Bio:
Prof. Iyad Dayoub is a Professor of Communications Engineering with a distinguished academic and professional trajectory.

He has been awarded a BEng in Electronics in 1993, and received his MSc in Electrical Engineering from Nancy University/INPL/France in 1997.
He earned his PhD in Wireless Communications in 2001 from Valenciennes University/IEMN in collaboration with Alcatel Business Systems/Colombes-Paris.
His career includes roles at Siemens-EWSD, Strasburg University, Supélec/Gif-sur-Yvette, and Alcatel Business Systems.
Currently, he is the Head of Telecommunications Technologies & Intelligent Systems Department at the IEMN-CNRS UMR 8520, and a professor at INSA HdF.

His past roles include serving on the National Council of Universities (CNU) in the area of Electrical Engineering, Electronics, Photonics, and Systems, and as an Adjunct Professor at Concordia University Montreal.
He has published over 250 papers in international journals and referred conferences, is an IEEE Senior Member, and serves on several journal editorial boards and international conference committees.

His research interests include 6G technologies such as mmWave communications, AI for wireless communications, NOMA, full-duplex communications, and ITS.

Abstract: Towards 6G: Standardization, Use-Cases, and Emerging Technologies - Application to ITS
6G is expected to transcend traditional notions of wireless connectivity, integrating various emerging technologies such as augmented reality (AR), virtual reality (VR), holographic communication, the Internet of Things (IoT), and the tactile Internet.

Emerging applications, including telemedicine and Intelligent Transport Systems (ITS), will require not only ultra-high data rates and low latency, but also new network architectures and service paradigms.

Although 6G is still in the early stages of development, standardization efforts and research into enabling technologies are already underway.

This conference will review recent and emerging technologies for future 5G/6G cellular communications, focusing on massive MIMO, millimeter-wave communications, non-orthogonal access (NOMA), and M2M communications.
It will also explore the application of these technologies in Intelligent Transport Systems (ITS), addressing both current systems and future research directions in Europe aimed at developing future European land transportation systems (railway and vehicular).

---

Bio:
Prof. Hasan Dincer is a distinguished academician in the interdisciplinary fields of business and finance, holding the position of Professor at Istanbul Medipol University in Turkey.

He completed his B.A. and M.A. from Marmara University and later went on to receive his Ph.D. from the same university.
With extensive international experience, Prof. Dincer has conducted research work at Hamburg University in Germany and served as a Research Professor at the University of Hertfordshire in the United Kingdom during the spring semester of 2019.
He has also worked as a Lecturer at Beykent University in Turkey from 2008 to 2015.

Prof. Dincer has a remarkable record of supervising theses at both the Master's and Doctoral levels. He has supervised successful theses on various topics of engineering, environmental, and social sciences.
With over 400 scientific articles to his name, many of which are indexed in high-impact journals like SSCI, SCI-Expanded, and Scopus, Prof. Dincer has contributed significantly to the academic literature.

He has focused his research work on a range of topics such as strategic management, innovation, sustainability, circular economy, decision making, as well as renewable energy investments, finance, and banking.
Prof. Dincer currently serves as associate editor and editorial board membership of outstanding SSCI/SCI/Scopus Journals. Apart from being the executive editor of the International Journal of Finance and Banking Studies (IJFBS), Prof. Dincer is also a founder member of the Society for the Study of Business and Finance (SSBF).
He has also served as an editor of several books published by Springer, Emerald, and IGI Global.

With exceptional teaching skills and academic achievements, Prof. Dincer is highly respected in the academic community. His valuable contributions to the interdisciplinary field of environmental and social sciences make him an asset to Istanbul Medipol University and the academic community at large.

Abstract: AI-based decision-making for expert prioritization and project assessment in Renewable Energy investments
The main purpose of this study is to make evaluations for the indicators of renewable energy investments in the agricultural sector of emerging economies.
For this purpose, a novel model is constructed that has three different stages.
Firstly, expert choices are prioritized with an artificial intelligence-based decision-making model.
Secondly, performance indicators of the renewable energy projects in the agricultural industry are weighted via quantum picture fuzzy rough sets-based M-SWARA.
Thirdly, investment priority alternatives are ranked by considering the quantum picture fuzzy rough sets based VIKOR technique.

The main contribution of this study is that artificial intelligence methodology is integrated with the fuzzy decision-making analysis.
With the help of this analysis, experts can be prioritized according to their qualifications.
According to the weighting results, it is identified that regulations play a crucial role for each group.

On the other side, the ranking results indicate that storage solutions play the most crucial role for the improvements of the renewable energy projects for the agriculture industry of emerging economies.

Bio:
Dr. Laurent Canale, PhD, Research Engineer and SMIEEE’19, was born in Saint-Martin d'Hères, France, in 1972.
He holds a master's degree and a doctorate in high-frequency electronics and optoelectronics from the University of Limoges, France, obtained in 1998 and 2002 respectively.
He published works on highly magnetic thin films, but his main area of interest has been the pulsed laser deposition of thin films of lithium niobate used for optical telecommunications.

From 2004 to 2010, he worked as a research engineer at the National Institute of Agronomic Research at the BioEMCo laboratory in Paris, France.
In 2010, he joined the National Center for Scientific Research (CNRS) and worked at LAPLACE Lab in the "Light & Matter" research group, focused on efficient light sources such as LEDs and OLEDs.
He has published more than 200 scientific communications, has been a part of the French Lighting Association as President of the Midi-Pyrénées region since 2014, and was honored with the Augustin Fresnel Medal in 2024.
He has served as President of the IEEE "Industry Lighting and Display Committee" (IEEE IAS ILDC) since 2023.

Abstract: "Light Yesterday, Today, and Tomorrow - An Everyday Perspective"
Artificial lighting has become as naturally evident to the point that we often overlook it, relegating it to the same ordinary necessity as the air we breathe. Without this artifact, humanity would not have even begun its evolution and would still be limited to mere survival.

The mastery of fire paved the way for learning and the transmission of knowledge by emancipating from the solar cycle.
This newfound independence led to the invention of writing, art, communication, and the development of agriculture, livestock, sciences… the development of humanity.

The mastery of light began with fire, then the torch, the oil lamp, the candle, the kerosene lamp, gas lighting, then electric lighting, fluorescent lamps, incandescence, and most recently, the ongoing revolution: LED lighting.

From fire to LED, 400,000 years of history of lighting sciences and techniques made up of evolutions and revolutions would take months of discourse to cover... Let us pause at the last moments of this long history to discover the latest arrival that has entered our homes and changed our daily lives: the Light Emitting Diode, or "LED."
Where did it come from? Who discovered it? Who invented it? When? Why? How?

---

Bio:
Prof. Adel Mellit received his PhD in Electronics from the University of Sciences and Technology (USTHB) Algiers in 2006.

Adel Mellit’s research interests include the application of artificial intelligence (AI) techniques, the Internet of Things (IoT) and embedded systems (ES) in solar photovoltaic plants.
He has authored and co-authored more than 200 papers in international peer-reviewed journals and conference proceedings, mainly on photovoltaic systems. He was the director of the Renewable Energy Laboratory at the University of Jijel, Algeria (2012-2022).

Associate member at the ICTP Trieste (Italy) since 2007, subject editor of Energy Journal (Elsevier, Ltd.), and editor of the IEEE Journal of Photovoltaics (JPV).

Abstract: Applications of machine learning and deep learning in photovoltaic systems: challenges, recommendations and future perspectives"
Recent focus on artificial intelligence (AI) techniques, such as machine learning (ML) and deep learning (DL), has spurred their utilization in tackling diverse issue within renewable energy domains, notably photovoltaic systems.

The potential applications of AI in photovoltaic systems include optimization, energy management, control, predictive maintenance, power forecasting, fault detection and diagnosis.
Overall, the application of AI in photovoltaics represents a paradigm shift in the field, unlocking new opportunities for sustainable energy generation.

In this talk, two selected topics will be covered:
1) photovoltaic power forecasting and 2) fault detection and diagnosis of photovoltaic plants.

Currently, these two subjects stand as pivotal and indispensable areas within the field of photovoltaics. Accurate forecasting of photovoltaic output power plays a crucial role in power planning, dispatching, optimal management, and ensuring grid quality and stability.
Designing of an accurate photovoltaic power forecasting models stay a challenging issue and a crucial task, as the photovoltaic power is extremely uncertain due mainly to solar irradiance variation.

A substantial number of photovoltaic plants have been installed globally in recent years, underscoring the need for meticulous protection and monitoring to prevent losses and mitigate the risk of fire.
Therefore, effective inspection methods and real-time diagnostics are essential and mandatory to prolong the lifespan of photovoltaic systems and ensure their safety. First, I will provide a concise introduction to AI, covering machine learning and deep learning concepts. Subsequently, I will delve into two commonly applied ML and DL applications in photovoltaic systems.

Throughout my presentation, I will try to answer and clarify the following questions:
when, why and how to apply ML or DL in photovoltaic systems.
The advantages and limits of AI-based methods in terms of feasibility, complexity, cost-effectiveness and generalization capability for large-scale integration, will be also discussed in this talk.
The conclusion of the presentation will summarize the challenges, offer recommendations, and outline future directions for both of these topics.

---