Dr. Alastair Hales (University of Bristol) is currently a Senior Lecturer at the University of Bristol, managing a small research team that focuses on the development of reduced order battery models and more sustainable battery technology. Alastair is a Co-I within the UK Faraday Institution’s Multi-Scale Modelling project and is working on the development of advanced parameterisation methods to reduce the complexity of battery models. Alastair has further ongoing research projects, supporting sustainable shipping through wind technology (Innovate UK) and collaborating with developers of second-life battery packs (EPSRC). Previously, Alastair completed a Faraday Institution Industry Fellowship, working to develop novel battery model parameterisation methods with exploit outstanding thermal control during experimentation.

Dr. Alper Kanak (ERARGE) received his BS from İstanbul Technical University, MS from Koc University, and PHD from Gebze Technical University all with honor degree in 2001, 2004 and 2013, respectively. He worked as a research and teaching assistant in Koc University between 2001 and 2003 and participated in a national project in the field of audio-visual speaker recognition. He then worked in TUBITAK and became a chief researcher for in 2008. He was employed in 5 projects and played a key role in establishing the Multimedia Technologies Reserarch Laboratory in TUBITAK. The great success of MULTISAUND project, which received the Turkiye’s first full score (15/15) in Framework Programmes, brough him the position of EU Projects Programme Manager of TUBITAK Research Institutes in Gebze between 2012 and 2015. In 2015, he started in ERARGE, Ergunler R&D Ltd. Co, as the R&D director and since then he has coordinated or co-coordinated 12 projects. He has taken full responsibility in full life cycle of national and international projects, i.e., Critical-Chains, Safety4Rails, Valu3s in Horizon 2020, ESCALATE, OPEVA, TEAMING in Horizon Europe, TioCPS, BIMy, C3PO in EUREKA-ITEA and 3 TUBITAK-TEYDEB national projects. He has published more than 50 papers in top journals and conferences in the fields of privacy-security-trust models, semantic Web and ontologies, cyber-physical systems, biometric security, speech and language technologies, and image/video processing.  He has also contributed to Türkiye’s ICT strategies as the national representative. Dr Kanak has lectured graduate courses on advanced topics of computer vision in Gebze Technical University, Türkiye.

Dr . Changfu Zou ( Chalmers University of Technology ) is an Associate Professor in the Automatic Control research unit at Chalmers University of Technology. He is leading a BMS research group, where the research covers topics ranging from microscale modelling of intercalation and dendrite formation, state and parameter estimation from traditional and new sensors, all the way up to fleet level modelling and estimation in the cloud. One highlight of his research focus is to blend physics-based and data-driven modelling approaches and to combine classical techniques with the latest machine learning techniques to derive adaptive feedback algorithms.

Dr. Fausto Stella (Politecnico di Torino) is a research fellow at Politecnico di Torino, Turin, Italy. His research interests include the design of power electronic converters, focusing on SiC semiconductors and reliability issues, and the control of converters via embedded systems.

Isabelle Dor ( CEA ) has graduated in solid mechanics engineering in 1987. She received the Von Karman institute diploma in fluid dynamic in 1988. She joined the CEA-Grenoble in 1989 and worked on thermal-hydraulics two-phase flow simulation for 25 years (cooling system of nuclear power plant). In 2014 she joined the CEA/LETI  and she has been involved in European projects coordination ever since.

Prof. Radu Bojoi (Politecnico di Torino) is a Professor at Dipartimento Energia “G. Ferraris,” Politecnico di Torino. He is also the Head of the Power Electronics Innovation Center at Politecnico di Torino. Radu is leading many research projects on power electronics and electrical drives for eMobility, with focus on design, fault tolerant control and proper exploitation on electrical vehicles.

Prof Salih Ergün (ERARGE) received his B. Sc. and M. Sc. degrees in 1998 and 2000, respectively, in electronics and telecommunication engineering from the Istanbul Technical University, Türkiye. Then, he received his Ph.D. degree in electrical engineering and information systems from the University of Tokyo, Japan, in 2011. In 2000, he joined the National Research Institute of Electronics & Cryptology, TUBITAK,Türkiye, where he was with the Cryptographic Hardware group as a manager. He has taken crucial roles in establishing research infrastructures of TÜTEL (IC Design and Education Laboratory) and prepared their feasibility and sustainability plans. In 2015, he founded ERARGE R&D Center in İstanbul and also founded ERGTECH Research Center in Switzerland to commercialize the productized devices for global markets. He has coordinated more than twenty national and international projects in various domains. Among these projects, C3PO (Collaborative City Co-Design Platform) received ITEA Award of Excellence 2018 for Business Impact and BIMy (Building Information Modelling in City) received ITEA Award of Excellence 2021 for Innovation. During his studies in TÜTEL, he actively participated in more than 5 projects including Horizon projects like EuroHPC-Pilot II, Beyond5 and MEEP. During his studies in ERARGE, he has had a leading role in both national and international projects: Critical-Chains, Safety4Rails, Valu3s in Horizon 2020, ESCALATE, OPEVA, TEAMING in Horizon Europe, TioCPS, BIMy, C3PO in EUREKA-ITEA and 3 TUBITAK-TEYDEB projects in smart and secure cyber-physical systems. His research interests are nonlinear circuits, random number generators, cryptography, security and privacy. He is an inventor of 12 international patents on security applications and published more than 120 papers in refereed journals and conference proceedings. He received three best paper awards at the European Conference on Circuit Theory and Design (ECCTD) 2005, the IEEE Asia Pacific Conference on Circuits and Systems (APCCAS) 2014 and Intelligent Information Hiding and Multimedia Signal Processing (IIHMSP) 2017.

Prof . Salim Hadj Saïd ( National Engineering School of Monastir ) received his PhD and his accreditation in Electric Engineering from National Engineering School of Tunis (ENIT) and National Engineering School of Monasir (ENIM) in 2009 and 2015, respectively.  He is currently Professor of automatic control in Preparatory Institute for Engineering Studies of Monastir (IPEIM), Tunisia. His research interests include Nonlinear Observation, Fault Detection and Isolation, Predictive and Adaptive Control, Tolerant Fault Control.

Dr. Sandro Rubino (Politecnico di Torino) is an Assistant Professor at Dipartimento Energia “G. Ferraris,” Politecnico di Torino. His main research interests include power electronics, modeling, and control of multiphase electrical machines and high-performance ac motor drives. Dr Rubino is an Associate Editor of IEEE Transactions on Industry Applications on behalf of the Industrial Drive Committee of the IEEE Industry Applications Society. He was the recipient of two paper awards from the Industrial Drives Committee of the IEEE Industry Applications Society.

Dr . Taoufik Ladhari ( National Engineering School of Monastir ) is affiliated with the Electrical Engineering Department at the National Engineering School of Monastir. Taoufik received his Electrical Engineering diploma in 2003 from INSAT, Tunisia. In 2004, he obtained his DEA in Automatic Systems from UPS-LAAS Toulouse, France, and his Master’s Degree from INSAT, Tunisia. He then earned his PhD degree in Process Engineering in 2007 from the National High School of Mines of Saint-Etienne, France. In 2019, he completed his Habilitation from ENIM, Tunisia. Currently, Taoufik serves as an Associate Professor at ENIM, focusing his research on the control and state observation of nonlinear systems, optimization of bioprocesses, and biomedical systems, Fault detection and isolation, Fault-Tolerant control.

Prof . Torsten Wik ( Chalmers University of Technology ) is Professor and Head of the Automatic Control research unit at Chalmers University of Technology. He focuses his research mainly on process control, involving methods and theoretical aspects as well as direct applications. Methods include optimal control, model reduction and systems with model uncertainties. The applications span energy materials, battery safety and design optimisation, thermal management and fast charging control.

Dr. Vincent Heiries ( CEA ) graduated from ENAC ( Civil Aviation National School ) and obtained his Msc from Toulouse Paul Sabatier University in 2003, where he specialised in digital communications and signal processing. He obtained a PhD in signal processing and digital communications from ISAE (Supaero, Toulouse, France). He has worked several years with THALES Space in the field of navigation satellite systems (GPS, GALILEO) for payloads development and for positioning/localization algorithms development. Since 2012, he is research engineer at CEA and his research activities are in the field of signal processing and machine learning applied to fault detection in electrical systems, fuel cell management systems, and battery management systems. Particularly, his research is focused on multi-physics sensors fusion for smart cells concept, and battery or fuel cell state indicators estimation algorithms. He is the author or co-author of more than 35 publications and main inventor or co-inventor of 20 patents.

Dr Ing Weihan Li (RWTH Aachen University) leads the junior research group, “Artificial Intelligence for Batteries”. The group develops technologies that integrate physics-based models and machine learning within battery research, empowering digitalized and intelligent approaches to battery production, testing and real-world application. Our research encompasses two core domains: At the material and component level, we are committed to enhancing image-based battery data analysis through deep learning. Our emphasis is on automating segmentation and detecting anomalies, ensuring the utmost accuracy and dependability. At the cell and system level, our expertise shines in battery modeling, parameterization, online monitoring, and control technologies, all aimed at ensuring the safe and reliable use of batteries. A special focus of our work is the fast characterization of the performance of batteries from the production lines with machine learning, accelerating battery production evaluation and optimization.