Keynote and Plenary Speakers


Laura Hass (NAE member, ACM/AAAS Fellow)
Professor and Dean, University of Massachusetts Amherst, USA

Keynote Talk Title: Computing for the Common Good
Time: 8:30-9:30, Tuesday, February 19, 2019

Abstract:
Abstract: We are poised on the brink of a new era of computing, one in which computer systems will be able to handle many of the tasks that only humans can do today. The new systems will feed on data and leverage a diverse set of analytic tools and strategies, constantly learning. They will be able to partner with people to improve our lives and enhance our ability to solve complex problems. But there are risks that arise with this new technology: systems can exhibit bias, leading to unfair results, or they may behave oddly and be hard to explain. To counteract these issues, researchers at the University of Massachusetts Amherst are embracing a vision of “Computing for the Common Good”: computing that not only may be used for good, but that is also, intrinsically, good – fair, accessible, explainable, trustworthy, effective and efficient. In this talk, I will discuss this vision, illustrate it in action with examples of ongoing research and its application, and end with a few thoughts on open research challenges.

Biography:
Dr. Laura Haas joined the University of Massachusetts Amherst in August 2017 as Dean of the College of Information and Computer Sciences, after a long career at IBM, where she was accorded the title IBM Fellow in recognition of her impact. At the time of her retirement from IBM, she was Director of IBM Research’s Accelerated Discovery Lab (2011-2017), after serving as Director of Computer Science at IBM’s Almaden Research Center from 2005 to 2011. She had worldwide responsibility for IBM Research’s exploratory science program from 2009 through 2013. From 2001-2005, she led the Information Integration Solutions architecture and development teams in IBM's Software Group. Previously, Dr. Haas was a research staff member and manager at Almaden. She is best known for her work on the Starburst query processor, from which DB2 LUW was developed, on Garlic, a system which allowed integration of heterogeneous data sources, and on Clio, the first semi-automatic tool for heterogeneous schema mapping. She has received several IBM awards for Outstanding Innovation and Technical Achievement, an IBM Corporate Award for information integration technology, the Anita Borg Institute Technical Leadership Award, and the ACM SIGMOD Edgar F. Codd Innovation Award. Dr. Haas was Vice President of the VLDB Endowment Board of Trustees from 2004-2009 and served on the board of the Computing Research Association from 2007-2016 (vice chair 2009-2015); she currently serves on the National Academies Computer Science and Telecommunications Board (2013-2019). She is an ACM Fellow, a member of the National Academy of Engineering, and a Fellow of the American Academy of Arts and Sciences.


Ali H. Sayed (NAE member, IEEE/AAAS Fellow)
Dean and Professor, EPFL, Switzerland

Keynote Talk Title: TBD
Time: 8:30-9:30, Monday, February 18, 2019

Abstract:
TBD

Biography:
Ali H. Sayed is Dean of Engineering at EPFL, Switzerland. He has also served as distinguished professor and former chairman of electrical engineering at UCLA, Los Angeles. He is recognized as a Highly Cited Researcher by Thomson Reuters and is also a member of the US National Academy of Engineering. An author of over 530 scholarly publications and six books, his research involves several areas including adaptation and learning, data and network sciences, and multi-agent systems. Dr. Sayed has received several awards including the 2015 Education Award from the IEEE Signal Processing Society, the 2014 Athanasios Papoulis Award from the European Association for Signal Processing, the 2013 Meritorious Service Award, and the 2012 Technical Achievement Award from the IEEE Signal Processing Society. He has also received the 2005 Terman Award from the American Society for Engineering Education, the 2003 Kuwait Prize, and the 1996 IEEE Donald G. Fink Prize. His articles received several Best Paper Awards from the IEEE. He is a Fellow of IEEE and the American Association for the Advancement of Science (AAAS). He is serving as President of the IEEE Signal Processing Society.


Raj Jain (IEEE Life Fellow, ACM/AAAS Fellow)
Professor, Washington University in St. Louis., USA

Keynote Talk Title: TBD
Time: 8:30-9:30, Wednesday, February 20, 2019

Abstract:
TBD

Biography:
Professor Raj Jain is a Life Fellow of IEEE, a Fellow of ACM, a Fellow of AAAS, and a Fellow of Academy of Science St. Louis. He is a winner of 2018 James B. Eads Award from Academy of Science, Saint Louis, ACM SIGCOMM Lifetime Achievement Award 2017, 2015 A. A. Michelson Award from Computer Measurement Group, 2014 Distinguished Alumnus Award from Indian Institute of Science, Bangalore Alumni Association, 2006 ACM SIGCOMM Test of Time award, and Center for Development of Advanced Computing - Advanced Computing and Communications Society (CDAC-ACCS) Foundation Award 2009, and WiMAX Forum Individual Contribution Award 2008.

Dr. Jain is currently the Barbara J. and Jerome R. Cox, Jr., Professor of Computer Science and Engineering at Washington University in St. Louis. Previously, he was the CTO and one of the Co-founders of Nayna Networks, Inc - a next generation telecommunications systems company in San Jose, CA. He was a Senior Consulting Engineer at Digital Equipment Corporation in Littleton, Mass and then a professor of Computer and Information Sciences at Ohio State University in Columbus, Ohio.

He is the author or editor of 12 books including ``Art of Computer Systems Performance Analysis,'' which won the 1991 ``Best-Advanced How-to Book, Systems'' award from Computer Press Association and " High-Performance TCP/IP: Concepts, Issues, and Solutions," published by Prentice Hall in November 2003. He is a co-editor of " Quality of Service Architectures for Wireless Networks: Performance Metrics and Management," published in April 2010.

Prof. Jain has 14 patents, and has written 17 book chapters, 79+ journal and magazine papers and 122+ conference papers. His papers have been widely referenced and he is known for his research on congestion control and avoidance, traffic modeling, performance analysis, and error analysis. Google Scholar lists over 25,200+ citations to his publications. He is a co-inventor of the DECbit scheme, which has been implemented in various forms in DECnet, OSI, Frame Relay, and ATM Networks. His team has developed several switch algorithms for explicit rate-based congestion avoidance in ATM networks.

A distinguishing factor of his research is its relevance to the Industry. As a faculty member, Dr. Jain actively participates in industry forums like WiMAX Forum, IEEE Standards group, ATM Forum and Internet Engineering Task Force and has made over 200 contributions that ensured that his research was implemented and not just published as papers. He is acknowledged in published versions of 170+ IEEE standards. Based on his active participation in the computer industry, Dr. Jain was awarded 1999 siliconindia Leadership Awards for Excellence and Promise in Business and Technology.

Raj Jain has served on the advisory boards of Bluesage Communications, Inc., InBay Technology Solutions, Inc, San Jose, CA and AKS University, Satna, MP, India, Indo-US Collaboration in Engineering Education (IUCEE). In the past, he has also served on the Board of Technical Advisors to a dozen Silicon Valley start ups including Nexabit Networks, Westborough, MA acquired by Lucent Corporation. (March 1997-1999), Amber Networks, Fremont, CA acquired by Nokia (1999-2001).

He was a keynote speaker at 45+ conferences including AEECT 2017, ACM SIGCOMM 2017, CITS 2017, CCISP 2016, CIC 2016, IEMCON 2016, ADCOM 2016, SSC 2016, CANSec 2016, IoT World Forum R&D Symposium 2015, ADCOM15, ADCOM14, WowMoM14, ADCOM13, ICC 2012, MCS12, ADCONS 2012, SBRC 2011, COMSNETS 2011, ANTS 2010, MICS 2010, ADCOM 2009, NBiS 2009, NetArch 2009, ICON 2008, ACM Multimedia 2008, ICCBN 2008, ICCCE 2008, AccessNets 2007, and a dozen other conferences. He has served in the program committees of over 275+ conferences.

He is on the Editorial Boards of Recent Advances in Communications and Networking, Journal of High Speed Networks (USA), Mobile Networks and Applications, International Journal of Virtual Technology and Multimedia (IJVTM) (UK), International Journal of Wireless and Optical Communications (IJWOC), Vehicular Communications (Elsevier), International Journal of Communication Networks and Distributed Systems (IJCNDS), ICST Transactions on Mobile Communications and Applications, International Journal on Advances in Internet Technology, and on the advisory boards of Global Science and Technology Forum (GSTF), Singapore, Journal of Communications (Finland), EIA Transactions on TSim Tools, Asia-pacific Journal of Neural Networks and its Applications (AJNNIA). He is also a co-guest editor of ACM/Springer Mobile Networks and Applications (MONET) special issue on Device-to-Device Communication in 5G Networks to be published in 2017. In the past, he was Guest Co-Editor of IEEE Communications Magazine September 2012 special issue on Cloud Computing: Networking and Communications Challenges and July 2011 special issue on Future Internet Architectures: Design and Deployment Perspective.

He has served as a Distinguished Lecturer for the IEEE Communications Society (1997, 1999-2006), ACM Lecturer (1991-97), IEEE Computer Society Distinguished Visitor (1993-96), Vice-Chair of ACM SIGCOMM (1991-95), Chair of TIA/SCD/CIS Working Group on ATM Traffic Management (1996-1998), Editor of the WiMAX Forum System Evaluation Methodology (2005-2008), Editor of ATM Forum Performance Testing Specification (1996-1998).


Lizhong Zheng (IEEE Fellow)
Professor, Massachusetts Institute of Technology

Keynote Talk Title: Connecting Data with Domain Knowledge in Neural Networks
Time: 8:30-9:30, Thursday, February 21, 2019

Abstract:
Part of the power of neural networks comes from the fact that it is a very generic, almost "blind", tool to extract useful information directly from data. Unlike more conventional data analysis approaches, it does not assume any knowledge of the statistical model, the structure, relation or constraints in the data, but tries to use a universal network structure to learn and represent all types of models. On the other hand, if we do have some of such knowledge of the model, such as in communication systems and almost all other engineering systems, in principle we should be able to make the inference algorithms more efficiently by taking advantage of the domain knowledge. It is however not clear how the domain knowledge should be used in deep learning in general. This talk tries to address this issue.

Conceptually, we need to identify what happens inside a neural network during the learning process, to find out what statistical quantities are being calculated and how are they stored inside a network. To that end, we formulate a new problem called the "universal feature selection" problem, where we need to select from the high dimensional data a low dimensional feature that can be used to solve, not one, but a family of inference problems. We solve this problem and show that 1) the solution is closely related to a number of concepts in information theory and statistics such as the HGR correlation and common information, and 2) a number of learning algorithms, PCA, CCA, Matrix Factorization, and Neural Networks, implicitly solve the same problem. We then demonstrate how such theoretical understanding of neural networks can help us to establish a performance limit and design network parameters more systematically; and to include specific domain knowledge in the design of new network structures.

Biography:
Lizhong Zheng received the B.S and M.S. degrees, in 1994 and 1997 respectively, from the Department of Electronic Engineering, Tsinghua University, China, and the Ph.D. degree, in 2002, from the Department of Electrical Engineering and Computer Sciences, University of California, Berkeley. Since 2002, he has been working at MIT, where he is currently a professor of Electrical Engineering. His research interests include information theory, statistical inference, communications, and networks theory. He received Eli Jury award from UC Berkeley in 2002, IEEE Information Theory Society Paper Award in 2003, and NSF CAREER award in 2004, and the AFOSR Young Investigator Award in 2007. He served as an associate editor for IEEE Transactions on Information Theory, and the general co-chair for the IEEE International Symposium on Information Theory in 2012. He is an IEEE fellow.


Victor Bahl (IEEE/ACM/AAAS Fellow)
Distinguished Scientist and Director, Microsoft, USA

Plenary Forum Title: AI/ML - A New Paradigm for Communication Networks
Time: 10:00-12:00, Wednesday, February 20, 2019

Biography:
Victor Bahl is a distinguished scientist and director of mobility & networking research in Microsoft. He serves on the Microsoft Research Redmond Lab leadership team managing over 200 researchers and staff. He advises Microsoft's CEO and his senior leadership team on strategy and long-term vision related to networked systems, cloud computing, data center infrastructure, mobile computing, and wireless systems. He heads a high-powered group that executes on this vision through research, technology transfers to product groups, industry partnerships, and associated policy engagement with governments and research institutes around the world. Dr. Bahl has published over 125 papers with close to 50,000 citations; has been granted over 150 patent and delivered over 40 keynotes. For his seminal work in wireless systems and broadband access he has received several technical and leadership awards including the IEEE Koji Kobayashi Computers and Communications Award, the ACM SIGMOBILE Outstanding Contributions Award, two United States FCC awards, two national transportation awards, two test-of-time award, three best paper awards, a distinguished service award, two distinguished alumni awards (from and a IEEE outstanding leadership award. Under his direction, his group has had game changing impact on Microsoft's cloud computing infrastructures both in the data center and in wide-area networking and on edge computing and live video analytics. Dr. Bahl is the founder of ACM SIGMOBILE, ACM MobiSys, ACM GetMobile and several other important conferences. With his wife, he co-founded Computing For All, a non-profit dedicated to increasing and enhancing computer science education for students of all ages and from all backgrounds. Dr. Bahl is a Fellow of the ACM, IEEE, and AAAS.


Elza Erkip (IEEE Fellow)
Institute Professor, New York University, USA.

Plenary Talk Title: An information theoretic perspective on web privacy
Time: 14:30-15:30, Tuesday, February 19, 2019

Abstract:
When we browse the internet, we expect that our social network identities and web activities will remain private. Unfortunately, in reality, users are constantly tracked on the internet. As web tracking technologies become more sophisticated and pervasive, there is a critical need to understand and quantify web users' privacy risk. In other words, what is the likelihood that users on the internet can be uniquely identified from their online activities?

This talk provides an information theoretic perspective on web privacy by considering two main classes of privacy attacks based on the information they extract about a user. (i) Attributes capture the user's activities on the web and could include its browsing history or its memberships in groups. Attacks that exploit the attributes are called “fingerprinting attacks,” and usually include an active query stage by the attacker. (ii) Relationships capture the user's interactions with other users on the web such as its friendship relations on a certain social network. Attacks that exploit the relationships are called “social network de-anonymization attacks.” For each class, we show how information theoretic tools can be used to design and analyze privacy attacks and to provide explicit characterization of the associated privacy risks.

Biography:
Elza Erkip an Institute Professor in the Electrical and Computer Engineering Department at New York University Tandon School of Engineering. She received the B.S. degree in Electrical and Electronics Engineering from Middle East Technical University, Ankara, Turkey, and the M.S. and Ph.D. degrees in Electrical Engineering from Stanford University, Stanford, CA, USA. Her research interests are in information theory, communication theory, and wireless communications.

Dr. Erkip is a member of the Science Academy of Turkey and is among the 2014 and 2015 Thomson Reuters Highly Cited Researchers. She received the NSF CAREER award in 2001 and the IEEE Communications Society WICE Outstanding Achievement Award in 2016. Her paper awards include the IEEE Communications Society Stephen O. Rice Paper Prize in 2004, and the IEEE Communications Society Award for Advances in Communication in 2013. She has been a member of the Board of Governors of the IEEE Information Theory Society since 2012 where she is currently the Society President. She was a Distinguished Lecturer of the IEEE Information Theory Society from 2013 to 2014.

Dr. Erkip has had many editorial and conference organization responsibilities. Some recent ones include Asilomar Conference on Signals, Systems and Computers, MIMO Communications and Signal Processing Track Chair in 2017, IEEE Wireless Communications and Networking Conference Technical Co-Chair in 2017, IEEE Journal on Selected Areas in Communications Guest Editor in 2015, and IEEE International Symposium of Information Theory General Co-Chair in 2013.


Monisha Ghosh (IEEE Fellow)
NSF Director and Research Professor, University of Chicago

Plenary Talk Title: TBD
Time: 14:30-15:30, Wednesday, February 20, 2019

Abstract:
TBD

Biography:
Dr. Monisha Ghosh joined NSF as a rotating Program Director in September 2017, in the Computer and Network System (CNS) division within the Directorate of Computer & Information Science and Engineering (CISE). She manages wireless networking research within the Networking Technologies and Systems (NeTS) program. Dr. Ghosh is also a Research Professor at the University of Chicago, with a joint appointment at the Argonne National Laboratories, where she conducts research on wireless technologies for the IoT, 5G cellular, next generation Wi-Fi systems, coexistence and machine learning for predictive oncology. Prior to joining the University of Chicago in September 2015, she worked at Interdigital, Philips Research and Bell Laboratories, on various wireless systems such as the HDTV broadcast standard, cable standardization and on cognitive radio for the TV White Spaces. She has been an active contributor to many industry standards and was recognized with a Certificate of Appreciation for her outstanding contributions to IEEE 802.22. She is a Fellow of the IEEE.

She received her Ph.D. in Electrical Engineering from the University of Southern California in 1991, and her B. Tech from the Indian Institute of Technology, Kharagpur (India) in 1986.


Tom Hou (IEEE Fellow)
Bradley Distinguished Professor, Virginia Tech, USA

Plenary Talk Title: Advances in Wireless Networking with Multiple Antennas
Time: 13:30-14:30, Wednesday, February 20, 2019

Abstract:
MIMO is becoming pervasive and has been widely used in many communication systems (e.g., Wi-Fi and cellular communications). With the increase of number of nodes in the network and the number of antennas at each node, traditional matrix-based model becomes intractable. In recent years, degree-of-freedom (DoF) based models prove to be very effective in studying MIMO-based wireless networks. However, a serious limitation with these models is that they assume channel matrix is of full-rank. Although this assumption is valid when the number of antennas is small, it quickly becomes problematic as the number of antennas increases and propagation environment is not close to ideal. In this talk, I present our recent findings on this important problem. In particular, I present a new and general DoF-based model under rank-deficient conditions. To gain a fundamental understanding of this research, I first present layout some basic understanding on how MIMO's DoFs are consumed for spatial multiplexing (SM) and interference cancellation (IC) in the presence of rank deficiency. Based on this understanding, I present a general DoF model that can be used for identifying DoF region of a multi-link MIMO network and for studying DoF scheduling in MIMO networks. Most interestingly, I show that a shared (cooperative) DoF consumption at both transmit and receive nodes is critical for optimal allocation of DoF for IC. This is in contrast to existing DoF-based models, which says that DoFs should only be consumed at either transmit or receive node, but not both. This new finding offers a new understanding on how DoFs are consumed for IC under the general rank-deficient condition and serve as an important tool for future research of many-antenna based MIMO networks.

Biography:
Tom Hou is the Bradley Distinguished Professor of Electrical and Computer Engineering at Virginia Tech, USA. He received his Ph.D. degree from NYU Tandon School of Engineering (formerly Polytechnic Univ.) in 1998. His current research focuses on developing innovative solutions to complex science and engineering problems arising from wireless and mobile networks. He is particularly interested in exploring new performance limits at the network layer by exploiting advances at the physical layer. In recent years, he has been actively working on cross-layer optimization problems for cognitive radio wireless networks, cooperative communications, MIMO-based networks and energy related problems. He is also interested in wireless security. Prof. Hou was named an IEEE Fellow for contributions to modeling and optimization of wireless networks. He has published two textbooks: Cognitive Radio Communications and Networks: Principles and Practices (Academic Press/Elsevier, 2009) and Applied Optimization Methods for Wireless Networks (Cambridge University Press, 2014). The first book has been selected as one of the Best Readings on Cognitive Radio by the IEEE Communications Society. Prof. Hou's research was recognized by five best paper awards from the IEEE and two paper awards from the ACM. He holds five U.S. patents.

Prof. Hou is a prominent leader in the research community. He was an Area Editor of IEEE Transaction on Wireless Communications (Wireless Networking area), and an Editor of IEEE Transactions on Mobile Computing, IEEE Journal on Selected Areas in Communications - Cognitive Radio Series, and IEEE Wireless Communications. Currently, he is an Editor of IEEE/ACM Transactions on Networking and ACM Transactions on Sensor Networks. He is the Steering Committee Chair of IEEE INFOCOM conference - the largest and top ranked conference in networking. He is a member of the Board of Governors as well as a Distinguished Lecturer of the IEEE Communications Society.


Yuji Inou (IEEE Life Fellow)
Chairman of Toyota Info Technology Center, Toyota, Japan

Plenary Forum Title: AI/ML - A New Paradigm for Communication Networks
Time: 10:00-12:00, Wednesday, February 20, 2019

Biography:
Yuji Inoue was born in 1948 in Fukuoka, Japan. He received the B.E., M.E. and Ph. D degrees from Kyushu University, Fukuoka, Japan, in 1971, 1973 and 1986, respectively, and was made an Honorary Professor of the Mongolian Technical University in 1999.

He joined NTT Laboratories in 1973. He was first engaged in the development of digital network equipment and systems, and then in the standardization of ISDN (Integrated Services Digital Network), SDH (Synchronous Digital Hierarchy) etc in ITU-T, then he was the chairperson of technical committee in TINA-C, Telecommunication Information Networking Architecture Consortium. In 1997, he lead a global business development division when NTT was de-regulated to the global business. He moved to NTT Data Corporation to head its R&D as a board member in 2000. He moved back to NTT Shareholding Company as its board member and CTO to direct NTT group’s R&D with 6000 researchers and engineers.

In 2006, he was the candidate for the Director of ITU-T. Based on this experience, he joined TTC, The Telecommunication Technology Committee, in 2007 as the President and CEO.

In 2010, he moved to Toyota Info Technology Center Co., Ltd. as the Chairman of the Board, where he has been supporting Toyota Motor Company as one of the leading edge Connected Car Services Providers. He is now serving Toyota ITC as the Adviser.

He is a life-time fellow of IEEE, and a Honorable Professor of Mongolian Science and Technology University. He received many awards such as Japanese Ministers Awards. He wrote and edited many technical books.


Sekiya Motoyoshi
Head of Service Oriented Network Research Center, Fujitsu, Japan

Plenary Forum Title:
Time: 10:00-12:00, Wednesday, February 20, 2019

Biography:
Dr. Sekiya Motoyoshi joined Fujitsu Limited 1990 and has been engaged in research and development of optical communication system, includes Optical module, WDM system, Network software etc. He joined Fujitsu labs of America in 2010 and leading the research group in photonic networks, optical transmission system and SDN. Currently, he is Head of Service Oriented Network Research Center Fujitsu Labs Limited. He has served as technical committee member of OFC/NFOEC, Globecom workshop SDN for Optics, ICCVE, AICT, ONDM etc.. He is an inventor of more than 70 patents.


Pramod K. Varshney (IEEE Fellow)
Distinguished Professor, Syracuse University

Plenary Talk Title: Information Fusion: Theory and Applications
Time: 13:30-14:30, Tuesday, February 19, 2019

Abstract:
Information fusion refers to the acquisition, processing and synergistic combination of information gathered by various knowledge sources and sensors to provide a better understanding of a phenomenon. This fascinating field has evolved over the past three decades. Information fusion concepts are being applied to a wide variety of fields such as military command and control, robotics, image processing, air traffic control, medical diagnostics, pattern recognition, environmental monitoring, IoT and smart cities. This talk will present an overview of the field, present some recent research results and illustrate its utility by means of some examples.

Biography:
Pramod K. Varshney was born in Allahabad, India, in 1952. He received the B.S. degree in electrical engineering and computer science (with highest honors), and the M.S. and Ph.D. degrees in electrical engineering from the University of Illinois at Urbana-Champaign in 1972, 1974, and 1976 respectively.

Since 1976 he has been with Syracuse University, Syracuse, NY where he is currently a Distinguished Professor of Electrical Engineering and Computer Science and the Director of CASE: Center for Advanced Systems and Engineering. He served as the Associate Chair of the department during 1993-96. He is also an Adjunct Professor of Radiology at Upstate Medical University in Syracuse, NY. His current research interests are in distributed sensor networks and data fusion, detection and estimation theory, wireless communications, physical layer security, image processing, and radar. He has published extensively. He is the author of Distributed Detection and Data Fusion, published by Springer-Verlag in 1997.

While at the University of Illinois, Dr. Varshney was a James Scholar, a Bronze Tablet Senior, and a Fellow. He is a member of Tau Beta Pi and is the recipient of the 1981 ASEE Dow Outstanding Young Faculty Award. He was elected to the grade of Fellow of the IEEE in 1997 for his contributions in the area of distributed detection and data fusion. In 2000, he received the Third Millennium Medal from the IEEE and Chancellor’s Citation for exceptional academic achievement at Syracuse University. He is the recipient of the IEEE 2012 Judith A. Resnik Award. He received an honorary Doctor of Engineering degree from Drexel University in 2014, ECE Distinguished Alumni Award from UIUC in 2015, and the Yaakov Bar-Shalom Award for Lifetime Excellence in Information Fusion, ISIF in 2018. He was the President of International Society of Information Fusion during 2001.


Peiying Zhu (IEEE Fellow, Nortel/Huawei Fellow)
Senior Director, Huawei, Canada

Plenary Forum Title: AI/ML - A New Paradigm for Communication Networks
Time: 10:00-12:00, Wednesday, February 20, 2019

Biography:
Dr. Peiying Zhu is an IEEE Fellow and Huawei Fellow. She is currently leading 5G wireless system research in Huawei. The focus of her research is advanced wireless access technologies with more than 200 granted patents. She has been regularly giving talks and panel discussions on 5G vision and enabling technologies. She served as the guest editor for IEEE Signal processing magazine special issue on the 5G revolution and IEEE JSAC on Deployment Issues and Performance Challenges for 5G. She co-chaired various 5G workshops in IEEE GLOBECOM. She is actively involved in 3GPP and IEEE 802 standards development. She is currently a WiFi Alliance Board member.

Prior to joining Huawei in 2009, Peiying was a Nortel Fellow and Director of Advanced Wireless Access Technology in the Nortel Wireless Technology Lab. She led the team and pioneered research and prototyping on MIMO-OFDM and Multi-hop relay. Many of these technologies developed by the team have been adopted into LTE standards and 4G products.

Peiying Zhu received the Master of Science degree and Doctor Degree from Southeast University and Concordia University in 1985 and 1993 respectively.