Latest Past Events

Running Deep Learning Models on Smartphones as Real-Time Apps for Signal and Image Processing Applications

The Doubletree Club Orange County Airport 7 Hutton Centre Dr, Santa Ana

Running Deep Learning Models on Smartphones as Real-Time Apps for Signal and Image Processing Applications Speaker:  Prof. Nasser Kehtarnavaz, Univ. of Texas at Dallas Date: Thursday, July 11, 2019 Time: Social Hour: 6:00 p.m. Dinner: 6:30 p.m. Presentation: 7:15 p.m. Location: The Doubletree Club Orange County Airport 7 Hutton Centre Drive, Santa Ana, CA, 92707-5794 714-751-2400 Please RSVP at http://oc-comsig.eventbrite.com/ Cost: First 10 early-birds (first-come-first-serve) are free! After that, $20 for non-members with dinner, $10 for IEEE members with dinner, $5 for student-members with dinner, free for presentation only For more information on current and future events, please visit Orange County ComSig chapter website at: http://comsig.chapters.comsoc.org/ Abstract: In many signal and image processing applications, deep learning models or deep neural networks have provided superior performance compared with conventional machine learning solutions. This talk covers how deep learning models can be turned into apps running in real-time on smartphones (both Android and iOS). One signal and one image processing application are presented. The image processing application involves real-time implementation of a deep learning model as a smartphone app to detect retinal abnormalities in an on-the-fly manner as retina images are captured by the smartphone camera through commercially available lenses. The motivation behind this application is to use smartphones as an alternative to fundus cameras providing a cost-effective and widely accessible approach to first-pass eye examination. The signal processing application involves real-time implementation of the speech processing pipeline of hearing aids as a smartphone app. The components of the implemented pipeline include a deep learning-based voice activity detection, noise reduction, noise classification, and compression. The motivation behind this application is to use smartphones as an open-source, programmable, and portable signal processing platform to conduct hearing enhancement studies in realistic audio environments. Speaker Biography: Prof. Nasser Kehtarnavaz is an Erik Jonsson Distinguished Professor with the Department of Electrical and Computer Engineering. His research interests include real-time signal and image processing, machine learning and deep learning, and biomedical signal and image analysis. He has authored or co-authored 10 books and over 380 journal papers, conference papers, patents, manuals, and editorials in these areas. He is a Fellow of IEEE, a Fellow of SPIE, a licensed Professional Engineer, and is serving as Editor-in-Chief of Springer Journal of Real-Time Image Processing. Questions: Dr. Lan Nguyen IEEE OC ComSig Chapter Chair lan.nguyen@linquest.com

Active Learning and Optimization for Next Generation Communication Networks

The Doubletree Club Orange County Airport 7 Hutton Centre Dr, Santa Ana

IEEE Orange County Communications Society and Signal Processing Society (ComSig) Chapter Invites You to the Following Event: Active Learning and Optimization for Next Generation Communication Networks Speaker:  Prof. Tara Javidi, ECE Dpt. UC San Diego   Date:   Monday, June 24, 2019 Time: Social Hour:  6:00 p.m. Dinner/Presentation: 6:30 p.m. Location:  The Doubletree Club Orange County Airport 7 Hutton Centre Drive, Santa Ana, CA, 92707-5794 714-751-2400 Please RSVP at https://www.eventbrite.com/e/active-learning-and-optimization-for-next-generation-communication-networks-tickets-63349771873 Cost: First 10 early-birds (first-come-first-serve) are free! After that, $20 for non-members with dinner, $10 for IEEE members with dinner, $5 for student-members with dinner, free for presentation only For more information on current and future events, please visit Orange County ComSig chapter website at: http://comsig.chapters.comsoc.org   Abstract: Network management and configuration is an essential attribute of any wireless network with reliable self-tuning capabilities.  In contrast to the past generations of networking solutions, on the other hand, in the ever-increasingly mobile and large-scale networks of tomorrow the network reconfiguration overhead may not be insignificant; this includes the initial beam alignment, link maintenance, spectrum sensing, packet resizing, etc.  Our work aims to provide fundamental limits on the overhead associated with learning, network tuning, and optimization of network parameters.  Our approach relies on the theory of active learning and optimization to quantify the networking overhead and utilizes recent data analytic and machine learning algorithms to develop practical learning/optimization algorithms. In the first part of the talk, we consider the problem of search and optimization of the directional link establishment and maintenance (beam alignment) in mmWave communications.  In the second part of the talk, we consider an important variant of the search problem: data-driven and empirical optimization for wireless network parameter tuning.   Speaker Biography Prof. Tara Javidi received her BS in electrical engineering at Sharif University of Technology, Tehran, Iran.  She received her MS degrees in electrical engineering (systems) and in applied mathematics (stochastic analysis) from the University of Michigan, Ann Arbor, in 1998 and 1999, respectively.  She received her Ph.D. in electrical engineering and computer science from the University of Michigan, Ann Arbor, in 2002. From 2002 to 2004, Tara Javidi was an assistant professor at the Electrical Engineering Department, University of Washington, Seattle.  In 2005, she joined the University of California, San Diego, where she is currently a professor of electrical and computer engineering.  In 2013-2014, she spent her sabbatical at Stanford University as a visiting faculty. At the University of California, San Diego, Tara Javidi is a founding co-director of the Center for Machine-Integrated Computing and Security, directs the Advanced Networking Science Lab and is a faculty member of the Centers of Information Theory and Applications (ITA), Wireless Communications (CWC), and Networked Systems (CNS).  She is a founding faculty member of HALICIOĞLU DATA SCIENCE INSTITUTE (HDSI) at UCSD. At UCSD, she is an affiliate faculty member in the departments of Computer Science and Engineering as well as Ethnic Studies.  She is also a member of Board of Governors of the IEEE Information Theory Society (2017/18/19). Tara Javidi’s research interests are in theory of active learning, information theory with feedback, stochastic control theory, and stochastic resource allocation in wireless communications and communication networks.  She was the guest editor for the IEEE Journal of Selected Areas in Communications special issue on Communications and Control. From 2011 to 2014, she was an associate editor for ACM/IEEE Transactions on Networking and the editor for the IEEE Information Theory Society Newsletter.  From 2014-2017, she served as the associate editor for IEEE Transactions on Information Theory. She currently serves as an associate editor for IEEE Transactions on Network Science and Engineering. Tara Javidi received the 2018 Qualcomm Faculty Award for her contributions to wireless technology.  Tara Javidi was a recipient of the National Science Foundation early career award (CAREER) in 2004, Barbour Graduate Scholarship, University of Michigan, in 1999, and the Presidential and Ministerial Recognitions for Excellence in the National Entrance Exam, Iran, in 1992.  In addition to numerous contributed and invited talks, she was a tutorial speaker at various international and prestigious conferences: International Conference on Cognitive Radio Oriented Wireless Networks (CROWNCOM) 2010, ACM International Symposium on Mobile Ad Hoc Networking and Computing (Mobihoc) 2013, International Symposium on Information Theory (ISIT) 2014, and IEEE Conference on Decision and Control (CDC) 2016.  Tara Javidi was a Distinguished Lecturer of the IEEE Information Theory Society (2017/18). Contact:   Lan Nguyen, Ph.D. IEEE OC ComSig Chapter Chair lan.nguyen@linquest.com