KEYNOTE SPEAKERS

“High-performance computing and “big data” in integrative cancer informatics. Challenges and opportunities in intelligent molecular medicine.” Personalized medicine requires better identification of patient subgroups and novel treatment options. Since most cancer treatments only work for subsets of patients we need alternative treatment options. Single drugs are rarely sufficient; thus, we need to identify drug combinations, and new drugs. Data on thousands of cancer patient profiles from diverse technology platforms provide essential resources for molecular medicine. However, effectively integrating, annotating, and analyzing these high-dimensional, heterogeneous and distributed data with aim to create intelligent hypotheses and realistic models of human disease is not trivial. Systematic computational analysis has the potential to unravel mechanism of action for therapeutics, re-position existing drugs for novel, use and prioritize multiple candidates to best treat an individual patient. We need to integrate algorithms and systems from machine learning, databases, image and text analysis, ontologies, human-computer interaction, graph theory and visualization to tackle these diverse problems. Scale changes everything, and size does matter. Integrating intelligent heuristics with novel computing environments, such as grid and GPU computing, provides scalable platform for these big data challenges. Dr. Hossam Hassanein School of Computing, Queen’s University Biography: Hossam Hassanein is leading research in the areas of broadband, wireless and mobile networks architecture, protocols, control and performance evaluation. His record spans more than 500 publications in journals, conferences and book chapters, in addition to numerous keynotes and plenary talks in flagship venues. Dr. Hassanein has received several recognition and best papers awards at top international conferences. He is also the founder and director of the Telecommunications Research (TR) Lab at Queen’s University School of Computing, with extensive international academic and industrial collaborations. Dr. Hassanein is a senior member of the IEEE, and is the former chair of the IEEE Communication Society Technical Committee on Ad hoc and Sensor Networks (TC AHSN). Dr. Hassanein is an IEEE Communications Society Distinguished Speaker (Distinguished Lecturer 2008-2010). Abstract: “Global Resource Utilization in the Internet of Things” The Internet of Things (IoT) is envisioned as a paradigm shift, with a plethora of applications, on the premise of well-established enabling technologies; prominently Wireless Sensor Networks (WSNs) and RFIDs. The former has evolved to improve energy efficiency and resilient operation, yet, true scalability has only been recently probed and quite sparsely advancing. Moreover, the traditional approach whereby most WSN platforms are tailored for a single-application to meet a given efficiency metric, imposes significant rigidity in re-utilizing devised platforms for new applications, and limitations on re-using previously deployed ones. In remedy, we present a novel paradigm in WSNs to efficiently utilize network resources, and extend it to a platform for multiple applications to cross utilize resources over multiple WSNs. This paradigm presents a leap in scalability, not only in a WSN, but across multiple ones, with dynamicity to accommodate for varying resources being “Global Resource Utilization in the Internet of Things” The Internet of Things (IoT) is envisioned as a paradigm shift, with a plethora of applications, on the premise of well-established enabling technologies; prominently Wireless Sensor Networks (WSNs) and RFIDs. The former has evolved to improve energy efficiency and resilient operation, yet, true scalability has only been recently probed and quite sparsely advancing. Moreover, the traditional approach whereby most WSN platforms are tailored for a single-application to meet a given efficiency metric, imposes significant rigidity in re-utilizing devised platforms for new applications, and limitations on re-using previously deployed ones. In remedy, we present a novel paradigm in WSNs to efficiently utilize network resources, and extend it to a platform for multiple applications to cross utilize resources over multiple WSNs. This paradigm presents a leap in scalability, not only in a WSN, but across multiple ones, with dynamicity to accommodate for varying resources being introduced and removed; in addition to utilizing transient resources in their vicinity. To this end, we present a global architecture to efficiently adopt WSNs in IoT with changing demands and scale. Our approach is further explained and demonstrated via a detailed use case depicting the premise of IoT application. Dr. Monty Newborn School of Computer Science, McGill University Biography: Monty Newborn received his Ph. D. in Electrical Engineering from The Ohio State University in 1967. He was an assistant professor and then associate professor at Columbia University in the Department of Electrical Engineering and Computer Science from 1967-1975. In 1975, he joined the School of Computer Science at McGill University and has been with the School since then, serving as its director from 1976-1983. He has been an ACM Fellow since 1994 and a member of the Canadian Chess Hall of Fame since 2001. His research has focused on search problems in artificial intelligence where two areas are of particular interest: chess-playing programs and automated theoremproving programs. He has published seven books on these subjects and a number of research papers as well. He served as chairman of the ACM Computer Chess Committee from 1981 until 1997. In that capacity he organized the first Kasparov versus Deep Blue match (known as the ACM Chess Challenge) in 1996. The following year he served as head of the officials at the second Kasparov versus Deep Blue match won by Deep Blue. Through the 1970s and 1980s, his chess program Ostrich competed in five world championships, coming close to winning in 1974.