Anastasia Vasileiou is a Dalton Fellow in Advanced Nuclear Manufacturing at the University of Manchester's Department of Mechanical and Aerospace Engineering. She holds a Doctor of Engineering from the National Technical University of Athens (2014), specializing in precision casting and heat transfer optimization. Her research focuses on residual stress analysis in welding, surrogate modeling for digital experiments, and nuclear materials characterization. Vasileiou has conducted visiting research at the Australian Nuclear Science & Technology Organisation (ANSTO) in 2014-2016. Her work contributes to UN Sustainable Development Goals related to affordable and clean energy. Key research interests include: Physics-informed neural networks for thermal and neutronics simulations Inverse heat source calibration in welding processes Residual stress modeling in nuclear reactor components Surrogate models for fast prediction of physical fields Notable achievements include winning the CIUK Best Poster Prize (2024) and leading the Solid Mechanics Group project at Manchester. Her collaborative work spans 17 countries, with recent studies published in Fusion Engineering and Design , International Journal of Heat and Mass Transfer , and Journal of Visualized Experiments . She actively supervises PhD students in advanced manufacturing technologies. Vasileiou's research infrastructure includes the Dalton Nuclear Institute and Energy Advanced Materials platforms. Her work addresses critical challenges in nuclear energy systems and material integrity under extreme conditions.
Edward Luke is a Professor in the Department of Computer Science and Engineering at Mississippi State University's Bagley College of Engineering. His research focuses on parallel algorithms and scientific computing, with particular expertise in computational fluid dynamics applications including turbulence modeling, aerodynamics, and multiphase flows. His publications demonstrate strong emphasis on developing advanced computational methods for aerospace and fluid dynamics problems. Recent work explores machine learning-based surrogate modeling, hypersonic flow simulations, and turbulence model assessments. Articles show consistent focus on high-performance computing applications in fluid-thermal systems, aerothermodynamics, and propulsion engineering. Dr. Luke maintains active research in computational mechanics, with recent investigations spanning atmospheric science experiments, reduced-order modeling techniques, and advanced solver development for complex multiphysics problems, particularly in aerospace contexts.
Aleksander Czekanski is a Professor in the Department of Mechanical Engineering at York University's Lassonde School of Engineering. He serves as co-Director of the Manufacturing Technology and Entrepreneurship Centre and previously held the NSERC Chair in Design Engineering. His expertise spans Additive Manufacturing, Bioprinting, Material Characterization, and Artificial Intelligence in Engineering Education. He holds an MBA from York University's Schulich School of Business and a Ph.D. in Mechanical Engineering from the University of Toronto. Dr. Czekanski's research focuses on advanced materials, including soft and super-soft materials, topology optimization, and in-situ bioprinting. He has pioneered studies on 4D printing, fatigue analysis of natural rubbers, and microstructural evolution in additive-manufactured alloys. His work bridges computational modeling with experimental validation, addressing challenges in both industrial and biomedical applications. Received the President's University-Wide Teaching Award and Lassonde Innovation Award. Served as CSME Board Director (2014-2024) and President of the Canadian Engineering Education Association (2020-2021). Active in professional leadership roles, including Fellowships in CSME, CEEA, and the Engineering Institute of Canada. His research outputs emphasize cross-disciplinary innovation, with over 80 publications spanning material science, manufacturing processes, and engineering education. Current projects include developing smart hydrogels for 4D printing and optimizing topology for fluid-structure interaction systems.
Raymond A. Yeh is an Assistant Professor in the Department of Computer Science at Purdue University since Fall 2022. Previously, he was a Research Assistant Professor at Toyota Technological Institute at Chicago (TTIC) and completed his PhD in Electrical Engineering at the University of Illinois at Urbana-Champaign (UIUC) in 2021. His research focuses on machine learning and computer vision, particularly in developing algorithms for effective and explainable models across audio, vision, language, and multi-agent systems. Education: Ph.D., Electrical Engineering, UIUC (2021) M.S., Electrical Engineering, UIUC (2016) B.S., Electrical Engineering, UIUC (2014) Research Interests: His work bridges machine learning and computer vision, emphasizing equivariance in neural networks, robustness, and scalable algorithms. Key areas include: Generative models (diffusion models, inpainting) Equivariant deep learning architectures Multi-modal reasoning (vision-language) 3D reconstruction and simulation Recent Contributions: Recent work includes model immunization techniques, scale-equivariant networks, and novel datasets like Tree-D Fusion. His publications span top venues (CVPR, NeurIPS, ECCV) with 4,551 total citations (h-index 18 as of 2025). Awards: Google PhD Fellowship (2018) Best Paper Runner-up at CVPR Workshop (2024) National Science Foundation (NSF) Grant (2024) Purdue Seed for Success Award (2024) Teaching: Courses include Introduction to AI, Computer Vision with Deep Learning, and Foundations of Deep Learning. Student evaluations consistently score above 4.5/5.0. Labs: Leads the Purdue Vision and Learning Lab, focusing on advancing AI through robust, interpretable models with practical real-world applications.
Prof. Duc Nguyen is a Professor in the Department of Civil & Environmental Engineering at Old Dominion University (ODU), affiliated with the Batten College of Engineering and Technology. His expertise spans Computational Mechanics, Finite Element Analysis (FEA), Structural Dynamics, and Parallel Computing. He has held numerous prestigious roles, including NASA-ASEE Fellowships and the 2010 ODU Shining Star Award. Nguyen holds a Ph.D. from the University of Iowa (1982), M.S. from the University of California (1976), and B.S. from Northeastern University (1974). Research focuses on large-scale algorithms for parallel supercomputing, design sensitivity analysis, sparse linear solvers, and multiphysics CAD-based optimization. He has led grants totaling over $2 million, including projects on numerical methods, engineering education, and structural analysis. Notable publications address parallel finite element methods, structural/acoustic coupling, and optimization using genetic algorithms. Awarded honors include recognition for citation impact (2004), teaching excellence (2001), and computational performance (1989). His work bridges computational efficiency with engineering applications, emphasizing interdisciplinary collaboration. Current research explores MPI-enabled algorithms, multi-hazard risk assessment, and coastal infrastructure resilience.
Ramin Rahmani is a Senior Lecturer in Tribology and Dynamics at Loughborough University, affiliated with the Wolfson School of Mechanical, Electrical and Manufacturing Engineering. His academic journey includes a BSc and MSc in Mechanical Engineering, followed by a PhD in Tribology. He transitioned from a Research Associate role into his current faculty position. His research focuses on tribology, dynamics, and mechanical systems, with emphasis on automotive components, lubrication, gear dynamics, and energy efficiency. Notable areas include the tribological performance of coatings, electrotribodynamics, and lifecycle assessments of alternative fuels in heavy-duty vehicles. Recent publications highlight advancements in hydrogen fuel applications, lubricant behavior in extreme conditions, and NVH (Noise, Vibration, Harshness) mitigation in electric vehicle powertrains. His work bridges theoretical modeling with experimental validation, addressing both academic and industrial challenges. Rahmani received the Associate Editor’s Recognition (2025) for his contributions to scholarly publishing. His research group, Dynamics & Tribology , explores cutting-edge topics including surface texturing, nanolubricants, and transient elastohydrodynamic analysis. While no specific grants or advising roles are detailed, his publications reflect a prolific engagement with interdisciplinary tribological challenges across automotive, aerospace, and renewable energy sectors.
Dr. Dave C.J. Krop is a full-time Assistant Professor in the Electromechanics and Power Electronics department at Eindhoven University of Technology (TU/e). His expertise includes linear motors, contactless energy transfer, and advanced actuator design with a focus on superconducting and high-dynamic applications. Prior to his full-time position since 2018, he held a part-time role and worked in industry roles at Punch Powertrain and Vostermans Ventilation. Krop holds a B.E. in Electrical Engineering (2004), M.Sc. in Electrical Engineering (2007), and Ph.D. in Electromechanics and Electromagnetics (2013), all from TU/e. His research emphasizes electromagnetic device modeling, finite element analysis, and the integration of energy transfer systems with actuators. Notable contributions include a patented linear motor with contactless energy transfer (2013) and pioneering work on high-dynamic superconducting linear motors. He has authored/co-authored 15 conference papers, 3 journal articles, and a book. Research Highlights: Developed HTS linear motor designs for high-dynamic applications using electromagnetic-thermal analysis Advanced MIMO magnetic levitation actuator control using neural networks Optimized PM-based planar actuators through semi-analytical modeling Awards: Best Paper Award (2018), Invited Paper Award (2013) Grants & Collaborations: Participated in STW-funded projects (2015–2024) focused on superconducting motors, automotive powertrains, and cooling systems. Collaborated with industry partners and academic teams on modular electric drives and energy-efficient systems. Labs/Teams: Involved with the Electromechanics Lab and High Tech Systems Center at TU/e, contributing to interdisciplinary projects in sustainable energy and precision engineering.
Xinxin Yu is an Assistant Professor (tenure-track) at Tampere University's Faculty of Engineering and Natural Sciences, leading the Machine Dynamics Group and managing the Full-scale Wheel-rail Lab. Her expertise spans multibody dynamics, friction estimation, and vehicle dynamics integration with AI/computer vision. She holds a PhD from LUT University (2021) and has held postdoctoral positions at the University of Seville (Spain) and Delft University of Technology (Netherlands). Education: PhD in Mechanical Engineering, LUT University, 2021 (Distinction) Research Focus: Dr. Yu's work bridges classical engineering with modern tech, focusing on multibody dynamics, frictional contact estimation, and computational/experimental vehicle dynamics. She explores AI-driven solutions for dynamic system simulations in automotive and mechanical systems. Key areas include wheel-rail contact modeling, real-time track irregularity detection, and multiphysics modeling for forestry cranes. Awards: 2024: Best Theoretical Award (Honourable Mention) – MMT Symposium 2023: Marie Skłodowska-Curie Fellowship 2022: Lagrange Award (Honourable Mention) – Multibody System Dynamics Leadership & Editorial Roles: Editorial Board Member – Multibody System Dynamics Journal (2024–present) Associate Editor – Mechanism and Machine Theory Journal (2024–present) Chair Secretariat – IFToMM Multibody Dynamics Committee (2024–present) Labs/Teams: Leads the Full-scale Wheel-rail Lab and Machine Dynamics Group, collaborating on projects like DETECT4WE and DIGIWHEEL.
Prof. Dr. Dirk Reith is a Research Professor at the Department of Engineering and Communication , Bonn-Rhein-Sieg University of Applied Sciences. He serves as Director of the Institute of Technology, Resource Conservation and Energy Efficiency (TREE) and holds roles such as Senior Consultant at Fraunhofer SCAI and Presidential Representative for Institutional Research Collaborations. Reith is also a Faculty Advisor for the BRS Motorsport (Formula Student) team. Education: Physics and Mathematics at Johannes Gutenberg University Mainz and Uppsala University, Sweden. Research Focus: Molecular simulations of soft materials (polymers, ionic liquids), computational fluid dynamics (Lattice-Boltzmann), fluid-structure interaction, and innovative engineering education methods like Problem-Based Learning (PBL) and peer mentoring. Leadership: Director of TREE Institute, co-founder of Digital Twin-4-Multiphysics Lab (Fraunhofer SCAI, Reinold Hagen Foundation), and active in interdisciplinary projects such as PAExSiDur (polymer aging), KIMODE (AI-optimized design), and UMMBAS (molecular modeling for biochemical applications). Awards: Recipient of the 2020 Teaching Prize at H-BRS for integrating peer teaching in Formula Student projects. Collaborations: Visiting Professor at UC Davis (2017), partnerships with GKN Driveline, Yarmouk University, and DFG-funded initiatives. Reith's work bridges computational methods, sustainability, and education, with projects like TRE³L (hydrogen energy lab) and ROFEE (resource-efficient e-mobility) highlighting his commitment to applied research and resource conservation.
Dr. Chérif Larouci is an Associate Professor and researcher at ESTACA (Higher School of Aeronautics and Space), where he has served as a teacher-researcher since 2002. Currently, he leads the Embedded Systems and Energy for Transport (S2ET) division, a position he has held since 2013. His academic career at ESTACA also included heading the Command and Systems Team from 2006 to 2013. In 2012-2013, he obtained Authorization to Supervise Research at the University of Paris-Sud 11. Dr. Larouci's educational background includes a PhD in Electrical Engineering from the National Polytechnic Institute of Grenoble (INPG) in 2002, with a thesis on "Design and optimization of static converters for power electronics; Application to sinusoidal absorption structures." Prior to that, he earned an Advanced Studies Diploma (DEA) in Electrical Engineering at INPG (1998-1999) and an Engineering Diploma from the National Polytechnic School of Algiers, specializing in Electrotechnics (1993-1998). His research focuses on power electronics, embedded systems, and energy management for transportation systems, particularly electric vehicles. Dr. Larouci's work spans multiple domains including power converter design, fault-tolerant control systems, energy management strategies, and multiphysical optimization of automotive components. His research has significant applications in electric vehicles, autonomous vehicles, more-electric aircraft, autonomous drones, and various electric transportation systems. Analysis of his recent publications reveals a strong emphasis on optimization techniques for power electronics in transportation applications. His work increasingly integrates multidisciplinary approaches, combining electrical engineering with mechanical, thermal, and control aspects. Recent trends show growing focus on sustainable transportation solutions, battery management systems, and intelligent energy management for electric mobility. His research bridges theoretical developments with practical automotive applications, often involving industry collaborations. IEEE Senior Member (elevated in March 2012) Member of the publication committee of the 3EI journal since 2004 Reviewer for numerous international journals and conferences Expert evaluator for collaborative projects (FUI, ANR, H2020, ADEME, regional projects) Dr. Larouci actively participates in research funding and collaboration through various channels. He has been involved in numerous research contracts and collaborative projects with industry partners. His leadership extends to coordinating the S2ET division, which comprises 20 teacher-researchers, 20 PhD students, and 6 technical and administrative support staff. He also contributes to strategic research directions as a member of several competitive clusters including MOVEO/Nextmove, ID4Car, and Astech. The S2ET division under Dr. Larouci's leadership serves as a comprehensive research environment focusing on embedded systems and energy solutions for transportation. The division maintains strong industry connections and participates in multiple national and European research initiatives. Current research directions emphasize electrification of transportation, autonomous vehicle systems, and sustainable mobility solutions, with particular attention to power electronics and energy management challenges.
David LE TOUZÉ is a Professor of Fluid Mechanics and Director of the Research Laboratory in Hydrodynamics, Energetics & Atmospheric Environment (LHEEA) at Centrale Nantes. His research focuses on advanced computational methods in fluid dynamics, particularly Smoothed Particle Hydrodynamics (SPH) and its applications to ocean engineering, wave-structure interactions, and multiphase flows. Research Interests: Prof. LE TOUZÉ's work spans: Development of high-fidelity SPH algorithms for complex fluid-structure interactions Hydrodynamic modeling of offshore structures and wave energy converters Numerical wave tanks and experimental validation techniques Multi-scale coupling methodologies (SPH-FEM, SPH-FV) Free-surface flows and multiphase systems Publication Focus: His recent publications demonstrate strong emphasis on: 1) SPH methodology enhancements for industrial applications, 2) Experimental-computational synergy in marine hydrodynamics, and 3) Novel approaches to modeling fluid-elastic systems. Dominant themes include wave-structure interactions, particle method optimizations, and marine renewable energy applications. Laboratory Leadership: Directs the LHEEA laboratory, coordinating research in hydrodynamic systems, atmospheric environment studies, and marine renewable energy technologies through the MÉLUHSINE IIHNÉ research group.
Michele Goano is a Full Professor in the Department of Electronics and Telecommunications (DET) at the Polytechnic University of Turin. He serves as Coordinator of the Doctoral School in Electrical, Electronics and Communications Engineering and is a member of both the PhotoNext Interdepartmental Center for Applied Photonics and the Doctoral School Council. His contact information includes phone number +39 0110904142 and email michele.goano@polito.it. Professor Goano's research spans multiple areas of optoelectronics and semiconductor physics. His primary interests include multiscale physics-based modeling of optoelectronic devices, far-infrared image sensor design, Si and III-V photonic integrated circuits, multiphysics CAD of vertical-cavity surface-emitting lasers (VCSELs), efficiency and reliability of visible and UV light-emitting diodes, and full-band Monte Carlo electron transport simulation. His work connects fundamental semiconductor physics with practical device applications, particularly in photonics and optoelectronics. His publication record shows consistent contributions to the field since the early 2000s, with recent work focusing on silicon photonics, infrared detectors, and advanced modeling of LED efficiency issues. The publications demonstrate a progression from fundamental band structure calculations to applied device modeling and optimization, with strong industry connections through commercial research contracts. Professor Goano actively supervises numerous PhD students across multiple research areas including radiation detectors, silicon photomultipliers, photonic integrated circuits, and semiconductor device modeling. He has secured significant research funding through both competitive international grants and commercial research contracts, particularly in the areas of infrared detector technology and silicon photonics. He is a member of the Microwave and Optoelectronics Group (MOG) within DET and has coordinated the Doctoral School in Electrical, Electronics and Communications Engineering for multiple cycles. His teaching portfolio includes courses on semiconductor device CAD, electronic transport in semiconductors, and specialized topics like VCSELs.
Professor Boris Balakin is affiliated with the Department of Mechanical Engineering and Maritime Studies at Western Norway University of Applied Sciences (HVL). His research focuses on multiphysics phenomena in industrial systems, including boiling, heat transfer, multiphase flows, turbulence, electrochemistry, and particle deposition. Specializes in CFD-DEM, Eulerian two-fluid, and VOF methods for multiphase flow modeling. Investigates renewable energy applications like nanosystems for solar and geothermal energy. Conducts non-invasive experimental validation using CT and PEPT techniques. Research Trends: Recent publications emphasize nanofluids for solar thermal systems, CFD modeling of industrial multiphase flows, and flow assurance in pipelines. Key subfields include photothermal conversion, particle agglomeration, and erosion analysis. Academic Leadership: Supervises PhD candidates in projects related to heat transfer, CFD modeling, and flow assurance. Teaches advanced courses like MAS536 CFD in Energy Technology and contributes to research groups on Solar Nano and Nanofluids for Energy and Process Technology .
Xiang Zhang serves as Associate Professor in the Department of Mechanical Engineering at the University of Wyoming, where he has held a faculty position since 2019. He directs the Computations for Advanced Materials and Manufacturing Laboratory (CAMML), focusing on establishing microstructure-processing-performance relationships through advanced computational models. His work bridges material microscale phenomena with structural-scale applications in high-performance materials and manufacturing processes. His educational foundation includes: Ph.D. in Civil Engineering from Vanderbilt University (2017) M.S. in Solid Mechanics from Beihang University (2012) B.S. in Engineering Mechanics from Northeastern University (2009) Dr. Zhang's research centers on multiscale and multiphysics computational modeling, with emphasis on deformation and damage mechanisms in metals and composites. His group develops crystal plasticity finite element models, interface-enriched generalized finite element methods (IGFEM), and reduced-order homogenization techniques. Current projects target frontal polymerization for composite 3D printing, metal additive manufacturing, and microstructure-informed material design. This work integrates computational modeling with experimental validation to solve challenges in structural integrity and manufacturing efficiency. Recent publications (2019-2023) reveal strong thematic continuity in multiscale modeling of composite manufacturing processes, particularly frontal polymerization applications in 3D printing. His work consistently connects microscale material behavior (e.g., crystal plasticity, interface damage) with structural performance through reduced-order modeling frameworks. Key journals include Computer Methods in Applied Mechanics and Engineering , Composite Science and Technology , and Additive Manufacturing , demonstrating cross-disciplinary impact in computational mechanics and materials engineering. His honors include: NSF CAREER Award (2023) for multiscale modeling of hybrid composites Dolling & Scott Faculty Research Award (2022) Multiple national conference awards including Melosh Medal Finalist (2017) Student paper competitions at Engineering Mechanics Institute (2016) Dr. Zhang actively mentors graduate researchers through CAMML, currently advising three PhD students and one MS student, with eight alumni completing degrees under his supervision. His NSF CAREER grant enables integrated research, education, and workforce development partnerships with Idaho National Laboratory, industry collaborators, and university centers including the School of Computing and Advanced Research Computing Center. The lab maintains strong industry connections for technology transfer in advanced manufacturing. The CAMML laboratory operates within the University of Wyoming's R1 research infrastructure, maintaining collaborations with Vanderbilt University, University of Illinois, and national laboratories. Current projects involve metal 3D printing, frontal polymerization composites, and reduced-order modeling frameworks, supported by state-of-the-art computational resources. The team actively recruits graduate students for positions requiring expertise in computational mechanics, materials science, and programming.
Hector Gomez is a Professor of Mechanical Engineering and Courtesy Professor of Biomedical Engineering at Purdue University’s School of Mechanical Engineering. He leads the Gomez Lab, focusing on computational mechanics, multiphase systems, and biomedical applications. His research bridges engineering and medicine through advanced modeling of interface problems, including tumor growth, fluid-structure interaction, and biomechanics. Education: Ph.D. in Civil Engineering from Universidade da Coruña, Spain. He also holds a Civil Engineering degree from the same institution. His work integrates isogeometric analysis, phase-field methods, and high-performance computing. Research Interests: Modeling multiphase and multiphysics systems using phase-field methods; isogeometric methods in fluid/solid mechanics; tumor growth simulation; computational fluid-structure interaction. His lab collaborates on prostate cancer growth forecasts using MRI data and personalized biomechanical models. Key Achievements: ERC Starting Grant (2012), MIT Technology Review Innovators Under 35 (2014), Princess of Girona Scientific Award (2017), USACM Fellow (2023). His team develops open-source tools for multiphysics simulation. Grants & Funding: Includes ERC grants, USACM awards, and Purdue University faculty scholarships. Active in computational oncology, drug delivery (subcutaneous injection modeling), and soft material mechanics. Labs/Teams: Gomez Lab at Purdue, specializing in computational engineering and medicine. Collaborations with biomedical researchers and industry on personalized medicine and medical device design.
