilsen
Program Director, Smart and Connected Health Program
National Science Foundation
Program Director, Smart and Connected Health Program
National Science Foundation
Biography: Wendy Nilsen, Ph.D. is the Program Director for the Smart and Connected Health Program in the computer and Information Science and Engineering Directorate of the National Science Foundation. Her work focuses on the intersection of 21st century computing, engineering and medicine/health. Her focus includes the supporting research, multidisciplinary dialogue and convergence training to encourage the development of a wide range of methods for data collection, advanced analytics and the creation of effective cyber-human systems. Her interests span the areas of sensing, analytics, cyber-physical systems, information systems, big data and robotics. More specifically, her efforts include: serving as cochair of the Health Information Technology Research and Development working group of the Networking and Information Technology Research and Development Program; the lead for the NSF/NIH Smart and Connected Health announcement; convening workshops to address methodology in technology in health research; serving on numerous federal technology initiatives; and, leading training institutes. Prior to joining NSF, Wendy was at the National Institutes of Health.
Abstract: With so many trained professionals and so much money, why can’t medicine and healthcare be smarter?
Paradoxically, the United States spends more on healthcare than any other industrialized country, yet America’s health outcomes rank among the worst. Given the expertise, training and access to technology available in the United States, how is this possible? This talk explores the current state of practice, as well as recent advances made possible by the convergence between the biomedical and technological disciplines. Issues such as personalized medicine and prevention approaches, aided by new sensing, analytics, language technologies, visualization tools and interface methods, have the potential to transform health from reactive treatments based on deviations from population-level data to one in which interventions are tailored to individual characteristics. While this may be the ideal state, to make this happen will require a range of new fundamental scientific advances across computing, engineering and the behavioral and social sciences in concert with the efforts of the biomedical research community. These partnerships are needed because the solutions to complex health problems and processes must effectively satisfy a multitude of constraints arising from characteristics of the data, limits of medical knowledge, a lack of ground truth, cultural differences between technical and medical disciplines and regulatory, safety and privacy concerns. This talk explores the opportunities and challenges in developing a smarter and more connected health ecosystem and highlights promising new areas of research.
Abstract: With so many trained professionals and so much money, why can’t medicine and healthcare be smarter?
Paradoxically, the United States spends more on healthcare than any other industrialized country, yet America’s health outcomes rank among the worst. Given the expertise, training and access to technology available in the United States, how is this possible? This talk explores the current state of practice, as well as recent advances made possible by the convergence between the biomedical and technological disciplines. Issues such as personalized medicine and prevention approaches, aided by new sensing, analytics, language technologies, visualization tools and interface methods, have the potential to transform health from reactive treatments based on deviations from population-level data to one in which interventions are tailored to individual characteristics. While this may be the ideal state, to make this happen will require a range of new fundamental scientific advances across computing, engineering and the behavioral and social sciences in concert with the efforts of the biomedical research community. These partnerships are needed because the solutions to complex health problems and processes must effectively satisfy a multitude of constraints arising from characteristics of the data, limits of medical knowledge, a lack of ground truth, cultural differences between technical and medical disciplines and regulatory, safety and privacy concerns. This talk explores the opportunities and challenges in developing a smarter and more connected health ecosystem and highlights promising new areas of research.
