Aidong Zhang (National Science Foundation and State University of New York at Buffalo)
Title: Dynamic Tracking and Analysis of Massive Time Series Data
Abstract: As massive amount of time series data becomes available and continues to grow, we are now coming to see how such data may be used to gain a better understanding of our life. The biggest challenges facing the field are not generating or even storing such data, but, rather, in developing computational methods and tools that will optimize their use. This is particularly important for data that is generated over time, which will allow us to monitor the progression or trend of the data. Having tools to reap the maximum benefit from time-series data will revolutionize our understanding of many dynamic applications. Indeed, temporal information in time series data can be used to reveal many important phenomena such as bursts of activities in social networks and evolution of functional modules in protein interaction networks. In this talk, I will present a few computational approaches to demonstrate how to tackle the challenging issues raised by massive time series data. I will focus on tracking the progression of a group of objects and individual interactions between objects, and on analyzing the roles of these objects and their interactions in dynamic time series data. Through identifying these objects and interactions in the progression process, we are able to detect the critical groups that are responsible for the transition of important features in the data, such as evolution of communities in social networks and progression of cancer stages in medicine. I will discuss various applications which generate and can benefit from tracking and analyzing time series data.
Bio: Dr. Aidong Zhang is currently on leave from the State University of New York (SUNY) at Buffalo and serving as a program director in the Information & Intelligent Systems division of the Directorate for Computer & Information Science & Engineering, National Science Foundation. Dr. Zhang is a SUNY Distinguished Professor of Computer Science and Engineering. Her research interests include data mining/data science, bioinformatics, health Informatics, multimedia and database systems, and content-based image retrieval. She has authored over 280 research publications in these areas. She has chaired or served on over 150 program committees of international conferences and workshops, and currently serves on several journal editorial boards. She has published two books “Protein Interaction Networks: Computational Analysis” (Cambridge University Press, 2009) and “Advanced Analysis of Gene Expression Microarray Data” (World Scientific Publishing Co., Inc. 2006). Dr. Zhang is an IEEE Fellow and is also a recipient of the SUNY Chancellor's Research Recognition award.
Jian Pei (Simon Fraser University, Canada)
Title: Building Data Science Tools and Platforms for Business Applications
Abstract: In the last several years, we have conducted in-depth data science research in several exciting applications, such as health informatics. We built a series of tools for our industry partners to analyze and explore transaction, spatial, temporal and social data, and conduct contrast aspect analysis, viral marketing analysis, benchmark analysis, fraud detection, investigation and management, early prediction, and population index analysis. In this talk, I will present a brief overview of our data science analytics platform, and showcase some recent technical breakthroughs in contrast aspect analysis and continuous influence maximization for viral marketing, as well as their successful applications in industry.
Bio: Jian Pei is currently a Canada Research Chair in Big Data Science, a professor in the School of Computing Science and the Department of Statistics and Actuarial Science at Simon Fraser University, Canada. His expertise is in developing business driven, technology enabled data analytics for critical applications. His publications have been cited by more than 56,000 in literature, and by more than 28,000 since 2011. He is also active in providing consulting service to industry and transferring the research outcome in his group to industry and applications. He is the founding director of the Pacific Blue Cross Health Informatics Laboratory. His leadership in creating industry relationship was highlighted by national news media. He is an editor of several esteemed journals in his areas and a passionate organizer of the premier academic conferences defining the frontiers of the areas. He received a few prestigious awards, including the 2014 IEEE ICDM Research Contributions Award and the 2015 ACM SIGKDD Service Award. He is a fellow of both ACM and IEEE.
Ning So Head of Technical Service and Support at Reliance Jio Global Resources, the largest communications service provider of India
Title: Relational Database and Graph Database: can they co-exist in the DevOps environment and how
Abstract: Today’s DevOps environment constantly pushes the boundaries of Cloud Control and Management systems. One of the fast developing requirement evolves around the rapid Cloud infrastructure resources recognition, optimization computation, and resources acquisition. This requirement has several unique characteristics that have not been encountered before, or at a much smaller skill. The Cloud infrastructure consist of network, compute, and storage resources. While some of them are best described as discrete objects with various attributes, the others are best described as connected domains. The former is best to be stored in a traditional relational database, while the latter is best to be stored in a graph database. However, all the resources can be used inter-changeably, thus they should be stored in a single database, or at least present themselves to the resource computation algorithms in unison to achieve optimized results. This talk will talk about the Cloud environment and the DevOps requirement in an actual use case, and describe the perceived challenges with real examples.
Bio: Ning So is Head of Technical Service and Support at Reliance Jio Global Resources, the largest communications service provider of India. Before he joined Reliance in 2016, he was the CEO and co-founder of Vinci Systems Inc., a software development and technical consulting company specializes in developing end-to-end comprehensive Cloud infrastructure solution using SDN and NFV technologies for global Tier 1 Carriers and Cloud operators. Ning is a pioneer, thought-leader, and one of the main contributors to communication industry’s SDN and NFV revolution since 2008, including its concept formulation, use case definition, framework establishment, and requirement refinement, all the way to the business case proposal, technology development, and lab trial. He is a member of NFV & SDN World Congress Advisory Panel, in recognition of his significant contribution to the industry and academia in the field of SDN and NFV.