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Time-varying Nonlinear Models of Human Heartbeat Dynamics

August 12, 2016 at 12:00 p.m. Gaetano Valenza, M.Eng., Ph.D., will be presenting “Time-varying Nonlinear Models of Human Heartbeat Dynamics”. Speaker: Dr. Gaetano Valenza Assistant Professor, University of Pisa Harvard Medical School/MGH, Boston, USA Day & Time: Friday, August 12, 2016 12:00 p.m. – 1:00 p.m. Location: UC-Lecture Theater (Basement) Toronto Rehab – University Centre 550 University Ave., Toronto, M5G 2A2 Contact: Azadeh Yadollahi For Registration: https://meetings.vtools.ieee.org/m/40511 Abstract: The application of nonlinear and time-variant systems theory to physiology and medicine has provided meaningful information for a wide range of biological processes and their disease-related aberrations. However, focusing on the cardiovascular system, information that can be extracted by quantifying second-order moments of time-varying heartbeat dynamics are often neglected. To this extent, we introduce a mathematical framework including instantaneous estimates defined in the time and frequency domains, as well as instantaneous complexity and higher-order statistics. Results from exemplary studies involving healthy subjects, as well as patients with Congestive Heart Failure, Major Depression Disorder, Parkinson’s Disease, and Post-Traumatic Stress Disorder will be presented. Multivariate analysis involving brain dynamics during visual affective elicitation will also be presented. Biography: Gaetano Valenza, M.Eng., Ph.D., is currently an Assistant Professor of Bioengineering at the University of Pisa, Pisa, Italy. In 2009, He started working at the Bioengineering and Robotics Research Centre “E. Piaggio” in Pisa and, in 2011, He joined the Neuro-Cardiovascular Signal Processing unit within the Neuroscience Statistics Research Laboratory at Massachusetts Institute of Technology, Cambridge, USA. In 2013, He received the Ph.D. degree in Automation, Robotics, and Bioengineering from the University of Pisa and, in the same year, was appointed as a Research Fellow at Harvard Medical School/ Massachusetts General Hospital, Boston, USA. His research interests include statistical and nonlinear biomedical signal and image processing, cardiovascular and neural modeling, and wearable systems for physiological monitoring. Application of his research include the assessment of autonomic nervous system activity on cardiovascular control, brain-heart interactions, affective computing, assessment of mood and mental disorders, and disorder of consciousness. He is author of more than 100 international scientific contributions in these fields published in peer-reviewed international journals, conference proceedings, books and book chapters, and is official reviewer of more than fifty international scientific journals. He has been involved in several international research projects, and currently is the scientific co-coordinator of the European collaborative project H2020-PHC-2015-689691-NEVERMIND. Dr. Valenza has been guest editor of several international scientific journals, and is currently member of the editorial board of the Nature’s journal “Scientific Reports”.

Sparsity Constrained Estimation Using Spike and Slab Priors

Room BA 7129 (tentatively) Bahen Centre for Information Technology

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.

Artificially Intelligent Imaging (AI2): System to Circuit to Device Level Implementations of Smart CMOS Imaging, A Generalized Approach for Non-Application Specific Intelligence Design (NAS-ID)

Room ENGLG 05 George Vari Engineering Building

August 11, 2016 at 1:00 p.m. Dr. Faycal Saffih, Department of Electrical Engineering, UAE University, will be presenting “Artificially Intelligent Imaging (AI2): System to Circuit to Device Level Implementations of Smart CMOS Imaging, A Generalized Approach for Non-Application Specific Intelligence Design (NAS-ID)”. Speaker: Dr. Faycal Saffih Assistant Professor, Department of Electrical Engineering UAE University Day & Time: Thursday, August 11, 2016 1:00 p.m. – 2:00 p.m. Location: Room ENGLG 05 George Vari Engineering Building Department of Electrical and Computer Engineering Ryerson University Contact: Dimitri Androutsos Abstract: In this talk we will present the development of intelligence (vs intelligent) implementations from top-down and bottom-up approaches and from Electrical engineering design and Biological Biomimicry to Solid-state Physics prediction. Smart CMOS imaging is the application of choice where these multi-disciplinary studies interacts to suggest a novel approach for research to design intelligent devices needed in a verity of advanced technological devices and systems for a variety of applications such as biomedical and renewables systems and devices to name a few. Biography: Dr. Fayçal Saffih (IEEE Member since 2000) received the B.Sc. (with Best Honors) degree in Solid-State Physics from the University of Sétif-1, Sétif, Algeria, in 1996, the M.Sc. degree in Digital Neural networks from Physics Department, University of Malaya, Kuala Lumpur, Malaysia, in 1998, and the Ph.D. degree in Smart CMOS Imaging from Electrical and Computer Engineering Department, University of Waterloo, Waterloo, ON, Canada. Taking a decade journey between academia and industry, Dr. Saffih enriched his experience multidimensionally spanning Microelectronics from devices up-to systems, and industry from R&D department to Entrepreneurship start-up, all of which from West USA (OR) to Singapore’s prestigious A*star Agency for Science, Technology and Research. Recently, Dr. Saffih endeavored into renewable energy research and business starting from Stanford certification in 2013 and currently undertaking an Online program from Renewables Academy (RENAC), Germany Dr. Faycal Saffih is currently an assistant professor at the Electrical Engineering Department of the UAE University and a regular visiting scholar at the University of Waterloo, University of Alberta among others. His research is on intelligence extraction and implementation on devices and systems particularly smart CMOS image sensors.