Bio:
Dr. Braham Himed received the Engineer Degree in electrical engineering from Ecole Nationale Polytechnique of Algiers, Algeria in 1984, and his M.S. and Ph.D. degrees both in electrical engineering, from Syracuse University, Syracuse, NY, in 1987 and 1990, respectively. Dr. Himed is a Research Fellow with the Air Force Research Laboratory, Sensors Directorate, Multi-Spectral Sensing and Detection Division, Passive RF Sensing Branch, in Dayton Ohio, where he is involved with several aspects of radar developments. His research includes detection and estimation, adaptive signal processing, waveform diversity and design, distributed active/passive MIMO radar, and over the horizon radar. Dr. Himed is the recipient of the 2001 IEEE region 1 award for his work on bistatic radar systems, algorithm development, and phenomenology. He is a Fellow of IEEE (Class of 2007), a past-Chair of the IEEE AESS Radar Systems Panel, and the AESS President-Elect. He is the recipient of the 2012 IEEE Warren White award for excellence in radar engineering. Dr. Himed is also a Fellow of AFRL (Class of 2013).

Abstract: Dual Function Radar and Communications
Recently, the problem of radio frequency (RF) spectrum congestion caused by the explosive growth and accelerating demand of the commercial wireless communications industry has been the focus of intensive research. During the last decade, several new concepts with the potential to contribute towards significant improvements in the efficiency of radio spectrum utilization have been introduced. The concept of coexistence between radar and communications offers a promising solution to one of the most pressing problems in the area of spectral congestion and dynamic frequency allocations by providing uncontested shared bandwidth between radar and communications. Dual system functionality, in which radar is the primary function, is the focus of this talk, where strategies for embedding communication signals in radar will be discussed. Depending upon the quality of service, error tolerance, and accuracy in signal estimation and target localization, dual functionality may require flexibility in beampattern synthesis and amenability to incorporate multiple transmit waveforms. This talk will provide an overview of recent advances in radar-embedded communication signals.

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Bio:
Lotfi BAGHLI (IEEE Senior Member 2012) was born in 1971. He received the Electrical Engineering Diploma degree (Hons.) in 1994 from the Ecole Nationale Polytechnique of Algiers, Algiers, Algeria. He received the DEA, and HDR PhD degrees in electrical engineering from the Universitéde Lorraine, Nancy, France, in 1995, 1999 and 2025 respectively. From 2000 to 2009, he was an Assistant Professor at Nancy University, Nancy. From 2009 to 2021, he was a Professor at Tlemcen University, Tlemcen, Algeria. Currently, he is an Assistant Professor at ENSEM, Nancy, and a member of Groupe de Recherche en Energie Electrique de Nancy. His research interests include digital control of electrical machines, metaheuristic algorithms applied to the control and identification of electrical machines, renewable energy and microgrids.

Abstract: Affordable Real-Time Power Electronics Control: Bridging the Gap Beyond High-End HIL/RCP Systems
These plenary addresses the implementation of Power Electronics converters and drives control on Digital Signal Controllers (DSC), specifically focusing on the challenges and solutions for achieving precise control in modern systems. We detail the necessary sensors for accurate control, including current sensors, temperature sensors, and an Inertial Measurement Unit (IMU) for instantaneous torque measurement. The keynotes explains a modern, cost-efficient DSC architecture and highlights the essential on-board features required, such as PWM, ADC, Quadrature Encoder Peripherals (QEP), and various communication protocols (CAN, SPI, I2C, UART). We demonstrate that the Texas Instruments F28379D LaunchPad is the optimal solution today for an affordable, industry-ready tool suitable for research and teaching in this field. While not a rival to high-end dSPACE MicroLabBox HIL/RCP solution, its programmability in C language allows for robust, self-driven expert control. The talk focuses particularly on onboard peripheral configuration and the appropriate selection of interfaces for sensors and Power Electronics control (e.g., Fiber Optic Connection). The discussion includes examples of driving 4Q buck converters, BLDC control using the TI inverter DRV8305EVM and potential communication considerations.

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Bio:
Yacine Amara (Senior Member, IEEE) received the Electrical Engineering degree from Ecole Nationale Polytechnique d'Alger, El-Harrach, Algeria, in 1997, and the Ph.D. degree from the University of Paris XI, Orsay, France, in 2001. He is currently with the Groupe de Recherche en Electrotechnique et Automatique du Havre, University of Le Havre, Le Havre, France, as a Full Professor, and the Head of the Electrical Machines and Actuators thematic. His research interests include the design, modeling, and control of rotating and linear synchronous machines for automotive and renewable energies applications.

Abstract: Hybrid Excited Synchronous Machines: A Technology Enabling Optimal Synergies
Hybrid excited synchronous machines (HESM) are synchronous machines where permanent-magnet (PM) excitation and wound field (WF) excitation are combined.The goal of hybrid excitation is to combine the advantages of PM excited machines and WF synchronous machines. HESM have been identified as one of the emerging technologies for modern energy conversion systems. They have been the subject of many review articles. The principle of hybrid excitation allows solving many drawbacks related to PM electric machines operation: flux weakening, energy efficiency, and PMs price fluctuation. It helps to introduce an additional degree of freedom in the design ofsynchronous machines, and allows therefore an easier adaptation of PM synchronous machines to a wider applications scope. The use of this technology for electric traction has been the subject of many scientific and technical contributions. In this talk, operating of these machines in motoring and generating modes will be addressed. For generating mode, the emphasis will be put on the use of these machines as generators in transportation applications and renewable energy applications. The design and operation of some HESM structures will be presented.

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Bio:
Fatma Zohra CHELALI received her engineering degree in Electronic Engineering from the University of Science and Technology Houari Boumediene (USTHB), Algiers, Algeria, in 1994. From 1997 to 2008, she worked as an assistant teacher at the High School of Aeronautical Technicians, where she taught courses in analog and digital telecommunications systems, digital electronics, basic electronic functions, and microwave systems. She pursued postgraduate studies from 2002 to 2003 and later earned both her "Magister" and Doctorate degrees in Speech Communication from the Faculty of Electronic Engineering and Computing at USTHB, in 2006 and 2012, respectively. She was promoted to Full Professor in July 2023. Currently, she is a lecturer at the Faculty of Electrical Engineering, University of Science and Technology Houari Boumediene (USTHB), Algiers, Algeria. Her research interests include human-machine interfaces, speech processing and recognition, the Internet of Things (IoT), artificial intelligence (AI), verbal and non-verbal communication, audiovisual recognition, as well as sign language recognition and translation, etc. Her name has appeared in Who’s Who in the World since 2012 and in the International Biographical Centre (IBC) of Cambridge since 2013. She has served as a reviewer for various journals published by IET and Elsevier. She was elevated to IEEE Senior Member status in September 2017 and has been active in the IEEE Algeria Section since 2015.

Abstract: Iot Based Gesture Recognition: Fundamentals and Advances.
The rapidly developing subject of IoT-based gesture recognition converts hand motions into digital commands for a variety of uses. The basic idea is to gather data from various sensors, such as cameras, flex sensors, accelerometers, and gyroscopes (typically found in wearable or smart gloves), followed by feature extraction, pre-processing, and classification through machine learning. Among the significant developments are the emergence of deep learning for improved accuracy, multimodal sensor fusion for resilience, and edge computing for real-time on-device processing. By enabling applications ranging from gaming and smart home control to crucial assistive technologies like real-time sign language translation for the hearing impaired, these advances encourage more natural human-machine engagement and enhanced accessibility. Real-time sign language translation and interpretation is being made possible by IoT-based gesture detection. The main tools used for the problem under consideration in this plenary are wearable sensors such as smart gloves with flex, accelerometer, and gyroscope sensors, and vision-based systems, which make use of cameras and sophisticated computer vision.

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