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Gudrun KlinkerView profile

Professor

• Industrial Augmented Reality
• Sensing
• Ubiquitous Tracking (Sensor Fusion)
• +4 more

Overview Prof. Gudrun Klinker is a Professor at Technische Universität München (TUM), leading the Chair of Computer Science Applications in Medicine & Augmented Reality. She holds a PhD from Carnegie-Mellon University and has extensive experience in academia and industry, including roles at Digital Equipment Corporation and Fraunhofer Institute. Affiliations Professor (C3/W2) since 2000 Head of the FAR (Augmented Reality) research group Member of the CAMP (Computer Aided Medical Procedures) interdisciplinary team Research Dr. Klinker specializes in augmented reality (AR) with focuses on industrial applications, sensor fusion, 3D interaction, and healthcare integration. Her work bridges computer science with medical and industrial challenges, emphasizing user-centric design and real-world deployment. Key projects include: AR-based maintenance systems for complex machinery Healthcare applications like serious games for nutrition education VR/AR training environments for medical and aerospace domains Awards and Recognition Robert Sauer Prize (2010) for contributions to Bavarian science ISMAR Lasting Impact Award (2014) for influential AR research Teaching and Mentorship Prof. Klinker teaches courses on 3D user interfaces, AR fundamentals, and game design. She advises students in thesis projects, focusing on AR applications, HCI, and medical computing. Labs and Collaborations Her research is supported by partnerships with industry and institutions, leveraging TUM's interdisciplinary environment to advance AR/VR systems for real-world impact.

• Sports Business Management
• Data Analytics
• Wearable Technologies
• +7 more

Jayamini Ranaweera is a Senior Lecturer in Sports Business Management and Data Analytics at Edge Hill University's Department of Sport and Physical Activity. Previously, he worked as a Lecturer in Performance Analysis at St Mary's University (2022-2024) and as a Data Scientist for Bath Rugby (2019-2022). He holds a PhD in Sport Informatics from Leeds Beckett University and advanced engineering degrees from the University of Moratuwa, University of Sri Jayewardenepura, and Sheffield Hallam University. Current Role: Senior Lecturer at Edge Hill University Former Roles: Lecturer at St Mary's University, Data Scientist at Bath Rugby Education: PhD (Sport Informatics), MSc (Electronics & Automation Engineering), BSc (Applied Sciences), BEng (Electronic Engineering), PGCAP Jay's research interests span digital optimization of athlete management systems, wearable technology development, and data science applications in sports performance. He also explores process improvement methodologies (Lean, Six Sigma, BPM) in sports contexts and has active collaborations in rugby union analytics. His recent work includes digital dashboards for basketball clubs and load factor analysis in rugby small-sided games. Key research trends include: Sports data analytics (2025: 2 articles, 2024: 2, 2023: 1, 2022: 4) Wearable technology applications (2025: 1 article, 2021: 1) Rugby union biomechanics (2024: 2 articles, 2023: 1, 2022: 1) Digital transformation in sports (2025: 1, 2024: 1, 2020: 2) Jay has received professional recognition as a Chartered Engineer (CEng), Member of the Institution of Engineering and Technology (MIET), and Fellow of the Higher Education Academy (FHEA). He actively teaches on the BSc Sport Management program and applies his industry experience from MAS Holdings (2013-2019) in product development and digital transformation to both academic and practical contexts.

Cesar RuizView profile

Assistant Professor

• Metal Additive Manufacturing
• Process-Informed Machine Learning
• Quality Control
• +3 more

Cesar Ruiz is an Assistant Professor in the Department of Industrial & Systems Engineering at The University of Oklahoma. His research focuses on integrating domain knowledge with machine learning and stochastic modeling for engineering applications, particularly in metal additive manufacturing, predictive maintenance, and quality control. He holds a Ph.D. and M.S. in Industrial Engineering from the University of Arkansas and a B.A. in Business Engineering from the Higher School of Economics and Business in El Salvador. His research domains include metal additive manufacturing processes, process-informed machine learning frameworks, and reliability evaluation in complex systems. Notable works address challenges in layer segmentation for quality assessment, predictive maintenance strategies, and degradation-based reliability analysis. Ruiz has received prestigious awards such as the RAMS Golomski Award (2020, 2022), ASQ Best Reliability Paper (2021), and IEEE CASE Best Conference Paper (2021). His affiliations include SRE, INFORMS, and ASME. His research spans aerospace and defense systems, with recent publications emphasizing advanced manufacturing techniques, functional data analysis, and Bayesian modeling for reliability growth. He collaborates on projects involving biosensor optimization and large-scale system maintenance frameworks.

Paul de VriezeView profile

Academic

• Enterprise Information Systems
• Business Process Management
• Digital Twins
• +12 more

Dr. Paul de Vrieze is a Principal Academic in Web Systems and Technologies at Bournemouth University's Faculty of Science and Technology, Department of Computing and Informatics. He is the coordinator of the EU H2020 FIRST project and leads research in enterprise information systems, digital twins, and Industry 4.0. His work contributes to the UN Sustainable Development Goals, particularly Quality Education, Decent Work and Economic Growth, Industry Innovation and Infrastructure, and Reduced Inequalities. Education: PhD in Information Systems, Radboud University Nijmegen, 2006 MSc in Information Systems Management, Tilburg University, 2002 His research focuses on the design and implementation of complex enterprise information systems, especially in supporting and automating business processes, with a strong emphasis on cross-organizational and collaborative systems. He investigates resilience, interoperability, and service-oriented architectures in virtual factories and digital twins. His recent work applies these concepts in industrial contexts, particularly under Industry 4.0. The 15 most recent publications show a strong trend toward digital twin technologies, predictive maintenance, federated simulation, and compliance in collaborative networks. These works are deeply rooted in computer science and industrial engineering, with applications in smart manufacturing, supply chain resilience, and sustainable production. Scientific Awards and Recognitions: Panel Member, Guardian round table on cloud computing, 2012 Dr. de Vrieze has supervised multiple PhD students to completion, including Olaolu Sofela, John-Paul Kasse, Oluwetoyin Fakorede, Go Sang, and Rushan Arshad. He has secured grants from the European Commission (H2020, Horizon Europe), National Natural Science Foundation of China, British Council, and internal Fusion Funding. His current major grant is the Sustainable Production of High Entropy Alloys from Secondary Metals (Horizon Europe MSCA, starting 2026). Labs and Research Teams: He is central to the EU H2020 FIRST project team, which focuses on virtual factories and interoperation supporting business innovation. He collaborates extensively with Prof. Liang Xu and researchers across Europe and China. He is also involved in the Service Computing Research group at Bournemouth University.

• Design Methodologies
• Manufacturing Process Planning
• Machining Process Characterization
• +2 more

Professor Joaquim de Ciurana Gay is a faculty member at the University of Girona in the Department of Mechanical and Industrial Construction Engineering , leading research in Manufacturing Process Engineering since 2009. He heads the Process, Product and Production Engineering Research Group (GREP) , with over 100 peer-reviewed articles and 12 book chapters focusing on biomedical device design, additive manufacturing, and machining optimization. Education: PhD in Industrial Engineering (UPC, 1997); Postdoctoral training at Rutgers University, Cranfield University, and Université du Québec à Trois-Rivières. Research Interests include additive manufacturing , machining process characterization , design methodologies , and industrial collaboration . His recent biomedical projects emphasize cell culture systems and medical device prototyping . Publications highlight trends in hybrid manufacturing , AI-driven process optimization , and sustainable biomedical design . Scientific Awards: Award for Scientific Collaboration with Companies (ASCAMM Centre Tecnològic, 2011) Teaching Innovation: Authored educational materials and led projects integrating industry partnerships into academic training. Labs & Teams: Director of GREP, fostering knowledge transfer through collaboration agreements with industrial partners.

Richard ZowallaView profile

Researcher

• Health Informatics
• Web Data Mining
• Text Mining
• +4 more

Dr. sc. hum. Richard Zowalla is a researcher at the Faculty of Computer Science, Heilbronn University, specializing in health informatics and software engineering. He works at the Interdisciplinary Center for Machine Learning (ZML) and focuses on health web analysis, text mining, and open source software. Education: Doctorate in human sciences (Dr. sc. hum.), dissertation on German health web data analysis (2022) Research interests include health information systems, focused web crawling, text mining, and software quality management in agile environments. His work bridges healthcare and computer science through data-driven analysis of online medical resources. Publication trends show expertise in health web readability, multilingual health data comparison, and AI-driven service innovation. His articles emphasize practical applications of machine learning and data visualization in healthcare contexts. Teaching: Software Lab (2016-2025), Advanced Programming Techniques (2020-2024), Database Internship (2014-2025), Distributed Systems (2016-2017) Labs & Teams: Active member of the Interdisciplinary Center for Machine Learning (ZML) at Heilbronn University, contributing to collaborative research in health data analysis.

• Mechanical Design
• Machine Construction
• Battery Electric Vehicles
• +14 more

Aurelio Soma is a Full Professor in the Department of Mechanical and Aerospace Engineering (DIMEAS) at the Polytechnic University of Turin, where he has served as a faculty member since at least the early 2000s. His academic career spans over two decades, with continuous involvement in teaching Mechanical Engineering doctoral programs since the 19th cycle (2003/2004). He teaches courses including Machine Construction and Product and Process Design with Numerical Methods. Professor Soma's research spans several critical areas of mechanical engineering with a strong focus on sustainable technologies. His primary research interests include Battery Electric Vehicles, Hybrid Electric Vehicles, Internet of Things (IoT) applications, MEMS technology, Railway Vehicles, and Working Vehicles. His work aligns with Sustainable Development Goals 9 (Industry, Innovation, and Infrastructure), 11 (Sustainable cities and communities), and 13 (Climate action), demonstrating his commitment to environmentally conscious engineering solutions. His research bridges theoretical mechanical design with practical industrial applications, particularly in energy harvesting and sustainable vehicle technologies. The analysis of his recent publications reveals a strong trend toward sustainable transportation systems, with particular emphasis on lithium-ion battery technology, energy harvesting for railway diagnostics, and electrification of agricultural machinery. His work consistently combines mechanical engineering principles with cutting-edge sustainable technologies, focusing on practical implementations that address real-world challenges in transportation and industrial systems. The interdisciplinary nature of his research spans mechanical engineering, materials science, electrical engineering, and environmental science. Professor Soma actively supervises PhD students, currently guiding nine doctoral candidates across multiple cycles of the Mechanical Engineering program. His research is supported by numerous competitive funding sources including PNRR Mission 4 (AGRITECH Spoke 6), national research projects, regional innovation centers, and commercial contracts. He has served as Scientific Manager for over 20 research projects spanning from 2006 to 2027, demonstrating sustained research productivity and leadership. His research group focuses on the Design and Experimentation of Industrial and Railway Systems and Microsystems (DIMEAS), developing innovative solutions for energy harvesting, vehicle diagnostics, and sustainable machinery. Professor Soma's work has resulted in numerous patents related to hybrid working vehicles, railway diagnostics systems, energy harvesters, and lithium battery applications, translating academic research into practical industrial solutions.

• Nonlinear Dynamics
• Structural Dynamics
• System Identification
• +3 more

Dario Anastasio is a Fixed-term Assistant Professor in the Department of Mechanical and Aerospace Engineering (DIMEAS) at Politecnico di Torino. He is affiliated with the College of Mechanical, Aerospace, and Automotive Engineering and actively contributes to both teaching and research activities in mechanical engineering. Dr. Anastasio's research focuses on several key areas within mechanical engineering and dynamics. His primary interests include: Nonlinear dynamics and structural dynamics System identification and modal analysis Energy harvesting, particularly vibration energy harvesting Dynamics of mechanical systems with nonlinear characteristics Pantograph-catenary dynamic interaction in railway systems His work spans both theoretical modeling and experimental validation, with particular emphasis on negative stiffness oscillators, railway contact line dynamics, and nonlinear system identification techniques. Dr. Anastasio applies advanced methodologies including subspace identification, Bayesian model selection, and signal processing to solve complex mechanical engineering problems related to vibration analysis and structural dynamics. Analysis of Dr. Anastasio's publications reveals a strong focus on nonlinear dynamics, particularly in mechanical systems with complex behaviors. His research consistently bridges theoretical modeling with experimental validation across multiple domains including railway systems, energy harvesting devices, and nonlinear oscillators. The publications demonstrate progression from fundamental nonlinear dynamics research toward practical applications in railway engineering and vibration-based energy harvesting systems. Dr. Anastasio has received notable recognition for his work: Quality Award 2019 conferred by Politecnico di Torino, Italy (2020) Dr. Anastasio actively contributes to the academic community through extensive teaching activities across multiple programs. He serves as a Teaching Assistant for "Dynamics and Identification of Nonlinear Systems" and as a Course Collaborator for "Dynamics of Mechanical Systems" and "Vibration Mechanics" at both Master's and Bachelor's levels. His teaching spans from 2019/20 through the upcoming 2025/26 academic year, demonstrating his ongoing commitment to mechanical engineering education. Additionally, he contributes to PhD-level instruction in "Rotordynamics of High-Speed Rotating Machinery." Dr. Anastasio is a key member of the "Dynamics of mechanical systems and identification" research group within DIMEAS. His research integrates multiple ERC sectors including Mechanical and manufacturing engineering, ODE and dynamical systems, Signal processing, and Simulation engineering and modelling. His work aligns with Sustainable Development Goals 7 (Affordable and clean energy) and 9 (Industry, Innovation, and Infrastructure).

• Carbon Materials
• Biochar
• Activated Carbon
• +7 more

Mauro Giorcelli is an Associate Professor at Politecnico di Torino, Italy, affiliated with the Department of Applied Science and Technology (DISAT). He holds a PhD in Physics (2009) and previously earned a degree in Electronic Engineering (2004). Dr. Giorcelli is a carbon materials specialist with over 10 years of experience, focusing on low-cost carbon materials derived from recycled biomasses, particularly biochar. His research interests span carbon materials, biochar, activated carbon, biopolymers, and Raman spectroscopy. Dr. Giorcelli's work falls under the scientific branch of Experimental Physics of Matter and Applications (PHYS-03/A) with ERC sectors in environmental chemistry, spectroscopic techniques, and surface science. His research aligns with multiple UN Sustainable Development Goals including clean water, industry innovation, sustainable cities, responsible consumption, and climate action. Dr. Giorcelli's publication record shows a consistent focus on biochar applications, particularly in water purification, composite materials, and electromagnetic properties. His most recent work (2023-2025) demonstrates increasing sophistication in biochar applications, moving from fundamental characterization to real-world implementation in water treatment and advanced composite development. The research shows strong interdisciplinary connections between materials science, environmental engineering, and sustainable technology development. His research is conducted through the Institute of Fundamental Physics and Materials for Nanotechnology at DISAT, utilizing specialized laboratories including the Carbon Materials Characterization Laboratory, Carbon Materials Synthesis Laboratory, and Nanomaterials for composites and photocatalysis Laboratory. Dr. Giorcelli actively teaches Physics I and II across multiple engineering programs at Politecnico di Torino, including Aerospace Engineering, Mechanical Engineering, and Computer Engineering. He teaches in both Italian and English, demonstrating international engagement. His current research projects include ICELESS (2023-2025) as Scientific Responsible, focusing on innovative biochar applications.

• X-ray tomography
• Computed tomography
• Ghost imaging
• +6 more

Dr. Andrew Kingston is a Postdoctoral Fellow in the Department of Materials Physics at the Australian National University, where he contributes to the X-ray tomography and applications research group. His work focuses on advancing imaging technologies with applications across materials science, geology, and potentially medical fields. Dr. Kingston's research spans X-ray tomography, computed tomography, ghost imaging, and digital image processing. He has developed novel techniques for high-fidelity X-ray micro-tomography and image reconstruction algorithms that address challenges in image quality, radiation dose reduction, and complex material analysis. His work bridges theoretical developments with practical applications in materials characterization and geological analysis. Analysis of Dr. Kingston's publication trend shows consistent innovation in X-ray imaging technologies, particularly in ghost imaging techniques and micro-tomography. His work demonstrates increasing sophistication in handling beam hardening effects, motion correction, and spectral information extraction, reflecting the evolving complexity of modern imaging challenges. Dr. Kingston actively collaborates with researchers across multiple institutions, contributing to the advancement of X-ray imaging methodologies. His work with the X-ray tomography and applications group at ANU has produced significant contributions to the field, particularly in developing methods that improve image quality while addressing practical constraints like radiation exposure and computational efficiency.

Martien HulsenView profile

Associate Professor

• Computational Rheology
• Viscoelastic Flow Modeling
• Polymer Processing
• +5 more

Martien Hulsen is an Associate Professor at the Department of Mechanical Engineering , Eindhoven University of Technology (TU/e) . His research focuses on Computational Rheology , with applications in Polymer Processing , Microfluidics , and Additive Manufacturing (3D Printing) . Academic background: PhD in Mechanical Engineering (Delft University of Technology, 1988) Specializes in Numerical Methods for viscoelastic flow simulation Key applications: External Gear Pumps , Cell Sorting , and Micro-rheology Recent research trends: Interface Rheology , Particle Dynamics , and Thermal-Viscous Coupling His work has been published in top journals like Journal of Non-Newtonian Fluid Mechanics and Physics of Fluids . Martien serves on the editorial board of the Journal of Non-Newtonian Fluid Mechanics. Contact: m.a.hulsen@tue.nl

• Heat Transfer
• Refrigeration Technology
• Energy Efficiency in Buildings
• +3 more

Artur Rusowicz is a Professor at the Faculty of Power and Aeronautical Engineering , Warsaw University of Technology , specializing in the Department of Refrigeration and Building Energy . His research focuses on heat and mass transfer in refrigeration systems, free cooling technologies, plasma coatings, and entropy generation minimization in thermal systems. Key Roles: Prodziekan ds. ogólnych (since 2016), former advisor for the Student Scientific Association of Refrigeration Engineers (until 2017), Editor-in-Chief of Chłodnictwo magazine, and expert for the International Institute of Refrigeration (IIR) in Paris. Projects: Led national and international research on refrigeration, heat recovery, and plasma waste destruction, including grants from KBN, MNiSW, and Warsaw Technology Incubator. Scientific Contributions: Authored 15+ publications in leading journals like Energy , Thermal Science , and Przemysł Chemiczny , addressing thermal optimization, refrigeration cycles, and sustainable energy systems. 2020: Optimized microjet cooling systems for data centers using CFD. 2019: Refrigerant selection for Organic Rankine Cycles with environmental impact analysis. 2017: Thermoacoustic refrigeration performance evaluation. Awards: Recipient of the Rector's Award (II Class) for scientific achievements (2017, 2012) , Golden SIMP Medal (2014) , and Bronze Medal for Long Service (2012) . Also recognized for mentorship in student thesis competitions. Editorial & Organizational Roles: Served as Editor-in-Chief of Chłodnictwo , head of Warsaw SIMP Refrigeration and Air Conditioning Section, and expert in numerous scientific committees.

• Electrical Machines and Energy Conversion
• Control Theory and Applications
• Artificial Intelligence
• +3 more

Hilmi AYGÜN is an Assistant Professor in the Department of Mechatronics Engineering at Karabük University's Faculty of Engineering and Natural Sciences, where he has been serving since 2019. His academic career began as a Research Assistant in the Electrical and Electronics Engineering Department from 2009-2019 before transitioning to his current position in Mechatronics Engineering. He also serves as the Erasmus Coordinator for both the Mechatronics Engineering Department and the university since 2021. Education: PhD in Electrical and Electronics Engineering (2011-2019), Karabük University, Institute of Science MSc in Electrical and Electronics Engineering (2010-2011), Karabük University, Institute of Science BSc in Electrical and Electronics Engineering (2003-2007), Kırıkkale University, Faculty of Engineering Hilmi AYGÜN's research primarily focuses on electrical machines and energy conversion systems, with particular emphasis on motor control algorithms for electric vehicle applications. His work integrates control theory with artificial intelligence techniques, especially optimization algorithms like Particle Swarm Optimization (PSO) and the Yusufcuk Algorithm. He has made significant contributions to field-oriented control of induction motors, DC motor control systems, and wind energy applications. His publication record shows a clear trajectory toward increasingly sophisticated control systems for electromechanical applications, with recent work focusing on metaheuristic methods for motor control, optimization of wind energy systems, and advanced DC motor control techniques. His research bridges theoretical control concepts with practical engineering applications, particularly in transportation and renewable energy sectors. Hilmi AYGÜN has successfully advised at least one Master's student, Hersh Hasan Taha Al Dawoodı, whose thesis focused on field-oriented control of induction motors using metaheuristic methods. He has participated in two major research projects: one on optimal flux reference direct torque control for asynchronous motors used in electric vehicles (2015-2019), and another on controlling bed temperature in fluidized bed boilers using PSO-PID controllers (2011-2013). As an educator, he has taught numerous courses including Electric Machine Dynamics, Modeling and Control of Biomedical Systems, Control of Electric Machines, Electric and Hybrid Vehicles, Industrial Automation, and various electronics courses. His teaching spans both undergraduate and graduate levels, demonstrating his versatility across multiple engineering disciplines within the mechatronics field.

Maurizio BevilacquaView profile

Professor

• Industrial Engineering
• Digital Twin Technology
• Industry 4.0
• +4 more

Maurizio Bevilacqua serves as a Full Professor in the Department of Industrial Engineering and Mathematical Sciences at the University of Ancona (Università Politecnica delle Marche). His academic focus falls under the scientific sector IIND-05/A - Impianti industriali meccanici (Mechanical Industrial Plants). Based at the university's Engineering faculty located at Via Brecce Bianche in Ancona, Italy, Professor Bevilacqua maintains an active research profile with numerous publications spanning industrial engineering, digital transformation, and smart manufacturing technologies. Professor Bevilacqua's research interests center on cutting-edge industrial engineering topics including Digital Twin technology, Industry 4.0 implementation, smart retrofitting of industrial machinery, maintenance engineering, and robotics applications in manufacturing. His work demonstrates particular expertise in applying these technologies to challenging sectors such as oil and gas, food manufacturing, and maritime transportation. His research bridges theoretical innovation with practical industrial applications, as evidenced by his numerous case studies across different manufacturing sectors. An analysis of his recent publications (2023-2025) reveals a strong emphasis on digital transformation in industrial settings, with particular focus on Digital Twin implementations across various sectors. His work shows a progression from foundational Industry 4.0 concepts toward more sophisticated applications including Digital Triplet frameworks and human-machine integration approaches that anticipate Industry 5.0 paradigms. Many of his studies combine multiple advanced techniques such as machine learning, fuzzy cognitive maps, and association rule mining to solve complex industrial problems. Professor Bevilacqua's research demonstrates strong industry collaboration, with numerous case studies conducted in real industrial settings across multiple sectors including oil and gas, food manufacturing, and maritime transportation. While specific grant information isn't provided in the available materials, his extensive publication record suggests active participation in research projects that bridge academic theory with practical industrial implementation. His work frequently addresses challenges related to legacy system modernization, operational resilience, and sustainable manufacturing practices. Though specific laboratory affiliations aren't detailed in the available information, Professor Bevilacqua's research appears to focus on industrial applications of digital technologies, suggesting collaboration with industrial partners and possibly university research centers focused on manufacturing innovation, robotics, and industrial IoT. His work on smart retrofitting solutions indicates involvement with projects that transform conventional machinery into intelligent systems capable of integration within modern digital manufacturing ecosystems.

PAOLO CASTELLINIView profile

Associate Professor

• Mechanical Measurements
• Vibration Analysis
• Hyperspectral Imaging
• +4 more

Paolo Castellini is an Associate Professor at the Department of Industrial Engineering and Mathematical Sciences, Università Politecnica delle Marche (UNIVPM). His research focuses on mechanical measurements, vibration analysis, and advanced imaging techniques. He teaches courses in the College of Engineering and has published extensively on applications of hyperspectral imaging, 3D scanning, and neural networks in industrial and biomedical contexts. Office hours: Monday-Friday, 08:30-13:00 Email: p.castellini@univpm.it Location: via Brecce Bianche, 12, Ancona Recent research trends include vibration decoupling metastructures, microplastic detection in biological samples, and UAV-based photogrammetric analysis of olive trees. His publications emphasize non-destructive testing, acoustic beamforming, and uncertainty evaluation in measurement systems. Notable projects involve mmWave radar displacement analysis, cardiac simulators for prosthetic valves, and light-controlled polymer films for mechanical motion.