Keynote & Plenary Speakers

(Speakers listed in name alphabet order)


David E. Culler (NAE member, ACM/IEEE Fellow)

Friesen Professor, University of California, Berkeley, USA

Keynote Talk Title: Once and Future Internet of Everything
Time: 8:30-9:30AM, Wednesday, Feb. 17, 2016


Back in 1999 we forecasted that in 15 years we would have connected essentially all the people on the planet and have the technology to connect all the things. That future is here and busy being reinvented. In this talk we look at key research contributions and interactions with the industrial ecosystem that brought us here. We explore synergies among embedded wireless networks, the maker movement, wearables and phones that are likely to shape a new renaissance of research and innovation as we interconnect people, the physical world, and our societal infrastructures. We consider the role of these developments in the larger quest for sustainability, including zero emission built environments, intelligent transportation, and smart cities.


David Culler is the Freisen Professor Electrical Engineering and Computer Sciences and Faculty Director of CITRIS Sustainable Infrastructures at the University of California, Berkeley. Professor Culler received his B.A. from U.C. Berkeley in 1980, and M.S. and Ph.D. from MIT in 1985 and 1989. He has been on the faculty at Berkeley since 1989. He is a member of the National Academy of Engineering, an ACM Fellow, an IEEE Fellow and was selected for the 2013 Okawa Prize, ACMs Sigmod Outstanding Achievement Award, Scientific American's 'Top 50 Researchers', and Technology Review's '10 Technologies that Will Change the World'. He has received Test-of-Time awards from Sensys, Usenix, NSDI, SIGCOMM, PLDI, HPDC, and ISCA. He was the Principal Investigator of the DARPA Network Embedded Systems Technology project that created the open platform for wireless sensor networks based on TinyOS, and was co-founder and CTO of Arch Rock Corporation and the founding Director of Intel Research, Berkeley. He has done seminal work on networks of small, embedded wireless devices, planetary-scale internet services, parallel computer architecture, parallel programming languages, and high performance communication, and including TinyOS, PlanetLab, Networks of Workstations (NOW), and Active Messages. He has served on Technical Advisory Boards for NSF and for several companies, including Accenture, People Power, Inktomi, ExpertCity (now CITRIX on-line), and DoCoMo USA. He is currently focused on utilizing information technology to address the energy problem and is co-PI on the NSF CyberPhysical Systems projects LoCal and ActionWebs and PI on Software Defined Buildings.


Bernd Girod (NAE/GNAS member, IEEE/EURASIP Fellow)

Robert L. and Audrey S. Hancock Professor, Stanford University, USA

Keynote Talk Title: From Pixels to Information - Recent Advances in Visual Search
8:30-9:30AM, Tuesday, Feb. 16, 2016


Terminator vision, i.e., augmenting our visual perception overlaying extra information, continues to present substantial technical challenges, not the least of which is recognizing and tracking what the user sees reliably, accurately, and in real-time. We review recent advances of algorithms and applications that retrieve information from large databases using images as queries. Remarkable improvements have been achieved over the course of the MPEG-CDVS (Compact Descriptors for Visual Search) standardization. Beyond CDVS lie techniques that continually match video frames against image databases and promise another leap in performance.


Bernd Girod is the Robert L. and Audrey S. Hancock Professor of Electrical Engineering at Stanford University, California. Until 1999, he was a Professor in the Electrical Engineering Department of the University of Erlangen-Nuremberg. His research interests are in the area of image, video, and multimedia systems. He has published over 600 conference and journal papers and 6 books, receiving the EURASIP Signal Processing Best Paper Award in 2002, the IEEE Multimedia Communication Best Paper Award in 2007, the EURASIP Image Communication Best Paper Award in 2008, the EURASIP Signal Processing Most Cited Paper Award in 2008, as well as the EURASIP Technical Achievement Award in 2004 and the Technical Achievement Award of the IEEE Signal Processing Society in 2011. As an entrepreneur, Professor Girod has worked with numerous startup ventures, among them Polycom, Vivo Software, 8x8, and RealNetworks. He received an Engineering Doctorate from University of Hannover, Germany, and an M.S. Degree from Georgia Institute of Technology. Prof. Girod is a Fellow of the IEEE, a EURASIP Fellow, a member of the German National Academy of Sciences (Leopoldina), and a member of the National Academy of Engineering. He currently serves Stanford’s School of Engineering as Senior Associate Dean at Large.


Aggelos K. Katsaggelos (IEEE/SPIE Fellow)

AT&T Professor, Northwestern University, USA

Keynote Talk Title: Learning for Media Computing
8:30-9:30AM, Thursday, Feb. 18, 2016


Learning has made it possible to unleash the power of data. We have moved away from the detailed modeling of a system or a phenomenon of interest thanks to the abundance of data as well as the huge improvements in processing power. With approaches like dictionary learning we can discover linear relationships between the input and output. On the other hand, recent advancements in deep learning have made it possible to discover non-linear relationships. We will address the impact of the recent developments in learning to communications, computing, and networking and discuss future research directions in these topics.


Aggelos K. Katsaggelos received the Diploma degree in electrical and mechanical engineering from the Aristotelian University of Thessaloniki, Greece, in 1979, and the M.S. and Ph.D. degrees in Electrical Engineering from the Georgia Institute of Technology, in 1981 and 1985, respectively. In 1985, he joined the Department of Electrical Engineering and Computer Science at Northwestern University, where he is currently a Professor holder of the AT&T chair. He was previously the holder of the Ameritech Chair of Information Technology (1997–2003). He is also the Director of the Motorola Center for Seamless Communications, a member of the Academic Staff, NorthShore University Health System, an affiliated faculty at the Department of Linguistics and he has an appointment with the Argonne National Laboratory. He has published extensively in the areas of multimedia signal processing and communications (over 250 journal papers, 500 conference papers and 40 book chapters) and is the holder of 25 international patents. He is the co-author of Rate-Distortion Based Video Compression (Kluwer, 1997), Super-Resolution for Images and Video (Claypool, 2007), Joint Source-Channel Video Transmission (Claypool, 2007), and Machine Learning Refined (Cambridge University Press, forthcoming). He has supervised 50 Ph.D. theses so far. He has been teaching the popular course on Coursera “Fundamentals of Digital Image and Video Processing.” Among his many professional activities Prof. Katsaggelos was Editor-in-Chief of the IEEE Signal Processing Magazine (1997–2002), a BOG Member of the IEEE Signal Processing Society (1999–2001), a member of the Publication Board of the IEEE Proceedings (2003-2007), and he is currently a Member of the Award Board of the IEEE Signal Processing Society. He is a Fellow of the IEEE (1998) and SPIE (2009) and the recipient of the IEEE Third Millennium Medal (2000), the IEEE Signal Processing Society Meritorious Service Award (2001), the IEEE Signal Processing Society Technical Achievement Award (2010), an IEEE Signal Processing Society Best Paper Award (2001), an IEEE ICME Paper Award (2006), an IEEE ICIP Paper Award (2007), an ISPA Paper Award (2009), and a EUSIPCO paper award (2013). He was a Distinguished Lecturer of the IEEE Signal Processing Society (2007–2008).


Nitin Vaidya (IEEE Fellow)

Professor, University of Illinois at Urbana-Champaign, USA

Keynote Talk Title: Network-Aware Distributed Algorithms
Time: 8:30-9:30AM, Monday, Feb. 15, 2016


In the past three decades, a large variety of distributed computing problems have been explored, and fundamental limits and optimal algorithms have been identified for many of these problems. Examples include clock synchronization, resource sharing, and consensus or agreement. The distributed algorithms are typically executed by entities that are interconnected by a communication network. Often the past work on distributed algorithms assumes that the network is fully connected. In some cases, incomplete networks topologies are considered, however, the impact of other network characteristics is often ignored.

In this talk, we will discuss some examples of distributed algorithms developed in prior work, and explain why these algorithms do not work well when the assumptions about the underlying network are changed. The examples will include average consensus over lossy wireless links, and consensus over incomplete networks.


Nitin Vaidya received the Ph.D. from the University of Massachusetts at Amherst. He is a Professor of Electrical and Computer Engineering at the University of Illinois at Urbana-Champaign. He has held visiting positions at Technicolor Paris Lab, TU-Berlin, IIT-Bombay, Microsoft Research, and Sun Microsystems, as well as a faculty position at the Texas A&M University. Nitin Vaidya has co-authored papers that received awards at several conferences, including 2015 SSS, 2007 ACM MobiHoc and 1998 ACM MobiCom. He is a fellow of the IEEE. He has served as Editor-in-Chief for the IEEE Transactions on Mobile Computing, and Editor-in-Chief for ACM SIGMOBILE publication MC2R. For more information, please visit


Georgios B. Giannakis (IEEE/EURASIP Fellow)

ADC Chair in Wireless Telecommunications, University of Minnesota, USA

Plenary Talk Title: Learning Tools for Big Data Analytics
13:30-14:30, Tuesday, Feb. 16, 2016


We live in an era of data deluge. Pervasive sensors collect massive amounts of information on every bit of our lives, churning out enormous streams of raw data in various formats. Mining information from unprecedented volumes of data promises to limit the spread of epidemics and diseases, identify trends in financial markets, learn the dynamics of emergent social-computational systems, and also protect critical infrastructure including the smart grid and the Internet’s backbone network. While Big Data can be definitely perceived as a big blessing, big challenges also arise with large-scale datasets. The sheer volume of data makes it often impossible to run analytics using a central processor and storage, and distributed processing with parallelized multi-processors is preferred while the data themselves are stored in the cloud. As many sources continuously generate data in real time, analytics must often be performed “on-the-fly” and without an opportunity to revisit past entries. Due to their disparate origins, massive datasets are noisy, incomplete, prone to outliers, and vulnerable to cyber-attacks. These effects are amplified if the acquisition and transportation cost per datum is driven to a minimum. Overall, Big Data present challenges in which resources such as time, space, and energy, are intertwined in complex ways with data resources. Given these challenges, ample signal processing opportunities arise. This keynote lecture outlines ongoing research in novel models applicable to a wide range of Big Data analytics problems, as well as algorithms to handle the practical challenges, while revealing fundamental limits and insights on the mathematical trade-offs involved.


Georgios B. Giannakis (Fellow’97) received his Diploma in Electrical Engr. from the Ntl. Tech. Univ. of Athens, Greece, 1981. From 1982 to 1986 he was with the Univ. of Southern California (USC), where he received his MSc. in Electrical Engineering, 1983, MSc. in Mathematics, 1986, and Ph.D. in Electrical Engr., 1986. Since 1999 he has been a professor with the Univ. of Minnesota, where he now holds an ADC Chair in Wireless Telecommunications in the ECE Department, and serves as director of the Digital Technology Center. His general interests span the areas of communications, networking and statistical signal processing – subjects on which he has published more than 375 journal papers, 625 conference papers, 20 book chapters, two edited books and two research monographs (h-index 113). Current research focuses on big data analytics, wireless cognitive radios, network science with applications to social, brain, and power networks with renewables.. He is the (co-) inventor of 22 patents issued, and the (co-) recipient of 8 best paper awards from the IEEE Signal Processing (SP) and Communications Societies, including the G. Marconi Prize Paper Award in Wireless Communications. He also received Technical Achievement Awards from the SP Society (2000), from EURASIP (2005), a Young Faculty Teaching Award, the G. W. Taylor Award for Distinguished Research from the University of Minnesota, and the IEEE Fourier Technical Field Award (2015). He is a Fellow of EURASIP, and has served the IEEE in a number of posts including that of a Distinguished Lecturer for the IEEE-SP Society.


Ravishankar K. Iyer (ACM/IEEE/AAAS Fellow)

George and Ann Fisher Distinguished Professor of Engineering, University of Illinois at Urbana-Champaign, USA

Plenary Talk Title: Achieving Resilience via Continuous Monitoring and Deep Analytics
14:30-15:30, Tuesday, Feb. 16, 2016


Above and beyond all the trends and developments in computer system design and implementation, are factors related to new applications domains.. We see an eclectic landscape that presents compelling new research, business and societal challenges - driven by the multi-disciplinary nature of societal problems - at the nexus of food, health, and energy. The next major innovations in computer science and engineering are likely to come from "intelligent" deployment of human-centric systems that must optimally interact with other man-made and natural systems with a focus on seamless availability of dynamic decision-making capabilities. Our need to measure, model, communicate, and manage our vast natural and social enterprise, requires a recognition that our physical world is complex and requires a level of adaptation and resilience that is unprecedented. New creative approaches are essential for handling the problems of scale and complexity envisioned in this future. Applications, such as the smart power grid, medical electronics, robotic management and control, wireless sensor networks, cloud based systems - all driven by advanced data-analytics, have spawned a level of complexity where traditional methods cannot form the backbone for resilient system design. This means that a new set of fault/attack models have to evolve and need to be studied carefully, either by significantly enhancing traditional techniques or by introducing new resiliency methods. Driven by real measurements and observations, this talk will present research directions and challenges related to building resilient applications in several new domains.


Ravishankar K. Iyer is Interim Vice Chancellor for Research at the University of Illinois at Urbana-Champaign, where he is a George and Ann Fisher Distinguished Professor of Engineering. He holds appointments in the Department of Electrical and Computer Engineering and the Department of Computer Science and he is Co-Director of the Center for Reliable and High-Performance Computing at CSL and Chief Scientist at the Information Trust Institute.

Iyer’s research interests are in the area of dependable and secure systems. He has been responsible for major advances in the design and validation of dependable computing systems. He currently leads the TRUSTED ILLIAC project at Illinois, which is developing application-aware adaptive architectures for supporting a wide range of dependability and security requirements in heterogeneous environments. Professor Iyer has a broad outreach to industry and government, both nationally and internationally, having worked with several major vendors.

Professor Iyer is a Fellow the AAAS, the IEEE and the ACM. He has received several awards including the Humboldt Foundation Senior Distinguished Scientist Award for excellence in research and teaching, the AIAA Information Systems Award and Medal for “fundamental and pioneering contributions towards the design, evaluation, and validation of dependable aerospace computing systems,” and the IEEE Emanuel R. Piore Award “for fundamental contributions to measurement, evaluation, and design of reliable computing systems.”


Geoffrey Li (IEEE Fellow)

Professor, Georgia Institute of Technology, USA

Plenary Talk Title: Device-to-Device Communications in Cellular Networks
13:30-14:30, Wednesday, Feb. 17, 2016


To satisfy the increasing demand of high data-rate services, provide better user experience, and alleviate the huge infrastructure investment of operators, device-to-device (D2D) communications have being considered as one of the key techniques in the 5G wireless networks. With D2D communications, proximity users in a cellular network can communicate directly to each other without going through the base station (BS). It can potentially increase spectral-efficiency (SE) and device energy-efficiency (EE) of communications. However, D2D communications may generate interference to the existing cellular network if not designed properly. Therefore, interference management is one of the most challenging and important issues in D2D communications. This talk will focus on interference management in D2D communications including quality-of-service (QoS) aware admission control and SE/EE based mode selection. Cross-layer optimization and concave-convex procedures (CCCP) are exploited to solve the related optimization problems.


Dr. Geoffrey Li is a Professor with the School of Electrical and Computer Engineering at Georgia Institute of Technology. He is also holding a Cheung Kong Scholar title at the University of Electronic Science and Technology of China since 2006. He was with AT&T Labs – Research for five years before joining Georgia Tech in 2000. His general research interests include wireless communications and statistical signal processing. In these areas, he has published over 300 referred journal and conference papers in addition to 26 granted patents. His publications have been cited by over 20,000 times and he has been listed as the World’s Most Influential Scientific Mind, also known as a Highly-Cited Researcher, by Thomson Reuters. He has been an IEEE Fellow since 2006. He received the Stephen O. Rice Prize Paper Award in 2010 and the WTC Wireless Recognition Award in 2013 from the IEEE Communications Society and the James Evans Avant Garde Award in 2013 and the Jack Neubauer Memorial Award in 2014 from the IEEE Vehicular Technology Society. Recently, he won the 2015 Distinguished Faculty Achievement Award from the School of Electrical and Computer Engineering, Georgia Tech.


Ness B. Shroff (IEEE Fellow)

Ohio Eminent Scholar endowed Chair, Ohio State University, USA

Plenary Talk Title: Minimizing Data Retrieval Latency in Cloud Storage Systems
Time: 14:30-15:30, Wednesday, Feb. 17, 2016


We are in the midst of a major data revolution. The total data generated by humans from the dawn of civilization until the turn of the new millennium is now being generated every two days. Driven by a wide range of data-intensive devices and applications, this growth is expected to continue its astonishing march, and fuel the development of new and larger data centers. In order to exploit the low-cost services offered by these resource-rich data centers, application developers are pushing computing and storage away from the end-devices and instead deeper into the data-centers. Hence, the end-users' experience is now dependent on the performance of the algorithms used for data retrieval within the data-centers. In particular, providing low-latency services are critically important to the end-user experience for a wide variety of applications. Our goal has been to develop the analytical foundations and methodologies to enable cloud storage solutions that result in low-latency services. In this talk, I will overview some of the recent research efforts at fast data retrieval in these large-scale data storage systems.


Ness B. Shroff received his Ph.D. degree in Electrical Engineering from Columbia University in 1994. He joined Purdue university immediately thereafter as an Assistant Professor in the school of ECE. At Purdue, he became Full Professor of ECE in 2003 and director of CWSA in 2004, a university-wide center on wireless systems and applications. In July 2007, he joined The Ohio State University, where he holds the Ohio Eminent Scholar endowed chair in Networking and Communications, in the departments of ECE and CSE. From 2009-2012, he served as a Guest Chaired professor of Wireless Communications at Tsinghua University, Beijing, China, and currently holds honorary Guest professorships at Shanghai Jiaotong University in China, and the Indian Institute of Technology, Mumbai. His research interests span the areas of communication, social, and cyberphysical networks. He is especially interested in fundamental problems in the design, control, performance, pricing, and security of these networks.

Dr. Shroff is currently an editor at large of IEEE/ACM Trans. on Networking, and on the editorial board of IEEE Transactions on Control of Networked Systems and the IEEE Networks Magazine. He has chaired various conferences and workshops, and co-organized workshops for the NSF to chart the future of communication networks. Dr. Shroff is a Fellow of the IEEE and an NSF CAREER awardee. He has received numerous best paper awards for his research, e.g., at IEEE INFOCOM 2008, IEEE INFOCOM 2006, Journal of Communication and Networking 2005, Computer Networks 2003 (two of his papers also received runner-up awards at IEEE INFOCOM 2005 and INFOCOM 2013), and also student best paper awards (from all papers whose first author is a student) at IEEE WiOPT 2013, IEEE WiOPT 2012 and IEEE IWQoS 2006.

He received the IEEE INFOCOM achievement award for seminal contributions to scheduling and resource allocation in wireless networks, and is noted on the Thomson Reuters ISI list of highly cited researchers, and in Thomson Reuters Book on The World's Most Influential Scientific Minds in 2014.