Speaker: Chancellor’s Prof. Hamid Jafarkhani Electrical Engineering and Computer Science The Henry Samueli School of Engineering University of California, Irvine Date: Tuesday, Oct 17, 2017 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://chapters.comsoc.org/comsig/ Abstract: We present a general review of space-time coding and beamforming in multiple-input multiple-output (MIMO) systems with an emphasis on the role of limited/quantized feedback. We continue with a description of wireless relay networks and formulate its system model as a virtual MIMO. We discuss the distributed nature of the network and present distributed space-time coding and distributed beamforming methods. We show that despite the existing challenges in a relay network, distributed methods can provide similar gains even in the case of limited/quantized feedback. Speaker Biography: Prof. Hamid Jafarkhani  is a Chancellor's Professor at the Department of Electrical Engineering and Computer Science, University of California, Irvine, where he is also the Director of Center for Pervasive Communications and Computing and the Conexant-Broadcom Endowed Chair. Prof. Jafarkhani ranked first in the nationwide entrance examination of Iranian universities in 1984. He was a co-recipient of the American Division Award of the 1995 Texas Instruments DSP Solutions Challenge. He received an NSF Career Award in 2003, the UCI Distinguished Mid-Career Faculty Award for Research in 2006 and the School of Engineering Fariborz Maseeh Best Faculty Research Award in 2007. Also, he was a co-recipient of the 2002 best paper award of ISWC, the 2006 IEEE Marconi Best Paper Award in Wireless Communications, the 2009 best paper award of the Journal of Communications and Networks, the 2012 IEEE Globecom best paper award (Communication Theory Symposium), the 2013 IEEE Eric E. Sumner Award, and the 2014 IEEE Communications Society Award for Advances in Communication. He received the 2015-2016 School of Engineering Excellence in Research Senior Career Award and was an IEEE ComSoc Distinguished Lecturer. He is listed as a highly cited researcher in http://www.isihighlycited.com.   According to the Thomson Scientific, he is one of the top 10 most-cited researchers in the field of "computer science" during 1997-2007. He is a Fellow of AAAS, an IEEE Fellow, and the author of the book "Space-Time Coding: Theory and Practice."   Questions: Dr. Lan Nguyen IEEE OC ComSig Chapter Chair lan.nguyen@linquest.com

  Speaker: Prof. Ahmed M. Eltawil, UCI Electrical Engineering and Computer Science University of California, Irvine   Date: Tuesday, May 1st, 2018 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: Enabling the 5G vision of a wirelessly interconnected ecosystem requires innovation and optimization at all levels of the hierarchy. In this talk, we first consider the system from a link enhancement perspective, where we present recent results directed at enabling Full-duplex communications. Currently systems operate in "Half duplex mode" to avoid self-saturation, where the high-powered transmitter saturates the receive path. Full-duplex transmission promises to double the spectral efficiency by allowing bidirectional communications to be carried out over the same resources. The key challenge in practical full-duplex systems is the un-cancelled self-interference power caused by a combination of hardware imperfections. We discuss recent work that identifies system limitations, performance, optimizations, and the practicality of proposed architectures. In the second part of the talk, we consider the Achilles heel of wireless systems, namely, power consumption. Traditionally, reliability is attributed to higher power consumption. We show that this is not necessarily true. In fact, one can design systems to be both reliable (within desired specifications) and low power. We present a unique approach for power management which factors in the built-in algorithmic resilience to errors inherent in all wireless designs. This error tolerance can be utilized and co-designed with the hardware circuitry in mind to provide resilience not only to channel induced errors but also to hardware induced faults (due to low power modes), thus expanding the adaptation space to unexplored domains. Speaker Biography: Ahmed M. Eltawil is a Professor at the University of California, Irvine. He has been with the Department of Electrical Engineering and Computer Science since 2005 where he is the founder and director of the Wireless Systems and Circuits Laboratory. His current research interests are in the general area of low power digital circuit and signal processing architectures with an emphasis on mobile systems. In addition to his department affiliation, he is also affiliated to a number of research centers across the University of California, Irvine. He received the Doctorate degree from the University of California, Los Angeles, in 2003 and the M.Sc. and B.Sc. degrees (with honors) from Cairo University, Giza, Egypt, in 1999 and 1997, respectively. Dr. Eltawil has been on the technical program committees and steering committees for numerous workshops, symposia, and conferences in the areas of low power computing and wireless communication system design. He received several awards, as well as distinguished grants, including the NSF CAREER grant in 2010 supporting his research in low power systems. Questions: Dr. Lan Nguyen IEEE OC ComSig Chapter Chair lan.nguyen@linquest.com

    Artificial Neural Networks (ANNs) and Machine Learning Speaker: Dr. Lan Nguyen, LinQuest Corporation Date: Thursday, December 13, 2018 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: The development of Artificial Neuron Networks (ANNs) began in the 1940s with the work of Warren McCulloch and Walter Pitts who showed that network of artificial neurons could in principle compute any arithmetic function or logical function. In recent years, neural networks have achieved results that surpass many traditional techniques. Thousands of neural networks have been applied successfully in hundreds of fields, which include target tracking, radar and image processing, cybersecurity, cancer diagnosis, mortgage screening, routing systems, and integrated circuits. These neural networks have been proven to learn complex relations between input data (features) and output values. The intent of this talk is for the public who want to understand neural networks and machine learning. Topics to be covered in this talk include: Introduction to Artificial Neural Networks (ANNs), what is an ANN and why ANN? A brief history of ANN, biological neural networks versus artificial neural networks, and principles of ANNs Important neural networks models, such as Adaline and Perceptron, feed forward and feedback networks, self-organizing networks (Kohonen’s model) Learning methods, such as Hebbian learning, supervised learning, unsupervised learning, reinforcement learning, back propagation learning, and data training Machine learning, what is machine learning? Challenges of machine learning, and the role of neural networks in machine learning Case studies Speaker Biography: Lan Nguyen is a System Engineer at LinQuest Corporation. He joined LinQuest in 2004 and has over 30 years of industry experience.  His current research interests are in the area of SATCOM, Communication Theory, Digital Signal Processing, and Machine Learning. Dr. Lan Nguyen has been on the technical program committees for numerous symposia and conferences.  He has published numerous conference and journal papers in the areas of SATCOM and wireless communication. He is a Senior IEEE member and a Certified Expert System Engineering Professional (ESEP), International Council on Systems Engineering (INCOSE). Questions: Dr. Lan Nguyen IEEE OC ComSig Chapter Chair lan.nguyen@linquest.com

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  

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