22nd ACM MSWiM 2019

Keynote Speakers

In addition to scientific papers, the MSWiM 2019 program includes distinguished Keynote Speakers.



Title: A Vision towards Pervasive Edge Computing

Yuanyuan Yang
Distinguished Professor
Stony Brook University, USA

Program Director, US National Science Foundation


Abstract: This talk presents an emerging pervasive edge computing paradigm where heterogeneous mobile edge devices (e.g., smartphones, tablets, IoT and vehicles) can collaborate to sense, process data and create many novel applications at network edge. We propose a data centric design where data become self-sufficient entities that are stored, referenced independently from their producers. This enables us to design efficient and robust data discovery, retrieval and caching mechanisms. The future research agenda including scalable data discovery, cache management, autonomous processing, trust, security and privacy, incentives and semantic data naming) will be discussed.

Short Bio: Yuanyuan Yang received the BEng and MS degrees in computer science and engineering from Tsinghua University, Beijing, China, and the MSE and PhD degrees in computer science from Johns Hopkins University, Baltimore, Maryland, USA. Dr. Yang is a SUNY Distinguished Professor in the Department of Electrical & Computer Engineering and Department of Computer Science at Stony Brook University, New York, USA. She is currently on leave serving as a Program Director at the US National Science Foundation. She has served as the Associate Dean for Academic Affairs of College of Engineering and Applied Sciences at Stony Brook University and a Division Director of New York State Center of Excellence in Wireless and Information Technology.
Dr. Yang is internationally recognized for her contributions in parallel & distributed computing systems and networking. She was named an IEEE Fellow in 2009 for contributions to the area. Her current research interests include cloud computing, edge computing and mobile computing. Her research group currently develops data center architectures and virtual machine placement algorithms in cloud computing systems, data discovery/retrieval/caching mechanisms in edge computing systems, and wireless energy-charging algorithms and mobile data gathering mechanisms in wireless rechargeable sensor networks.


 
 
 

Title: A Roadmap for the Acceleration of Technology in Computational Science for the next Decade

S.S. Iyengar, Ph.D.
Distinguished University Professor
Director and Ryder Professor
Florida International University


Abstract: This talk covers a detailed direction for developing a Roadmap in the discipline of Computer Science for the next Decade. Over the past two decades, the science of computing has changed drastically both in the context of theory and applications. Dr. Iyengar is going to cover his experiences of four decades in areas of Sensor Fusion, Quantum Computing and theory of Machine Learning and AI for various applications. The duration of the talk is 1 hour and there will be time for discussions after the seminar.
For more details refer to the WebPage: Here

Short Bio: Dr. S. S. Iyengar, PhD, D.Sc (h.c.), (ACM Fellow, IEEE Fellow, AAAS Fellow, NAI Fellow, AIMBE Fellow) is a pioneer in the field of distributed sensor nerworks/sensor fusion, computational aspects of robotics and high performance computing. He has published over 600 research papers and has authored/edited 22 books published by MIT Press. John Wiley \& Sons, Prentice Hall, CRC Pres, Springer Verlag, etc. These publications have been used in major universities all over che world. He has many patents and some patentents are featured in the World's Best Technology Forum in Dallas, Texas. His research publications are on the design and analysis of efficient algorithms, parallel computing, sensor networks, and robotics. Daring the last four decades has supervised over 55 Ph.D. students, 100 Master's students, and many undergraduate studenes who are now faculty at Major Universities worldwide or Scientists or Engincers at National Lab/Industries around the woeld. He has also had many undergraduate stadents working on his research projects.
Dr. lyengar is a member of the European Academy of Sciences, a Life Fellow of IEEE, a Fellow of ACM, a Fellow of AAAS, a Fellow of the National Academy of Inventors NAI and a Fellow of Society of Design and Process Program (SPDS), Fellow of Institution of Engineers (FIE), a Fellow of the American Instituse for Medical and Biological Engineering (AIMBE), was warded a Distinguished Alumnus Award of the Indian Institute of Science, Bangalore, and the IEEE Computer Society Technical Achievement for the contributions to sensor fusion algorithms, and parallel algorithms. He also received the IBM Distinguished Faculkty Award, NASA Fellowship Summer Awards at Oakridge National Lab and the Jet Propulsion Lboratory. He is a Village Fellow of the Academy of Transdisciplinary Learning and Advanced Studies in Austin, Texas, 2010. Dr. lyengar was bonored by the Institute of Electrical and Electronics Engineers" (IEEE) Cybermatics Congress in Atlanta, Georgia, where he received the Outstanding Research Award known as the "Test of Time Award" for his work in creating the Brooks-lyengar Algorithm (2019).
He has also received various national and international awards including the Times Network NRI (Non-Resident Indian) of the Year Award for 2017, a presigious award for Global Indian leaders received out of five thousand nominations; the most distinguished Ramamoorthy Award at the Sociery for Design and Process Science (SDPS 2017): the National Academy of Inventors Fellow Award in 2013: the NRI Mahatma Gandhi Pradvasi Medal at the House of Lords in London in 2013: a Lifetime Achievement Award conferred by International Society of Agile Manufacturing (ISAM) in recognition of his illustrious career in teaching, research and administracion and a lifelong contribution to the fields of Engineering and Computer Science at Indian Institute of Technology (BHU). In 2012, lyengar and Nulogix were awarded the 2012 Innovation-2-Industry (i2i) Florida Award. Iyengar received a Distinguished Research Award from Xaimen Uiversity, China for his rescarch in Sensor Networks, Computer Vision and Image Processing. lyengar's landmark contributions with his research group include the development of grid coverage for surveillance and target location in distributed sensor networks and the Beooks Iyengar fusion algorithm. He has also been awarded Honorary and Doctorate of Science and Engineering Degree. He serves on the advisory board of many corporations and universities around the world. He has served on many National Science Boards such as NIH - National Libeary of Medicine in Bioinformatics, National Science Foundation review panel, NASA Space Science, Department of Homeland Security, Office of Naval Security, and many ochers. His contribution to the US Naval Research Laboratory was a centerpiece of a pioneering effort to develop image analysis for science and technology and to expand the goals of the US Naval Research Laboratory.
The impact of his research contributions can be seen in companies and National Labs like Raytheon, Telecordia, Motorola, the United States Navy, DARPA, and other US agencies. His contribution in DARPAS's program demonstration with BBN, Cambridge, Massachussetts, MURI, researchers from PSU/ARL, Duke, University of Wisconsin, UCLA, Cornell university and LSU has been significant He is also the founding Editor of the International Journal of Distributed Sensor Networks. He has been on the editorial board of many journals and is also a PhD Committee Member at various universities, including CMU, Duke University, and many others throughout the world. He is presently the Editor of ACM Computing Surveys and ocher journals. He is also the founding director of the FIU's Discovery Laboratory. His research work has been cited extensively. His fundamental work has been transitioned into unique technologies. All through his four-decade long professional career, Dr. Iyengar has devoted and employed mathematical morphology in a unique way for quantitative understanding of computational processes for many applications.