The 4th IEEE International Conference on Cyber Security and Cloud Computing
(IEEE CSCloud 2017)
June 26-28, 2017, New York, USA.

Keynote Speakers

Dr. Jian Pei
Professor, Simon Fraser University,
Canada Research Chair in Big Data Science
ACM Fellow, IEEE Fellow

Bio: Jian Pei is a Canada Research Chair (Tier 1) in Big Data Science and a Professor in the School of Computing Science at Simon Fraser University. He is also an associate member of the Department of Statistics and Actuarial Science, Faculty of Science, and Faculty of Health Sciences. During his current sabbatical leave, he is acting as the Chief Data Scientist and a Technical VP of Huawei Technologies. He is a well known leading researcher in the general areas of data science, big data, data mining, and database systems. His expertise is on developing effective and efficient data analysis techniques for novel data intensive applications. At the same time, he is also renowned for his professional leadership. He is one of the most cited authors in data mining, database systems, and information retrieval. Since 2000, he, with H-index 73, has published one textbook, two monographs and over 200 research papers in refereed journals and conferences, which have been cited by more than 67,000 in literature. His research has generated remarkable impact substantially beyond academia. For example, his algorithms have been adopted by industry in production and by popular open source software suites. He is the recipient of several prestigious awards, such as the IEEE ICDM Research Contributions Award and the ACM SIGKDD Service Award. He is an ACM Fellow and an IEEE Fellow.

Topic: Enabling AI Applications by Network Analysis and Mining: from Algorithms to Systems and from Academia to Industry

Abstract: Unprecedentedly more and more AI applications are enabled by network analysis and mining. Many new algorithms have been proposed, partly by academic research, and are adopted actively by industry. Those algorithms extract knowledge at the macro and micro levels. When applying those algorithms to problems in practice, a series of challenges ranging from algorithms to systems need to be addressed. In this talk, I will conduct a random walk and present a few anecdotes about related topics on algorithm and system aspects and from academia and industry angles, such as implementability of network analysis algorithms, building industry scale cloud-based graph computing engines, integration and exchange of graph data, and driving business actions using network analysis and mining.

Dr. Weisong Shi
Professor, Wayne State University,
Charles H. Gershenson Distinguished Faculty Fellow,
IEEE Fellow

Bio: Weisong Shi is a Charles H. Gershenson Distinguished Faculty Fellow and a Professor of Computer Science at Wayne State University. There he directs the Mobile and Internet SysTems Laboratory (MIST) and the Data Science Initiative and Wireless Health Initiative, investigating performance, reliability, power- and energy-efficiency, trust and privacy issues of networked computer systems and applications. Dr. Shi was on leave with the National Science Foundation as a Program Director in the Division of Computer and Network Systems, Directorate of Computer and Information Science and Engineering during 2013 – 2015, where he was responsible for the Computer and Network Systems (CNS) Core CSR Program, and two key crosscutting programs, including Cyber-Innovation for Sustainability Science and Engineering (CyberSEES), Smart and Connected Health (SCH). He is the founding steering committee chair of IEEE/ACM Symposium on Edge Computing (SEC) and Connected Health (CHASE) conference. He is an IEEE Fellow and an ACM Distinguished Scientist. More information can be found at

Topic: Edge Computing: Vision and Challenges

Abstract: The proliferation of Internet of Things and the success of rich cloud services have pushed the horizon of a new computing paradigm, Edge computing, which calls for processing the data at the edge of the network. Edge computing has the potential to address the concerns of response time requirement, battery life constraint, bandwidth cost saving, as well as data safety and privacy. In this talk, he will discuss the vision and challenges of Edge Computing.

Dr. Samee U. Khan
Program Director, National Science Foundation,
North Dakota State Universit,
IET Fellow, BCS Fellow

Bio: Samee U. Khan received a PhD in 2007 from the University of Texas, Arlington, TX, USA. Currently, he is a Program Director at the National Science Foundation, where he is responsible for the Smart & Autonomous Systems program, Critical Resilient Interdependent Infrastructure Systems and Processes program, and Computer Systems Research cluster. He also is a faculty at the North Dakota State University, Fargo, ND, USA. Prof. Khan’s research interests include optimization, robustness, and security of computer systems. His work has appeared in over 350 publications. He is on the editorial boards of leading journals, such as IEEE Access, IEEE Communications Surveys and Tutorials, IET Wireless Sensor Systems, Scalable Computing, IET Cyber-Physical Systems and IEEE IT Pro. He is an ACM Distinguished Speaker, an IEEE Distinguished Lecturer, a Fellow of the Institution of Engineering and Technology (IET, formerly IEE), and a Fellow of the British Computer Society (BCS).

Topic: Cloud and Beyond

Abstract: Cloud computing brought with itself a promise to revolutionize computing. In many aspects it did, but it many other aspects it evolved into something bigger and more user centric. In this talk, we will revisit some of the original promises of cloud computing and in retrospect discuss emerging topics of edge computing, Internet of Things, and Smart Systems. In the latter portion of the talk, we will revisit some relevant National Science Foundation programs pertaining to the various domain topics discussed.