Events

July 4, 2016 at 1:00 p.m. Matthieu Bloch, Associate Professor at Georgia Institute of Technology, will be presenting “What can physical-layer security do for you?”. Speaker: Matthieu Bloch Associate Professor, School of Electrical and Computer Engineering Georgia Institute of Technology Day & Time: Monday, July 4, 2016 1:00 p.m. – 2:00 p.m. Location: Room ENG LG21 245 Church St., Toronto, ON, M5B 2K3 All are welcome – No registration necessary Abstract: The conventional approach to ensure confidential communications relies on public-key/private-key protocols, which operate on error-free data after the physical-layer has been established. While the effectiveness of this approach in traditional settings is unquestionable, new systems are emerging where treating confidentiality as an overlay feature of top of reliability may not be the most appropriate solution. In particular, modern wireless networks, which comprise heterogeneous nodes with limited computational and energy resources, would benefit from the integration by design of confidentiality in the physical-layer, especially if this can be done in a cost-effective way. In this talk, we will provide a perspective on what physical-layer security can realistically do for wireless communication systems. Our objective will be not only to review the challenges faced by physical-layer security but also to present some of our recent research activities in the areas of information theory, coding theory, and wireless systems that suggest potential solutions to overcome these challenges. Biography: Matthieu Bloch is an Associate Professor in the School of Electrical and Computer Engineering. He received the Engineering degree from Supélec, Gif-sur-Yvette, France, the M.S. degree in Electrical Engineering from the Georgia Institute of Technology, Atlanta, in 2003, the Ph.D. degree in Engineering Science from the Université de Franche-Comté, Besançon, France, in 2006, and the Ph.D. degree in Electrical Engineering from the Georgia Institute of Technology in 2008. In 2008-2009, he was a postdoctoral research associate at the University of Notre Dame, South Bend, IN. Since July 2009, Dr. Bloch has been on the faculty of the School of Electrical and Computer Engineering, and from 2009 to 2013 Dr. Bloch was based at Georgia Tech Lorraine. His research interests are in the areas of information theory, error-control coding, wireless communications, and cryptography. Dr. Bloch is a member of the IEEE and has served on the organizing committee of several international conferences; he was the chair of the Online Committee of the IEEE Information Theory Society from 2011 to 2014. He is the co-recipient of the IEEE Communications Society and IEEE Information Theory Society 2011 Joint Paper Award and the co-author of the textbook Physical-Layer Security: From Information Theory to Security Engineering published by Cambridge University Press.

July 27, 2016 at 1:00 p.m. Adam Noel, Postdoctoral Fellow at the University of Ottawa, will be presenting “Finding Common Ground: Channel Analysis and Receiver Models for Diffusive Molecular Communication”. Speaker: Dr. Adam Noel Postdoctoral Fellow University of Ottawa Day & Time: Wednesday, July 27, 2016 1:00 p.m. – 2:00 p.m. Location: Room BA 1200 40 St. George Street, Toronto, M5S 2E4 Contact: Eman Hammad Abstract: Diffusive molecular communication (MC) is a promising strategy for the transfer of information in synthetic networks of “small” devices (on the scale of living cells or smaller). If such devices could communicate, then it would potentially enable applications such as cooperative diagnostics in medicine, bottom-up fabrication in manufacturing, and sensitive environmental monitoring. Results in this domain can also contribute to our understanding of diffusive signaling in natural biological systems and the diseases that develop when the signaling malfunctions. Diffusion based MC for synthetic networks faces challenges such as infinite inter-symbol interference and constrained computational resources in “simple” transceivers, but also interesting opportunities such as the possibility to manipulate the channel response via chemical means. This presentation highlights our contributions to the modeling and analysis of diffusion-based MC systems, including derivations of the channel impulse response and the development of simulation tools. We describe our recent work to find a unifying analytical framework for the two most common but distinct receiver models, where molecules are either absorbed by the receiver surface or passively diffuse through it. We also discuss some of our on-going work to bridge the gap between the realism of existing analytical models and the availability of relevant experimental data. Biography: Adam Noel is a Postdoctoral Fellow at the University of Ottawa. His Ph.D. and postdoctoral work are on the study of molecular communication, where he has focused on channel modeling, system design, and simulation methods. He has received the support of NSERC Postgraduate Scholarships and is currently holding an NSERC Postdoctoral Fellowship. He also received a Best Paper Award at IEEE ICC 2016. Dr. Noel received the B.Eng. degree in Electrical Engineering in 2009 from Memorial University in St. John’s, Newfoundland and Labrador, and both the M.A.Sc. degree in Electrical Engineering and the Ph.D. degree in Electrical and Computer Engineering from the University of British Columbia in 2011 and 2015, respectively. In 2013 he was a Visiting Scientist at the Institute for Digital Communication at Friedrich-Alexander-University in Erlangen, Germany.

August 12, 2016 at 11:00 a.m. Prof. Vishal Monga, Associate Professor at Pennsylvania State University, will be presenting “Sparsity Constrained Estimation Using Spike and Slab Priors”. Speaker: Prof. Vishal Monga Associate Professor, Pennsylvania State University, University Park Day & Time: Friday August 12th, 2016 11:00 a.m. – 12:00 p.m. Location: Room BA 7129 (tentatively) Bahen Centre for Information Technology 40 St George St, Toronto, ON M5S 2E4 Contact: Eman Hammad Abstract: We address sparse signal, i.e. image recovery in a Bayesian estimation framework where sparsity is enforced on reconstruction coefficients via probabilistic priors. In particular, we focus on the popular spike and slab prior which is considered the gold standard in the statistics literature. The optimization problem resulting from this model has broad applicability in recovery, regression and classification problems and is known to be a hard non-convex problem whose existing solutions involve simplifying assumptions and/or relaxations. We propose an approach called Iterative Convex Refinement (ICR) that aims to solve the aforementioned optimization problem directly allowing for greater generality in the sparse structure. Essentially, ICR solves a sequence of convex optimization problems such that sequence of solutions converges to a sub-optimal solution of the original hard optimization problem. Applications will be considered in image classification as well as image reconstruction. Biography: Vishal Monga is a tenured Associate Professor in the School of Electrical Engineering and Computer Science at the Pennsylvania State University in University Park, PA. He was with Xerox Research from 2005-2009 and his doctoral work in Electrical Engineering was completed at the University of Texas, Austin in Aug 2005. His research interests are in computational imaging, statistical signal processing and convex optimization approaches to estimation problems. Prof. Monga is an elected member of the Editorial Board of the IEEE Transactions on Image Processing and the IEEE Signal Processing Letters. Prof. Monga is a recipient of the US National Science Foundation (NSF) CAREER award. Four of his papers have won best paper or Top 10 percent awards at IEEE Signal Processing conferences. He is a 2016 recipient of Joel and Ruth Spira Foundation Teaching Excellence award. He holds 40 US patents.