Dr. Mohamed Bakr

Mohamed H. Bakr received a B.Sc. degree in Electronics and Communications Engineering from Cairo University, Egypt in 1992 with distinction (honors). In June 1996, he received a Master's degree in Engineering Mathematics from Cairo University. In 1997, he was a student intern with Optimization Systems Associates (OSA), inc. From 1998 to 2000, he worked as a research assistant with the Simulation Optimization Systems (SOS) research laboratory, McMaster University, Hamilton, Ontario, Canada. He earned the Ph.D. degree in September 2000 from the Department of Electrical and Computer Engineering, McMaster University. In November 2000, he joined the Computational Electromagnetics Research Laboratory (CERL), University of Victoria, Victoria, Canada as an NSERC Post Doctoral Fellow. Dr. Bakr received a Premier’s Research Excellence Award (PREA) from the province of Ontario, Canada, in 2003. He also received an NSERC Discovery Accelerator Supplement (DAS) award in 2011. His research areas of interest include optimization methods, computational electromagnetics, computer-aided design and modeling of microwave circuits and photonic devices, nanotechnology, neural network applications, smart analysis of high frequency structures and efficient optimization using time/frequency domain methods. He is currently working as professor with the Department of Electrical and Computer Engineering, McMaster University. He is the author/coauthor of over 200 journal and conference papers, one book on engineering optimization, two book chapters on optimization and electromagnetic modeling, and two patents.

Topic of Keynote: Optimization of Time-Intensive Electromagnetic Structures Using Adjoint Sensitivities

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Dr. Aparicio Carranza

Dr. Aparicio Carranza is an Associate Professor in the Department of Computer Engineering Technology, New York City College of Technology (NYCCT), of the City University of New York (CUNY), Brooklyn, New York, and adjunct instructor at State University of New York (SUNY) at New Paltz. His research involves cybersecurity and Technology Education, Software Defined Networking (SDN), Virtualization and Cloud Computing, and Linux clustering. He serves as an advisory council to four colleges (Vaughn College of Aeronautics and Technology, New York; DeVry University, New York; Technical Career Institute College of Technology, New York; and SUNY Rockland Community College) and was chair of his department from 2007 to 2013. Dr. Carranza earned a doctorate in electrical engineering from The Graduate School and University Center — CUNY; Bachelor of Science in Electrical Engineering (summa cum laude) and Master of Science in Electrical Engineering from The City College of New York — CUNY; and an Associate of Applied Science in Electronics Circuits and Systems (summa cum laude) from Technical Career Institutes of New York. Dr. Carranza joined the Computer Engineering Technology Department of New York City College of Technology as fulltime faculty in fall 2000. For several years he worked as an engineer and scientist at the Development Division of IBM Corporation in Poughkeepsie, New York. He teaches analog electronics, digital electronics, Networking, Programming Languages (MATLAB, C, C++, Java and Python), engineering analysis, data communications, engineering design and other related courses.

Topic of Keynote: Integration of Methods to Implement a Hybrid Flipped Classroom for Cybersecurity Education

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Dr. Bipin C. Desai

Dr. Desai is a professor in the CSE Department of Concordia University. He has degrees from Jadavpur, Purdue and McGill universities. He has over his career worked at General Electric, B&L, CAE industries, Loyola College and since its inception Concordia University. He has published numerous articles in journal and conference proceedings and lectured in Europe, North America and Asia. He is the general chair of two international conferences series: IDEAS and C3S2E.

Topic of Keynote: Data Singularity

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Dr. Abdel Aziz Farrag

Dr. Farrag is currently a professor in the Faculty of Computer Science at Dalhousie University, Halifax, NS, Canada. His research areas are fault tolerance, theoretical computer science and databases. He has published, refereed and his work is frequently cited in the top-ranked journals in his fields, including IEEE-TSE, ACM-TODS, Networks, IEEE-TPDS, Parallel Computing (among others).

Topic of Keynote: Designing and Reconfiguring Fault-tolerant Graphs for Multicomputer Networks

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Dr. Ziad Kobti

Dr. Ziad Kobti is a full professor and director of the School of Computer Science at the University of Windsor, Ontario, Canada. He received his Ph.D. from Wayne State University, Michigan (2004), specializing in modeling hierarchical human social networks and cultural evolution. He received his B.Sc. Honors with a double major in Biological and Computer Sciences (1996) and an M.Sc. in Computer Science (1999) from the University of Windsor. He is an active researcher and lecturer at the University of Windsor and a past researcher at the Artificial Intelligence Laboratory at Wayne State University and the Department of Anthropology at Washington State University.

His research interests include evolutionary computation, particularly individual and population based models such as Cultural Algorithms in general optimization and applications. He is pioneering the use of cultural algorithms as a framework to enable social evolution in artificial models of human populations and knowledge based interactions. He received past funding from the National Science Foundation for work on modeling complex human ecosystems of the Village Ecodynamics Project and the NSERC for extending the development of cultural adaptation models. He is the current executive vice-president and former secretary to the Canadian Association for Artificial Intelligence (CAIAC.ca). He is a regular promoter of Computer Science education to the youth in Ontario, including funded initiatives by Google to work with secondary school educators in South-Western Ontario.

Industrial work experience includes programmer/analyst positions on large scale corporate software systems and independent IT consultant. Recent projects include decision support systems and intelligent agent modeling in healthcare automotive safety funded by the Canadian Institute of Health Research (CIHR), Auto21 Network Centres for Excellence (NCE) as well as pioneering computational models for artificial societies through NSERC. Profiled projects include a national award winning critical-time client/server and distributed database software solution for the emergency freight trucking industry, government funded civil and environmental engineering software, technical educator and corporate trainer in community college and industry.

Topic of Keynote: Motivating social community detection with Cultural Algorithms

Keynote Abstract

Dr. Bijan Raahemi

Bijan Raahemi received his Ph.D. in Electrical and Computer Engineering from the University of Waterloo, Canada, in 1997. He is an Associate Professor of Information Systems at the Telfer School of Management, University of Ottawa, Canada, with cross-appointment with the School of Electrical Engineering and Computer Science. Dr. Raahemi has established the Knowledge Discovery and Data mining (KDD) lab at the University of Ottawa where researchers from the multidisciplinary areas of Computer Science, Computer Engineering, Systems Science, and E-Business Technologies focus on novel techniques in data analytics and machine learning, as well as their emerging applications in healthcare, engineering, and business. Prior to joining the University of Ottawa, Dr. Raahemi held several research positions in Telecommunications industry, including Nortel Networks and Alcatel-Lucent, focusing on Computer Networks Architectures and Services. His current research interests include Big Data Analytics, Machine Learning, and Information Systems. Dr. Raahemi’s research has appeared in peer-reviewed journals and conference proceedings. He also holds several patents in Data Communications. Dr. Raahemi is a senior Member of the Institute of Electrical and Electronics Engineering (IEEE), and a member of the Association for Computing Machinery (ACM).

Topic of Keynote: Data Analytics in Healthcare

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Dr. David Wei

David S.L. Wei received his Ph.D. degree in Computer and Information Science from the University of Pennsylvania in 1991. He is currently a Professor of Computer and Information Science Department at Fordham University. From May 1993 to August 1997 he was on the Faculty of Computer Science and Engineering at the University of Aizu, Japan (as an Associate Professor and then a Professor). Dr. Wei has authored and co-authored more than 100 technical papers in the areas of distributed and parallel processing, wireless networks and mobile computing, optical networks, peer-to-peer communications, cognitive radio networks, and cloud computing in various archival journals and conference proceedings. He served on the program committee and was a session chair for several reputed international conferences. He was a lead guest editor of IEEE Journal on Selected Areas in Communications for the special issue on Mobile Computing and Networking, a lead guest editor of IEEE Journal on Selected Areas in Communications for the special issue on Networking Challenges in Cloud Computing Systems and Applications, a guest editor of IEEE Journal on Selected Areas in Communications for the special issue on Peer-to-Peer Communications and Applications, and a lead guest editor of IEEE Transactions on Cloud Computing for the special issue on Cloud Security. He was the chair of Intelligent Transportation Forum of Globecom 2010, the general chair of Intelligent Transportation Workshop of ICC 2011, and the chair of Cloud Security Forum and Intelligent Transportation Forum of Globecom 2011. He is currently an Associate Editor of IEEE Transactions on Cloud Computing and an Associate Editor of Journal of Circuits, Systems and Computers. Currently, Dr. Wei focuses his research efforts on cloud computing, big data, IoT, and cognitive radio networks.

Topic of Keynote: Technologies that Enhance Cloud Computing Performance

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