Jean-François Ferrero is a Professor at Université Paul Sabatier (Toulouse III), where he directs the UMR 5312 ICA research unit and coordinates the Scientific College of Applied Sciences. He is also a member of the Department of Mechanics Council. His research group, Matériaux et Structures Composites (MSC), investigates impact dynamics, damage modeling, and crashworthiness of composite materials. His research interests include: Experimental mechanics of composite structures under impact Finite element analysis (linear/nonlinear) Hybrid composite material behavior Energy absorption in crash scenarios Recent publications (2019–2023) demonstrate a strong focus on: 3D digital image correlation for impact analysis Post-impact fatigue behavior of carbon/epoxy and glass/epoxy laminates Numerical modeling of intralaminar damage in thick composites Dynamic crushing of energy-absorbing tubular structures He teaches advanced courses in Finite Element Methods, Impact & Crash, and Composite Structures. As laboratory director, he oversees research on experimental characterization of structural adhesives and composite reinforcement techniques.
Mariel Alfaro-Ponce serves as an Assistant Professor in the Biomedical Engineering Program at Tecnológico de Monterrey's Campus Ciudad de México, where she leads the Manufacturing Processes for Advanced Materials research unit since 2022. Her academic journey spans biomedical engineering, microelectronics, and computer science, creating a unique interdisciplinary profile that bridges engineering disciplines with practical healthcare applications. Dr. Alfaro-Ponce earned her Bio-medical Engineering degree, Master of Science in Microelectronics Engineering, and PhD in Computer Science from Instituto Politécnico Nacional in Coyoacán, Mexico. This educational foundation has enabled her to develop innovative approaches at the intersection of multiple engineering disciplines. Her research program demonstrates remarkable breadth across several interconnected domains. She applies artificial intelligence techniques to develop rehabilitation devices and intelligent bioinstrumentation systems, with particular focus on neural network applications for medical diagnostics and prosthetics. Her work extends into sustainable manufacturing processes, including advanced 3D printing applications for both medical devices and food systems. The integration of machine learning with traditional engineering problems represents a consistent thread throughout her research portfolio, demonstrating how computational approaches can solve practical engineering challenges in healthcare and manufacturing. Analysis of her recent publications reveals a clear trajectory toward increasingly sophisticated applications of AI in biomedical contexts, with growing emphasis on sustainable manufacturing solutions. Her work spans from fundamental neural network research to practical implementations in medical devices, food engineering, and environmental applications. The interdisciplinary nature of her research connects computer science, electrical engineering, mechanical engineering, and biomedical applications through the unifying framework of machine learning and intelligent systems. National System of Researchers of Mexico (SNI-Level I) Mexican Researcher Certification - Level 1 Dr. Alfaro-Ponce's academic leadership extends beyond her research publications to include significant educational contributions. She teaches advanced courses including Design of Digital Bioinstrumentation Systems and supervises doctoral research across multiple disciplines. Her expertise aligns with multiple UN Sustainable Development Goals, particularly in areas of good health and well-being, industry innovation, responsible consumption, and clean energy. The practical orientation of her research suggests strong potential for technology transfer and real-world implementation of her innovations in medical devices and sustainable manufacturing systems. As leader of the Manufacturing Processes for Advanced Materials research unit in Mexico City, Dr. Alfaro-Ponce oversees a multidisciplinary team working at the cutting edge of sustainable manufacturing technologies. Her research group focuses on integrating artificial intelligence with advanced materials processing, particularly in medical device development and sustainable food production systems. The team's work demonstrates strong connections between theoretical machine learning approaches and practical engineering implementations across multiple application domains.
Dr. Ali Kadir is a Reader in Mechanical Engineering at the University of Salford's School of Science, Engineering & Environment. Previously serving as International Exchange Director for the School of Computing, Science and Engineering for nearly two decades until 2020, he currently acts as Admissions Tutor for BEng (Hons) and MEng (Hons) programmes in Aeronautical Engineering and Aircraft Engineering with Pilot Studies. With extensive teaching experience spanning Engineering Mathematics, Engineering Dynamics, and Mechanical Systems across multiple engineering disciplines, his academic career demonstrates deep commitment to engineering education. Dr. Kadir's educational background includes: BSc (Hons) Applicable Mathematics (Part Time, 1985-1991) - Project: Finite element analysis of heat transfer problems PhD in High temperature gas turbine micro and nanocoating CFD, FEA and experimental (Part Time, 2013-2021) His research spans multiple interconnected domains with primary focus on high temperature corrosion, micro and nano coating materials for jet engines, Finite Element Analysis, and Computational Fluid Dynamics. Additional research thrusts include biomechanics and orthopaedic engineering (particularly bone fracture analysis), electromagnetic smart materials, medical fluid dynamics, and renewable energy systems with nanofluid solar collectors. His methodology consistently integrates advanced mathematical modeling, finite element simulation, computational fluid dynamics, and experimental validation through flame spray coating techniques. Dr. Kadir's publication trajectory reveals strong interdisciplinary trends, with recent work (2022-2025) increasingly focused on nanofluid applications across aerospace, marine engineering, medical technologies, and renewable energy systems. His research demonstrates sophisticated integration of computational and experimental approaches to solve multi-physical engineering problems, with particular emphasis on nano-scale materials engineering and cross-domain applications. Professional recognition includes: Fellow of the Institute of Mathematics and its Applications (FIMA) As an active PhD supervisor, Dr. Kadir mentors students in high temperature corrosion modeling, nanocoatings development for aerospace/medical/marine applications, orthopaedic biomechanics (spinal analysis, bone stress modeling), and mathematical modeling of electromagnetic smart fluids. He serves as Associate Director of the Multi-physical Engineering Sciences Research Group (MPESG) under Prof. Anwar Bég, which provides critical infrastructure for computational and experimental research across engineering disciplines. The MPESG facilitates collaboration between theoretical modeling, simulation, and experimental validation, with strong industry connections in aerospace, marine engineering, and medical device sectors that enable translation of research findings into practical engineering solutions for complex real-world challenges.
