Machine Learning over Networks: From Fundamentals to Applications.
In this talk, we review sample results based on our recent work in the areas of machine learning
over networks and edge intellligence. In particular, we touch upon our work on communication-efficient federated learning and its applications.
In the first part of the talk, we shed light on topics pertaining to federated learning. First, we overview a second-order federated learning algorithm, coined Fed-Sophia, with communication and computation efficiency merits. Next, we introduce our recent work on second order state synchronization (SOSS) to address the limitations of Fed-Sophia with non-IID data. Afterwards we overview MIRA which proposes a novel approach of federated multi-task learning for fine-tuning LLMs.
In the second part of the talk, we shift focus to edge intelligence applications in digital health with particular focus on CVD prediction. Finally, we present our work on architecting, designing and demonstrating a system prototype for multi-tier intelligence for IoT.
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- 500 El Camino Real
- Santa Clara, California
- United States 95053
- Building: Sobrato Campus for Discovery and Innovation
- Room Number: 1308
- Click here for Map
- Starts 15 August 2026 07:00 AM UTC
- Ends 01 September 2026 07:00 PM UTC
- No Admission Charge
Speakers
Dr. Tamer ElBatt
Machine Learning over Networks: From Fundamentals to Applications
Biography:
Tamer ElBatt is a Professor at the Computer Science and Engineering (CSE) Dept.,
The American University in Cairo (AUC), Egypt. He received the B.S. and M.S.
degrees in EECE from Cairo University, Egypt, respectively, and the Ph.D. degree in
ECE from the University of Maryland, College Park, USA in 2000. From 2000 to 2009
he was with major U.S. industry R&D, e.g., HRL Labs, Malibu, USA and Lockheed
Martin ATC, Palo Alto, USA, at various positions. From 2009 to 2017, he served at
the EECE Dept., Cairo University, as an Assistant Professor and later as an Associate
and Full Professor. He also held a joint appointment with Nile University, Egypt from
2009 to 2017 and served as the Director of the Wireless Intelligent Networks Center
(WINC) from 2012 to 2017. In July 2017, he joined the CSE Dept. at the American
University in Cairo as an Associate Professor, where he is currently a Professor. He
served as the CSE Director of the Graduate Program and later as the Associate Chair,
from 2019 to 2022. He published more than 165 papers in major journals and
international conferences. Dr. ElBatt holds seven issued U.S. patents and one WIPO
patent.
Dr. ElBatt served on the TPC of numerous IEEE and ACM conferences. He served as
an Executive TPC Vice Chair of the 6 th ICCSPA’24, TPC Co-Chair of IEEE MELECON’26
and 5 th ICCSPA’22, Tutorial Co-Chair of IEEE MECOM’25, Track Co-Chair of ITC-
Egypt’22, Publicity co-chair of IEEE LCN’23 and VTC-Spring 2020, Demo Co-Chair of
ACM Mobicom 2013 and the Publication Co-Chair of IEEE Globecom’12 and
Mobiquitous’14. He is currently serving on the Editorial Board of Frontiers in
Communications and Networks – Data Science for Communications and IEEE TCCN
and served on the Editorial Board of IEEE TCCN, TMC and Wiley IJSC&N. He served
on NSF and Fulbright review panels. Dr. ElBatt was a Visiting Professor at Politecnico
di Torino in Aug. 2010, Sabanci University in Aug. 2013 and University of Padova in
Aug. 2015. Dr. ElBatt is a ComSoc Distinguished Lecturer, the recipient of the Google
Faculty Research Award in 2011, 2012 Cairo University Incentive Award in
Engineering, 2015 State Incentive Award in Engineering and the 2025 AUC Faculty
Merit Award for Excellence in Research. His research interests lie in the broad areas
of modeling, performance analysis, design and optimization of wireless networks,
mobile computing and IoT systems. He served as the IEEE Egypt Section Vice
Chairman (2020-2023). Dr. ElBatt is a Fellow of the African Academy of Sciences
(AAS) and a Senior Member of the IEEE.