Dear students,

The IEEE Malaysia Communications Society & Vehicular Technology Society (ComSoc/VTS) joint Chapter would like to invite you to our upcoming IEEE ComSoc Distinguished Lecturer Program (DLP) by Prof. Tamer ElBatt from The American University in Cairo (AUC), Egypt that will be conducted as follows:

Lecture 1: Machine Learning and Edge Intelligence: Key Enablers for xG Wireless and IoT

Date: 21 August 2023 (Monday)

Time: 2:30pm – 4:00 pm (Malaysia) – Refreshment will be provided after the talk

Physical Venue: Bilik Sidang, Fakulti Kejuruteraan, Universiti Putra Malaysia, Serdang, Selangor

Co-organizers: WiPNET Research Centre, Dept of Computer and Communication Systems Engineering, Faculty of Engineering, UPM and IEEE UPM Student Branch

Lecture 2: Edge Computing and Communications: Fundamental Limits and Applications in Wireless Caching and IoT

Date: 22 August 2023 (Tuesday)

Time: 10:00am – 12:00 pm (Malaysia) – Lunch will be provided after the talk

Physical Venue: Bk17, Fakulti Kejuruteraan Elektronik dan Kejuruteraan Komputer (FKEKK) Universiti Teknikal Malaysia Melaka (UTeM), Melaka

Co-organizer: Wireless Broadband and Networking research group, Faculty of Electronic and Computer Engineering, UTeM

Lecture 3: Green Wireless: Optimization of Wireless Networks with RF Energy Harvesting

Date: 23 August 2023 (Wednesday)

Time: 10:00am – 12:00 pm (Malaysia) – Lunch will be provided after the talk

Physical Venue: Bilik Seminar 3, BATC, Universiti Teknologi Malaysia (UTM) Kuala Lumpur Campus

Co-organizers: Ubiquitous Broadband Access Network (U-BAN) Research Group, UTM and IEEE KL Subsection

ADMISSION IS FREE

Registration Link: https://bit.ly/3s6lTED

* Links for online participants will be e-mailed to registered participants.

** Please register by 11:59pm Wednesday 16th August 2023.

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Biography of Prof. Tamer ElBatt
Tamer ElBatt is currently a Professor at the CSE Dept., The American University in Cairo (AUC). He received the B.S. and M.S. degrees in EECE from Cairo University, Egypt in 1993 and 1996, 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, currently on leave. 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 Dept. of CSE 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 has published more than 140 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 is currently serving as an executive TPC Co-Chair of the 6th ICCSPA’24 and has served as the TPC Co-Chair of the 5th ICCSPA’22 and Track Co-Chair of ITC-Egypt’22, publicity co-chair of IEEE LCN’23, VTC-Spring 2020, Demos Co-Chair of ACM Mobicom 2013 and the Publication Co-Chair of IEEE Globecom 2012 and Mobiquitous 2014. Dr. ElBatt currently serves on the Editorial Board of Frontiers in Communications and Networks – Data Science for Communications and has served on the Editorial Board of IEEE TCCN, TMC and Wiley IJSC&N. Dr. ElBatt also 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 and 2015 Egypt’s State Incentive Award in Engineering. His research interests lie in the broad areas of modeling, performance analysis, design and optimization of wireless networks, mobile computing and IoT. He serves as the IEEE Egypt Section Vice Chairman since 2020 (re-elected for a 2nd term). Dr. ElBatt is a Senior Member of IEEE.

Abstract of Lecture 1: Machine Learning and Edge Intelligence: Key Enablers for xG Wireless and IoT
In this talk, we review recent results based on our work in the areas of machine learning for wireless and IoT systems with Edge Intelligence. In particular, we touch upon a sample of our work on deep learning-based proactive caching, Q-learning-based wireless access and IoT systems with edge intelligence. In the first part of the talk, we shed light on two samples of our work. The first is on deep learning-based proactive content caching using a public movie rating data set. We show the performance merits of the proposed E2E deep learning caching approach compared to a two-stage approach, among other baselines. Afterwards, we shift attention to a reinforcement learning problem formulation for channel access in dynamic spectrum access networks exploiting the primary user feedback. The studied schemes achieve performance comparable to classic optimization-based solutions, yet, with no/minimal knowledge about the primary user network. In the second part of the talk, we shift gears to the emerging paradigm of edge intelligence with focus on IoT. We design and prototype a multi-tier system, with distributed machine learning, for a use case of vehicle tracking based on data captured by roadside cameras. Using a public data set, the results reveal the merits of a three-tier system in terms of prediction performance compared to classic centralized machine learning on the same test set, yet, with a significant reduction in the training data.

Abstract of Lecture 2: Edge Computing and Communications: Fundamental Limits and Applications in Wireless Caching and IoT
In this talk, we review our recent work on edge computing and communications as a key enabler for future wireless networks. In particular, we present samples of our work on proactive caching, decentralized coded caching, cache-aided MIMO networks and edge networking for IoT and D2D communications. In the first part of the talk, we shed light on samples of our work on edge content caching, e.g. proactive, on-device caching. In addition, we present performance limits for decentralized coded caching in Fog Radio Access Networks with focus on the normalized delivery time (NDT) performance metric. Afterwards, we extend our discussion to cache-aided MIMO networks where we generalize prior studies to the case of arbitrary number of transmitters, receivers and antennas. We establish fundamental limits characterizing the relative contributions of the spatial multiplexing gain vs. the coded caching gain, with respect to reducing the delivery latency. In the second part of the talk, we shift our focus to edge networking with applications to IoT systems and opportunistic D2D communications. We propose a multi-tier IoT system, with distributed machine learning, for a vehicle tracking use case. The prediction performance, using a public data set, reveals the merits of the proposed three-tier system relative to centralized machine learning on the same test set, yet, with a significant reduction in the training data.

Abstract of Lecture 3: Green Wireless: Optimization of Wireless Networks with RF Energy Harvesting
In this talk, we review our work on energy harvesting wireless networks towards 6G and beyond. In particular, we touch upon sample work on RF energy harvesting wireless networks, e.g., wireless powered communication networks (WPCNs), Slotted Aloha with RF energy harvesting and simultaneous wireless and information power transfer (SWIPT) with Hybrid ARQ. In the first part of the talk, we shed light on two samples of our work on WPCNs. The first is on the optimized design of WPCNs with two types of nodes, namely RF powered nodes and legacy nodes. It reveals interesting insights about the performance and fairness of the studied system compared to prior work with RF energy harvesting nodes only. We then present WPCNs with non-orthogonal multiple access (NOMA) and propose approximate solutions due to the sheer complexity (non-convexity) of the formulated problems. We contrast two problem formulations, namely max-sum rate and max-min rate, and assess their performance merits and trade-offs. In the second part of the talk, we focus on establishing fundamental limits for Slotted Aloha with RF energy harvesting. We develop a model of interacting queues for a network with two user types. Our main contribution is to establish an inner bound on the stable throughput region via generalizing stochastic dominance arguments proposed in the literature. This reveals a key insight, that is, the stability region for RF energy harvesting Slotted Aloha is comprised of two sub-regions, namely interference-limited region and energy-limited region.

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Best regards,

PROF. DR. MOHAMAD YUSOFF ALIAS
Chair, IEEE Malaysia ComSoc/VTS Joint Chapter 2023/24
Counselor, IEEE Multimedia University Student Branch (STB65471)
Professor, Faculty of Engineering (FOE), Multimedia University (MMU), Cyberjaya, Selangor, MALAYSIA
Tel:+60(0)3-83125421, Fax:+60(0)3-83183029
Website: https://mmuexpert.mmu.edu.my/yusoff