Keynote Speakers

Bharat Bhargava is a professor of the Department of Computer Science with a courtesy appointment in the School of Electrical & Computer Engineering at Purdue University. Professor Bhargava is conducting research in security and privacy issues in distributed systems. This involves host authentication and key management, secure routing and dealing with malicious hosts, adaptability to attacks, and experimental studies. His recent work is on Intelligent Autonomous Systems and data analytics and machine learning. It includes cognitive autonomy, reflexivity, deep learning and knowledge discovery. His earlier work on Waxed Prune with MIT and NGC built a prototype for privacy preserving data dissemination in cross-domains. Based on his research in reliability, he is studying vulnerabilities in systems to assess threats to large organizations. He has developed techniques to avoid threats that can lead to operational failures. The research has direct impact on nuclear waste transport, bio-security, disaster management, and homeland security. These ideas and scientific principles are being applied to the building of secure networks and systems.

Professor Bhargava is recipient of seven best paper awards in various international computer science conferences. Professor Bhargava is a Fellow of the Institute of Electrical and Electronics Engineers and of the Institute of Electronics and Telecommunication Engineers. In 1999, he received the IEEE Technical Achievement Award for a major impact of his decade long contributions to foundations of adaptability in communication and distributed systems. He has been awarded the charter Gold Core Member distinction by the IEEE Computer Society for his distinguished service. He received Outstanding Instructor Awards from the Purdue chapter of the ACM in 1996 and 1998. He has graduated the largest number of Ph.D students in CS department and is active in supporting/mentoring minority students. In 2003, he was inducted in the Purdue's Book of Great Teachers. In 2017, he received the Helen Schleman Gold Medallion Award for supporting women at Purdue and Focus award for advancing technology for differently abled students.

He serves on seven editorial boards of international journals. He also served on the IEEE Computer Society on Technical Achievement award and Fellow committees. Professor Bhargava is the founder of the IEEE Symposium on Reliable and Distributed Systems, IEEE conference on Digital Library, and the ACM Conference on Information and Knowledge Management.

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Inderjit Dhillon is the Gottesman Family Centennial Professor of Computer Science and Mathematics at UT Austin, where he is also the Director of the ICES Center for Big Data Analytics. Currently he is on leave from UT Austin and works as Amazon Fellow at A9/Amazon, where he is developing and deploying state-of-the-art machine learning methods for Amazon search. His main research interests are in big data, machine learning, network analysis, linear algebra and optimization. He received his B.Tech. degree from IIT Bombay, and Ph.D. from UC Berkeley. Inderjit has received several awards, including the ICES Distinguished Research Award, the SIAM Outstanding Paper Prize, the Moncrief Grand Challenge Award, the SIAM Linear Algebra Prize, the University Research Excellence Award, and the NSF Career Award. He has published over 175 journal and conference papers, and has served on the Editorial Board of the Journal of Machine Learning Research, the IEEE Transactions of Pattern Analysis and Machine Intelligence, Foundations and Trends in Machine Learning and the SIAM Journal for Matrix Analysis and Applications. Inderjit is an ACM Fellow, an IEEE Fellow, a SIAM Fellow and an AAAS Fellow.

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Title: Understanding Visual Appearance from Micro Scale to Global Scale

Mixed reality environments require understanding scenes, and then seamlessly blending the rich visual appearance of real and virtual materials to create a compelling user experience. In this talk I will describe our work on modeling and recognizing complex materials, and visual recognition. Using these algorithms as core building blocks we can understand appearance at a global scale by mining social media to discover visual patterns across geography and time. This talk will describe our work on understanding global fashion styles and trends.

Kavita Bala is the Chair of the Computer Science Department at Cornell University. She received her S.M. and Ph.D. from the Massachusetts Institute of Technology (MIT), and her B.Tech. from the Indian Institute of Technology (IIT, Bombay). She was a post doctoral researcher at the Program of Computer Graphics. She co-founded GrokStyle (acquired by Facebook), and is a faculty Fellow with the Atkinson Center for a Sustainable Future. Bala specializes in computer vision and computer graphics, leading research in recognition and visual search using deep learning; material modeling and acquisition using physics and learning; realistic, physically-based rendering; and material and lighting perception. Bala's work on scalable rendering, Lightcuts, is the core production rendering engine in Autodesk's cloud renderer; and her instance recognition research is the core technology of GrokStyle's visual search engine. Her work on 3D Mandalas was featured at the Rubin Museum of Art, New York.

Bala serves on SIGGRAPH's Papers Advisory Group (PAG). Bala has served as the Editor-in-Chief of Transactions on Graphics (TOG), on the Papers Advisory Board for SIGGRAPH and SIGGRAPH Asia, and as Associate Editor for TOG (Transactions on Graphics), TVCG (Transactions on Visualization and Computer Graphics) and CGF (Computer Graphics Forum). Bala has co-authored the graduate-level textbook "Advanced Global Illumination" (A K Peters publisher, second edition). She has chaired SIGGRAPH Asia 2011, and co-chaired Pacific Graphics (2010) and the Eurographics Symposium on Rendering (2005).

Bala has received the NSF CAREER award, Cornell's College of Engineering Fiona Li and Donald Li Excellence in Teaching Award (2015), James and Mary Tien Excellence in Teaching Award (2006 and 2009), and the Affinito-Stewart award.

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Title: Determinism and energy efficiency in Industrial IoT

Industrial applications, such as smart grid, smart manufacturing or automotive industry applications, require ultra low-latency, ultra low-power consumption and high network reliability. The Time Slotted Channel Hopping (TSCH) mode of IEEE802.15.4 can provide these characteristics; however, as all the wireless technologies, it is prone to internal and external interference. A number of techniques to mitigate or avoid potential collisions since the formation of the network is described. Moreover, promising wireless power transfer methods are introduced to provide energy efficiency and even power autonomy to Industrial Internet of Things (IIoT) applications.

Christos Douligeris, currently a professor at the department of Informatics, University of Piraeus, Greece held positions with the Department of Electrical and Computer Engineering at the University of Miami. He was an associate member of the Hellenic Authority for Information and Communication Assurance and Privacy and the President and CEO of Hellenic Electronic Governance for Social Security SA.Dr. Douligeris has published extensively in the networking scientific literature and he has participated in many research and development projects. He is the co-editor of a book on ‘‘Network Security’’ published by IEEE Press/ John Wiley and he is on the editorial boards of several scientific journals as well as on the technical program committees of major international conferences.

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Raghu Kacker is a mathematical statistician in the Mathematical and Computational Sciences Division (MCSD) of the Information Technology Laboratory (ITL) of the National Institute of Standards and Technology (NIST). He received his Ph.D. in statistics from the Iowa State University in 1979. After one year on the faculty of Virginia Tech in Blacksburg, he worked for seven years in the former AT&T Bell Laboratories in New Jersey. He joined NIST in 1987. His current interests include evaluation of uncertainty in physical and virtual measurements, quantification of uncertainty from bias, combining information from interlaboratory evaluations and multiple methods of measurement, meta-analysis of clinical trials, measurement equations, Bayesian uncertainty, linear models and variance components, industrial statistics, quality engineering, and Taguchi methods. He is a Fellow of the American Statistical Association and a Fellow of the American Society for Quality. He was elected member of the International Statistical Institute. He has received Bronze medal from the U.S. Department of Commerce and Distinguished Technical Staff Award from the AT&T Bell Laboratories. He was member of an NIST team that developed software to assay large parallel processing programs, which won R&D 100 award. He is a member of the editorial boards of the journals Total Quality Management and Journal of Applied Statistics.

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Prof. Soundar Kumara is Allen E. Pearce and Allen M. Pearce Professor of Industrial Engineering, Penn State College of Engineering, USA.

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Sanjay Ranka is a Professor in the Department of Computer Information Science and Engineering at University of Florida. His current research interests are high performance and parallel computing with a focus on energy efficiency; and big data science with a focus on data mining/machine learning algorithms for spatiotemporal applications. His work is driven by applications in CFD, remote sensing, health care and transportation. He teaches courses on data science (three course curriculum), data mining and parallel computing.

From 1999-2002, he was the Chief Technology Officer at Paramark (Sunnyvale, CA). At Paramark, he developed a real-time optimization service called PILOT for marketing campaigns. PILOT served more than 10 million optimized decisions a day in 2002 with a 99.99% uptime. Paramark was recognized by VentureWire/Technologic Partners as a top 100 Internet technology company in 2001 and 2002 and was acquired in 2002. He has also held positions as a tenured faculty positions at Syracuse University and as a researcher/visitor at IBM T.J. Watson Research Labs and Hitachi America Limited.

Sanjay earned his Ph.D. (Computer Science) from the University of Minnesota and a B. Tech. in Computer Science from IIT, Kanpur, India. He has coauthored four books, 250+ journal and refereed conference articles. His recent co-authored work has received a best student paper runner up award at IGARSS 2015, best paper award at BICOB 2014, best student paper award at ACM-BCB 2010, best paper runner up award at KDD-2009, a nomination for the Robbins Prize for the best paper in journal of Physics in Medicine and Biology for 2008, and a best paper award at ICN 2007.

He is a fellow of the IEEE and AAAS, and a past member of IFIP Committee on System Modeling and Optimization. He is an associate Editor-in-Chief of the Journal of Parallel and Distributed Computing and an associate editor for ACM Computing Surveys, IEEE/ACM Transactions on Computational Biology and Bioinformatics, Sustainable Computing: Systems and Informatics, Knowledge and Information Systems, and International Journal of Computing. He is also an edittorial board member of Applied Sciences (Compuing and Artificial Intelligence). Additionally, he is a book series editor for CRC Press for Bigdata. In the past, he has been an associate editor for IEEE Transactions on Parallel and Distributed Systems and IEEE Transactions on Computers.

He was a past member of the IFIP Committee on System Modeling and Optimization, Parallel Compiler Runtime Consortium, the Message Passing Initiative Standards Committee and Technical Committee on Parallel Processing. He is the program chair for 2015 High Performance Computing, 2013 International Parallel and Distributed Processing Symposium, 2010 International Conference on Contemporary Computing and co-general chair for 2009 International Conference on Data Mining and 2010 International Conference on Green Computing.

Sanjay has had consulting assignments with a number of companies (AT∧T Wireless, IBM, Hitachi) and has served as an expert witness in patent disputes. He is a series editor for CRC press on Bigdata. His work has received 10000+ citations with an h-index of 49 (based on Google Scholar).

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