Abstract: Many basic services that are essential to human dignity, such as education and healthcare remain inaccessible (at acceptable quality level) to large numbers of people. With increasing digitization of the world and easy availability of computational power, there is an opportunity to apply data science to transform these services. We begin by describing our attempts to make learning more effective via a platform called VideoKen. Our platform, available as a cloud-hosted portal, uses novel techniques to evaluate videos, support search and recommendation of educational videos on a given topic, index them to support more effective navigation, e.g., by automatically generating a table of contents and glossary, and to gain insights from the learner's interactions with the videos. VideoKen also supports social learning at multiple levels. It enables faculty to conveniently share their curated video content within and across institutes, thus helping each other as a community. Likewise, it enables students also to curate specific video clips and share with their classmates, friends or the community at large. We describe many outstanding challenges in creating an engaging and personalized learning experience for each learner, and describe our preliminary efforts to deal with those challenges. We then describe a dire need and an opportunity to improve the healthcare system worldwide by supporting a shift from reactive treatment to more proactive action. As examples of what is possible, we present machine learning techniques to predict a class of complications in an ICU, and to identify patients in a hospital who are likely to experience a deterioration in their medical condition. We also present work that shows the applicability of remote sensing and data analytics to measure body vitals such as respiration and heart rate, to screen for diseases, and to reduce the need for people to visit a hospital. We frame all of the above efforts as examples of using data science and cloud to offer personalized services at scale. We describe many open problems that require further research.
About the Speaker: Prof. Manish Gupta is the Infosys Foundation Chair Professor at IIIT Bangalore and co-founder and CEO of VideoKen, an educational technology startup. Previously, Manish has served as Vice President and Director of Xerox Research Centre India, and has held various leadership positions with IBM, including that of Director, IBM Research - India and Chief Technologist, IBM India/South Asia. As a Senior Manager at the IBM T.J. Watson Research Center in Yorktown Heights, New York, Manish he led the team developing system software for the Blue Gene/L supercomputer. IBM was awarded a National Medal of Technology and Innovation for Blue Gene by US President Barack Obama in 2009. Manish holds a Ph.D. in Computer Science from the University of Illinois at Urbana Champaign. He has co-authored about 75 papers, with more than 6,000 citations in Google Scholar (and an h-index of 42) in the areas of high-performance computing, compilers, and virtual machine optimizations, and has been granted 19 US patents. While at IBM, Manish received two Outstanding Technical Achievement Awards, an Outstanding Innovation Award and the Lou Gerstner Team Award for Client Excellence. Manish is currently serving as the chair of IKDD, the ACM India Special Interest Group on Knowledge Discovery and Data Mining, and was General Co-Chair for IKDD Conference on Data Sciences 2015. He is an ACM Fellow, a Fellow of the Indian National Academy of Engineering, and a recipient of a Distinguished Alumnus Award from IIT Delhi.