Biomedicine is increasingly driven by digital data describing everything from molecules to cohorts of patients. The NIH response to this opportunity and challenge can be broadly characterized as both fundamental research and development in data science. The former is exemplified by the Big Data to Knowledge (BD2K) program and I will describe some of the latest developments impacting the human condition. The latter is exemplified by the NIH Commons which is attempting to move us from a siloed approach to data and analysis to a platform based approach. I will describe how we are approaching this transition.
Dr. Philip E. Bourne PhD, FACMI is the Associate Director for Data Science at the National Institutes of Health in the Office of the Director. Prior to joining NIH, Dr. Bourne was Associate Vice Chancellor for Innovation and Industry Alliances in the Office of Research Affairs and a Professor in the School of Pharmacy and Pharmaceutical Sciences at the University of California at San Diego. Dr. Bourne is a Past President of the International Society for Computational Biology, an elected fellow of the American Association for the Advancement of Science (AAAS), the International Society for Computational Biology (ISCB) and the American Medical Informatics Association (AMIA). He has published over 300 papers and 5 books.
Jason A. Hoffman, Ph.D. VP, Head of Product Area Cloud Infrastructure, Ericsson
The three silos of our industry have been network, compute, and data. The trend has been to converge the management of these three while candidly thinking of compute as a networking add-on or storage as an afterthought to an application. Now we're in an era where supply chain, factory thinking and sustainability concepts have to be introduced into infrastructure and make possible a data-centric design where compute and network are features of the storage environment. The use of silicon photonics and opticals networks in the datacenter along with the disaggregation into network addressable components is the system basis of such an architecture.
Jason Hoffman is the Head of Product Area Cloud Infrastructure at Ericsson and is the P&L owner (GM) of the Ericsson Cloud business in Business Unit IT & Cloud. Our portfolio includes datacenters/DCIM, hardware, platforms (applications and data), data and storage and security. Prior to Ericsson he was a founder and the CTO at Joyent, a pioneering high performance cloud IaaS and software provider, where he ran product, engineering, operations and commercial management for nearly a decade. He is considered to be one the pioneers of large scale cloud computing, in particular the use of container technologies, asynchronous, high concurrency runtimes and hyperconverged/hyperscale server, storage and networking designs. Jason holds several early patents in the area. Jason is also an angel investor, strategy and execution advisor, venture and private equity advisor, has served on several boards and is on the board of the Wordpress Foundation. Jason has a BS and MS from UCLA and a PhD from UCSD. He is a San Francisco native that now lives in Stockholm with his wife and daughters.
Technology transitions and the confluence of several well known technologies (mobility, cloud, social platforms, analytics, artificial intelligence, IoT and others) signals a new era of IT and unleashes two converging digitization waves: people centric digitization and machine centric digitization. Among the most important shifts driven by the these digitization waves is the shift and expansion of an enterprise's interaction with its customers away from the core of the enterprise - away from 100% dependence on the legacy and internal systems-of-record and towards the consumer, intelligent things and engaging customer experiences. In this new era, Big Data means core data can become a platform. If there is sufficient size and uniqueness, if it's useful enough to others, and if there are appropriate (e.g., legal, technical) methods to exchange/federate it with other data sources, it becomes the accretion point for even more new data, services and products. The challenge is no longer to connect the data sources within the enterprise, but to connect data sources from a myriad of places - both inside and outside the enterprise. Connectivity with things, computing at the edge-cloud, streaming analytics, edge-cloud process orchestration are the new requirements for next generation architectures. Next generation architectures focus on agility and rapid scale and innovation using APIs as the interaction point and micro services, small, autonomous, and self-contained focused on a single business capability that can run on the edge, cloud or anywhere. Edge analytics, hyper distributed computing, hyper distribution of data, the rise of machines requires a hybrid approach and a shift to event driven architectures, data streaming, data focused applications and platform thinking. This keynote addresses these concepts and more in discussing the new era of IT.
Kerrie Holley is VP and CTO for Software Platform Group at Cisco. Kerrie drives the application of Cisco's analytics and automation software portfolio into vertical markets and cross-industries. He was previously an IBM Fellow appointed in 2006. Prior to joining IBM Research, he was CTO for IBM's Global Business Services' Application Innovation Service. He holds several patents, authored two books, and published articles. He appeared on ABC News and a TED talk when IBM Watson was first introduced describing Watson's next job. He holds a mathematics, Juris Doctorate and honorary Ph.D. degree from DePaul University
Sushil K.Prasad, NSF, USA
There is a flood of geospatial and temporal data ranging from satellite imagery of vegetation cover in Africa, to dynamic hurricane evolution and tracking over USA, to traffic patterns over large metros. Parallel processing is, therefore, imperative for data-and-compute-intensive Geospatial computations, such as spatial join, polygonal overlay (also utilized over medical images, VLSI CAD, graphics) and interesting region discovery. The computer architecture now is massively parallel and hybrid, with a pair of multi-core CPU and many-core GPU now commonplace in laptops to computer nodes of high-performance machines and clouds. Beyond the usual concerns of distribution of data and computation across compute nodes of clusters and clouds, an efficient utilization of the CPU-GPU pair is critical, else the Geospatial software will remain inefficient, incurring loss of one to two orders of magnitude in speedup. Recently, we have undertaken GPU-based parallelization of two key tree-based data structures, namely R-tree and Heap, have employed parallel R-tree in polygon overlay system and have parallelized interesting interval discovery problem. This talk will summarize these and introduce some interesting open problems. We foresee significant opportunities for Computer Science research while enabling discoveries in Geoscience and other domain sciences and impacting society at large. I will also briefly discuss National Science Foundation (NSF) programs related to Advanced Cyberinfrastucture's (ACI) multi-disciplinary learning and workforce development such as CAREER, NRT, CRII, and REU site programs.
Sushil K. Prasad (BTech'85 IIT Kharagpur, MS'86 Washington State, Pullman; PhD'90 Central Florida, Orlando - all in Computer Science/Engineering), an ACM distinguished Scientist, is a Professor of Computer Science at Georgia State University (GSU) and Director of Distributed and Mobile Systems (DiMoS) Lab. He has over 140 publications and procured $6M in external collaborative funding for research in Parallel, Distributed, and Data Intensive Computing and Systems. He has been twice-elected chair of IEEE-CS Technical Committee on Parallel Processing (TCPP), and leads the NSF-supported TCPP Curriculum Initiative on Parallel and Distributed Computing. He is currently a Program Director at National Science Foundation in its Advanced Cyberinfrastructure (ACI) Division of Computer and Information Science and Engineering (CISE) directorate.
MapReduce-oriented systems such as Hadoop or the more recent Spark or Flink implement parallelism in a particular way. That fact leads to a new theory of algorithm design for MapReduce. We shall outline the theory, which is based on the existence of a tradeoff between (main) memory size and communication cost. We shall offer some examples of how to get the right design for a number of common problems, including similarity joins, matrix multiplication, and computing marginals.
Jeff Ullman is the Stanford W. Ascherman Professor of Engineering(Emeritus) in the Department of Computer Science at Stanford and CEO of Gradiance Corp. He received the B.S. degree from Columbia University in 1963 and the PhD from Princeton in 1966. Prior to his appointment at Stanford in 1979, he was a member of the technical staff of Bell Laboratories from 1966-1969, and on the faculty of Princeton University between 1969 and 1979. From 1990-1994, he was chair of the Stanford Computer Science Department. Ullman was elected to the National Academy of Engineering in 1989, the American Academy of Arts and Sciences in 2012, and has held Guggenheim and Einstein Fellowships. He has received the Sigmod Contributions Award (1996), the ACM Karl V. Karlstrom Outstanding Educator Award (1998), the Knuth Prize (2000),the Sigmod E. F. Codd Innovations award (2006), and the IEEE von Neumann medal (2010). He is the author of 16 books, including books on database systems, compilers, automata theory, and algorithms.
Wu Chou, Ph.D., IEEE Fellow VP&CTO Network and Enterprise Communications, Huawei Technologies
Internet-of-Things (IoT) combines both digital and physical world into one connected entity. New business opportunities are emerging with IoT, and many of them have already been deployed today. This talk will take a holistic view of IoT from the perspectives new applications and business opportunities, as well as new research challenges in making IoT successful. In particular, we will present the emerging IoT paradigms, such as smart city street lighting, connected cars, smart wearable devices, smart transportation, etc., and the research challenges and opportunities including software-defined-networking (SDN), network-as-a-service, AI, and machine learning in IoT.
Wu Chou is IEEE Fellow, VP, and Chief Technology Officer (CTO) of Network and Enterprise Communications product line of Huawei. He is a member of IEEE Signal Processing Society, Computer Society, and Communication Society - a leading expert in the field of IT, Cloud computing, data networking, SDN/NFV, Internet-of-things (IoT), Big Data, communication, Internet/Web, machine learning, signal processing, UC&C, speech and natural language processing, multimedia and multimodal interaction, service computing, and Web services. He graduated from Stanford University in 1990 with Ph.D. degree in electrical engineering. He worked at AT&T Bell Labs from 1990 to 1996, Lucent Bell Labs from 1996 to 2000, and Avaya from 2000 to 2011 where he was a R&D director and Avaya Labs Fellow. He joined Huawei in 2011 as the global head of Huawei Shannon (IT) Lab, and became CTO in 2015. He published over 200 journal and conference papers, holds more than 40 US and international patents with many additional patent applications pending. He received Bell Labs President's Gold Award for his achievement in 1997, Avaya Leadership Award in 2005, and the outstanding standard, innovation, and patent contribution award in 2008 and 2009. He is a well known figure in standard bodies and professional societies, served as an editor for multiple standards at W3C, ECMA, ISO, ETSI, etc. He was an editor of IEEE Transactions on Services Computing (TSC), IEEE TSC Special Issue on Cloud Computing, IEEE Transactions Special Issue on Human-machine Interaction, IEEE Transactions on Audio and Language Processing, and Journal of Web Services Research. He served as a member of the advisory board in multiple professional committees, including the advisory board of MIT Computer Science and Artificial Intelligence Lab (CSAIL) Big Data Research Program, etc.
IEEE Computer Society's Technical Committee on Services Computing (TC-SVC) is a multi-disciplinary group whose purpose is to advance and coordinate work in the field of Services Computing carried out throughout the IEEE in scientific, engineering, standard, literary and educational areas.
Services Computing has become a cross-discipline that covers the science and technology of bridging the gap between Business Services and IT Services. The underneath breaking technology suite includes Web services and service-oriented architecture (SOA), cloud computing, business consulting methodology and utilities, business process modeling, transformation and integration. This scope of Services Computing covers the whole lifecycle of services innovation research that includes business componentization, services modeling, services creation, services realization, services annotation, services deployment, services discovery, services composition, services delivery, service-to-service collaboration, services monitoring, services optimization, as well as services management. The goal of Services Computing is to enable IT services and computing technology to perform business services more efficiently and effectively.
The Services Society is a non-profit professional organization that has been created to promote worldwide research and technical collaboration in Services Computing among academia and industrial professionals. Its members are volunteers from industry and academia with common interests. The Services Society is registered in the USA as a "501(c) organization", which means that it is an American tax-exempt nonprofit organization. The Services Society collaborates with other professional organizations such as the IEEE to sponsor conferences and to promote an effective services curriculum in colleges and universities. The Services Society initiates and promotes a "Services University" program worldwide to bridge the gap between industrial needs and university instruction. It has created Services Society Young Scientist Forums (SSYSF) worldwide. The Services Society has provided professional services for more than 30,000 researchers, practitioners, professors, and students directly.
If you have any questions or queries on ICWS 2016, please send email to icws AT ServicesSociety.org.