Distinguished Lecture: Machine Learning in NextG Networks via Generative Adversarial Networks
Generative Adversarial Networks (GANs) implement Machine Learning (ML) algorithms that can address competitive resource allocation problems, together with detection and mitigation of anomalous behavior. In this talk, the speaker will discuss their use in next-generation (NextG) communications within the context of cognitive networks to address i) spectrum sharing, ii) detecting anomalies, and iii) mitigating security attacks. GANs have the following advantages. First, they can learn and synthesize field data, which can be costly, time-consuming, and non-repeatable. Second, they enable pre-training classifiers by using semisupervised data. Third, they facilitate increased resolution. Fourth, they enable recovering corrupted bits in the spectrum. The talk will provide basics of GANs, a comparative discussion on different kinds of GANs, performance measures for GANs in computer vision and image processing as well as wireless applications, a number of datasets for wireless applications, performance measures for general classifiers, a survey of the literature on GANs for i)–iii) above, some simulation results, and future research directions. In the spectrum sharing problem, connections to cognitive wireless networks are established. Simulation results show that a particular GAN implementation is better than a convolutional autoencoder for an outlier detection problem in spectrum sensing.
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- Co-sponsored by Vishnu S. Pendyala, SJSU
- Starts 18 July 2025 07:00 AM UTC
- Ends 12 August 2025 07:00 AM UTC
- No Admission Charge
Speakers
Dr. Vishnu S. Pendyala of San Jose State University
Moderator
Biography:
Vishnu S. Pendyala, PhD is a faculty member in Applied Data Science and an Academic Senator with San Jose State University, current chair of the Santa Clara Valley Chapters of IEEE Computer and Computational Intelligence Societies, Area 4 Coordinator for Region 6, and a Distinguished Contributor of the IEEE Computer Society. As a past ACM Distinguished Speaker, researcher, and industry expert, he gave nearly 100 talks and tutorial sessions in various forums such as faculty development programs, the 12th IEEE GHTC, IEEE ANTS, 12th IACC, 10th ICMC, IUCEE, 12th ACM IKDD CODS and 30th COMAD to audiences at venues such as Stanford University, Google, University of Bolton, Computer History Museum, Universidad de Ingeniería y Tecnología, Lima, Peru, IIIT Hyderabad, KREA, IIT Jodhpur, University of Hyderabad, IIT Indore, IIIT Bhubaneswar. Some of these talks are available on YouTube and IEEE.tv. He is a senior member of the IEEE and ACM. He has over two decades of experience in the software industry in the Silicon Valley, USA. His book, “Veracity of Big Data,” is available in several libraries, including those of MIT, Stanford, CMU, the US Congress and internationally. Two other books on machine learning and software development that he edited are also well-received and found place in the US Library of Congress and other reputed libraries. Dr. Pendyala taught a one-week course sponsored by the Ministry of Human Resource Development (MHRD), Government of India, under the GIAN program in 2017 to Computer Science faculty from all over the country and delivered the keynote in a similar program sponsored by AICTE, Government of India in 2022. Dr. Pendyala served on a US government's National Science Foundation (NSF) proposal review panel in 2023. He received the Ramanujan memorial gold medal and a shield for his college at the State Math Olympiad. He also played an active role in the Computer Society of India and was the Program Secretary for its annual national convention.
Address:One Washington Sq, San Jose State University, San Jose, New York, United States, 95192-0250
Prof. Ender Ayanoglu
Machine Learning in NextG Networks via Generative Adversarial Networks
Biography:
Ender Ayanoglu received the Ph.D. degree from Stanford University,
Stanford, CA, in 1986, in electrical engineering. He was with the
Communications Systems Research Laboratory, part of AT&T Bell
Laboratories, Holmdel, NJ, until 1996, and Bell Labs, Lucent
Technologies until 1999. From 1999 until 2002, he was a Systems
Architect at Cisco Systems, Inc., San Jose, CA. Since 2002, he has
been a Professor in the Department of Electrical Engineering and
Computer Science, University of California, Irvine, Irvine, CA, where
he served as the Director of the Center for Pervasive Communications
and Computing and held the Conexant-Broadcom Endowed Chair during
2002-2010. His past accomplishments include the invention of the 56K
modems, characterization of wavelength conversion gain in Wavelength
Division Multiplexed (WDM) systems, and diversity coding, a technique
for link failure recovery in communication networks employing erasure
coding introduced in 1990, before the publication of the first
papers on network coding. During 2000-2001, he served as the founding
chair of the IEEE-ISTO Broadband Wireless Internet Forum (BWIF), an
industry standards organization that developed and built a broadband
wireless system employing Orthogonal Frequency Division Multiplexing
(OFDM) and a Medium Access Control (MAC) algorithm that provides
Quality-of-Service (QoS) guarantees. This system is the precursor of
today’s Fourth and Fifth Generation (4G and 5G) cellular wireless
systems. From 1993 until 2014, Dr. Ayanoglu was an Editor, and since
January 2014 is a Senior Editor of the IEEE Transactions on
Communications. He served as the Editor-in-Chief of the IEEE
Transactions on Communications from 2004 to 2008. From January 2015
until December 2016, he served as the Editor-in-Chief of the IEEE
Journal on Selected Areas in Communications - Series on Green
Communications and Networking. This series published three special
issues with record number of papers. He led the efforts to start the
IEEE Transactions on Green Communications and Networking and served as
its Founding Editor-in-Chief from August 2016 to August 2020. From
1990 to 2002, he served on the Executive Committee of the IEEE
Communications Society Communication Theory Committee, and from 1999
to 2002, he was its Chair. Dr. Ayanoglu is the recipient of the IEEE
Communications Society Stephen O. Rice Prize Paper Award in 1995, the
IEEE Communications Society Best Tutorial Paper Award in 1997, the
IEEE Communications Society Communication Theory Technical Committee
Outstanding Service Award in 2014, and the IEEE Communications Society
Joseph LoCicero Award for outstanding contributions to IEEE Communications
Society Journals as Editor, Editor-in-Chief (EiC), and the founding EiC in
2023. He has been an IEEE Fellow since 1998. He served as an IEEE Communications
Society Distinguished Lecturer in 2022-2023. He is serving a second term as
the IEEE Communications Society Distinguished Lecturer in 2024-2025.
Address:United States