Kevin GODINEAU is a Lecturer at ENS Paris-Saclay (Université Paris-Saclay) since 2020, specializing in mechanical engineering and additive manufacturing. He coordinates the ORACLE project focused on trajectory interpolation optimization in LPBF processes and contributes to the RA(SI) educational project involving augmented reality for engineering sciences. Education: Doctorate in Mechanics (2019), Master 2 in Digital Product Process Engineering (2016) Research Focus: Laser powder bed fusion (LPBF), opto-mechanical calibration, digital twin development, and augmented reality applications in production system calibration His recent publications analyze spatter formation in Inconel 718 manufacturing, laser trajectory control, and calibration techniques for LPBF machines. He supervises Master's internships and teaches modules on poly-articulated systems, production machine control, and proof-of-concept methodologies. Scientific contributions include: Industrial Engineering Science Aggregation Competition Winner (2015) Key developments in CNC-laser interaction modeling for additive manufacturing
Vojislav Vujičić serves as an Assistant Professor at the Department of Mechanical Engineering , Faculty of Technical Sciences , University of Kragujevac . His work bridges Mechatronic Systems and Industrial Automation , with a focus on Robotics and Simulation tools like MATLAB/Simulink. He teaches courses such as PLC programming and CAD/CAE design. Research Interests include mechatronic process modeling, industrial robot programming, and renewable energy systems. His recent publications (2024) highlight advancements in ABB IRB 120 robot simulation , CNC feed systems , and project-based learning in engineering education. Earlier works (2022–2015) cover photovoltaic-thermal systems, hydraulic modeling, and educational laboratory setups. Publication Trends show a strong emphasis on robotics , simulation , and education technology , often integrating MATLAB and ABB RobotStudio . Collaborations with researchers like Ivan Milićević and Nedeljko Dučić are frequent, spanning topics from 3D printing optimization to control systems .
Dr Robert Ward is an Industrial Research Fellow at the University of Sheffield's School of Electrical and Electronic Engineering, with a joint appointment at the Advanced Manufacturing Research Centre (AMRC). His work bridges academic research and industrial applications in autonomous manufacturing systems. MEng(Hons) in Avionics and Aerospace Systems, University of Manchester Engineering Doctorate (EngD) in Machining Science and Control Engineering, University of Sheffield Research interests focus on Digital Machining and Machine Tool Control , particularly in CNC trajectory generation, robotic machining, and digital twin technologies. His recent publications emphasize real-time control algorithms, neural network applications for machining optimization, and synchronization of manufacturing systems. As module leader for Rapid Control Prototyping , he teaches advanced control techniques to undergraduate students. He actively supervises both undergraduate and postgraduate students, emphasizing industrial collaboration and professional preparation. Professional memberships include: Chartered Engineer (CEng) Member of Institute of Engineering and Technology (MIET) Member of Institute of Electrical and Electronic Engineers (MIEEE) At AMRC, Ward leads the Control of Subtractive Manufacturing Operations theme within the Digital Machining Research Team, collaborating on both high-TRL industrial projects and low-TRL research funded by HVMC and EPSRC.
Sven Ekered is a Senior Research Engineer at the Department of Production Systems , Chalmers University of Technology. He serves as an instructor and head of the production laboratory at IMS Lindholmen, teaching CAD/CAM, automation technology, and CNC-technology . Research Focus: Automation engineering, robotics, digital twins, IoT, and sustainable manufacturing. Projects: ShiftBeds (2023–2026), DIH World (2020–2023), MOTION (2015–2016). Collaborations: VINNOVA, European Commission, and industry partners. Publication Trends: His work over 17 years explores robotic automation, interoperability in assembly, digital twins for IoT/VR, and MQL drilling. Recent studies emphasize real-time connectivity and AI-driven vision systems.
Hajo Wiemer is a Researcher at the Department of Process Informatics and Machine Data Analysis within the Faculty of Mechanical Science and Engineering at Dresden University of Technology . His work bridges data-driven methodologies with mechanical engineering, focusing on machine learning, thermal error compensation, and digital twins. Research Focus: Usable AI, additive manufacturing, and data mining in production systems. Key Contributions: Development of the DMME framework, ontology-based data management, and thermal simulation-driven models. Dr. Wiemer’s recent publications emphasize machine learning robustness , domain-specific AI applicability , and data-driven quality assurance in cyber-physical systems. He actively collaborates on projects like AMTwin and SaxFDM, addressing challenges in interdisciplinary engineering data integration.
Professor Sangkee Min is a Mechanical Engineering faculty member at the University of Wisconsin–Madison. He holds a PhD from UC Berkeley and has extensive experience in academia and industry across the US, Japan, Germany, and Korea. His research focuses on ultra-precision machining, manufacturing energy efficiency, and sustainable manufacturing strategies. He has led projects on advanced manufacturing technologies, including development of ultra-precision 5-axis machines and smart manufacturing systems. Education: PhD 2001 (UC Berkeley), MS 1993 (Yonsei University), BS 1991 (Yonsei University) Research interests include Manufacturing for Design (MFD) , digital manufacturing , and hybrid manufacturing . He emphasizes the economic importance of maintaining advanced manufacturing ecosystems. His work has been recognized with awards such as the NSF CAREER Award and multiple best paper/poster awards. Recent publications explore topics like crack morphology in sapphire machining, energy-efficient CNC systems, and AI-driven assembly monitoring. He teaches courses on manufacturing processes, precision engineering, and independent research. Labs/Teams: Advanced Manufacturing Center at Lawrence Berkeley National Laboratory, UW-Madison Mechanical Engineering research groups
Prof. Alberto Boschetto is a Full Professor in the Department of Industrial and Information Engineering at Sapienza University of Rome. He specializes in advanced manufacturing technologies, with a focus on additive manufacturing processes and their applications in aerospace, materials science, and surface engineering. His research integrates computational modeling, material characterization, and digital image processing to optimize manufacturing workflows and improve material performance. Key research areas include 4D printing, laser powder bed fusion (LPBF), fused filament fabrication (FFF), and the development of corrosion-resistant coatings for aerospace components. He has contributed to projects on lightweight satellite structures and CubeSat fabrication, demonstrating expertise in both academic and industrial applications. His work also addresses surface finishing techniques like barrel finishing and CNC machining to enhance part quality. Prof. Boschetto has authored over 70 peer-reviewed articles, with recent publications emphasizing Industry 4.0 integration in manufacturing, defect detection via digital image analysis, and material property optimization. His research bridges theoretical advancements with practical implementations, particularly in aerospace and biomedical applications. No scientific awards or grants are explicitly listed in the provided texts. His advising record remains unspecified, though his extensive publication history suggests active mentorship of graduate students in materials engineering and manufacturing systems.
Professor Kuang-Hua Chang is a David Ross Boyd Professor and Williams Companies Foundation Presidential Professor at the University of Oklahoma's Department of Aerospace & Mechanical Engineering. He specializes in computational mechanics, material design, and bioengineering applications. His research focuses on multi-scale modeling, structural fatigue/fracture analysis, and innovative design projects like green tricycle development and 3D-printed bioengineering solutions. Education: PhD (1990), MS (1987), and BS (1980) in Mechanical Engineering from The University of Iowa and Taipei Institute of Technology. Research interests include CAD/CAM integration, reverse engineering, assistive device design, and concurrent engineering. He has pioneered methods like bridging scale decomposition for multiscale simulations and developed design tools using software such as Creo, SOLIDWORKS, and CAMWorks. Award highlights: David Ross Boyd Professorship (2013), multiple OU Alumni Teaching Awards, and the Don Davis Award for disability advocacy. He serves on editorial boards for journals like Computer-Aided Design and Applications . Teaching spans courses on CAD/CAE, mechanism design, and structural optimization. His work integrates education and innovation, emphasizing experiential learning and entrepreneurship through projects like the Green Tricycle initiative.
Tony R. Kuphaldt is a Professor in the Electronics Engineering Technology department at Lewis-Clark State College's Schweitzer Career and Technical Education Center in Lewiston, Idaho. With over 25 years of full-time teaching experience in the Washington and Idaho college systems, he specializes in electronics education and curriculum development. His office is located in STC 222, and he teaches in room 237 of the Schweitzer Career and Technical Education Center with regular office hours throughout the week. Kuphaldt is renowned as the author of the 'Modular Electronics Learning Project' (ModEL), an open-source collection of tutorials and problem sets designed for inverted instruction of electronics at the two-year college level. He is also the founding author of 'Lessons In Electric Circuits,' an early open-source textbook on electronics. His educational philosophy emphasizes first-principles understanding, Socratic dialogue, and problem-based learning approaches. The ModEL project, copyrighted 2016-2025, represents over two decades of professional instruction experience in industrial electricity and electronics. His work integrates computer-based simulation tools including SPICE and programming languages like C, C++, and Python to enhance circuit exploration. The ModEL curriculum is structured across four semesters with theory, experiment, and project components, totaling less than 60 semester credits. Kuphaldt has developed comprehensive practice exams that mirror industry standards for electronics technician assessment. A lifelong learner himself, Kuphaldt studied Instrumentation and Industrial Electronics at J.M. Perry Technical Institute (1987-1989) and earned his Electronics Engineering Technology degree from Skagit Valley Community College in 2004. Before teaching, he gained extensive industry experience including 2 years with CNC machine tools, 2.5 years as an instrument/electrical technician at ARCO Cherry Point oil refinery, and 6.5 years as a meter/instrument technician at Intalco aluminum smelter. An amateur radio operator with call sign AJ7FJ, Kuphaldt has created numerous educational resources covering mathematics fundamentals, electrical principles, semiconductor devices, amplification, communication systems, and programmable systems. His materials are licensed under Creative Commons Attribution 4.0 International, making them freely available for educational use while maintaining attribution requirements.
Prof. Omid Fatahi Valilai is a Professor of Industrial Engineering at the School of Business, Social & Decision Sciences, Constructor University Bremen. He holds a PhD in Industrial Engineering from Sharif University of Technology (2010-2012), along with master’s and bachelor’s degrees in the same field from Sharif University (2003-2009). His research focuses on cloud manufacturing, blockchain integration in supply chains, sustainable manufacturing systems, and digital transformation in industrial processes. Key research interests include optimizing manufacturing systems through cloud-based platforms, leveraging blockchain for supply chain transparency, and applying AI to enhance operational efficiency. His work spans areas such as smart energy systems, additive manufacturing, and circular economy frameworks for industries like textiles and automotive. Prof. Valilai’s recent publications emphasize sustainable logistics, resilient service networks in manufacturing, and AI-driven solutions for product lifecycle management. He has contributed to EU projects such as YouthTeamUp and serves on editorial boards, including the International Journal of Rapid Manufacturing. His academic roles include former positions at Sharif University as Associate Professor and Department Vice President of Graduate Studies. He leads research groups exploring cloud manufacturing ecosystems, blockchain-enabled supply chains, and the integration of social media analytics for market insights. His lab focuses on practical applications of Industry 4.0 technologies, including digital dentistry and smart manufacturing systems.
John C. Cesarone is an Associate Teaching Professor in Mechanical Engineering at the Armour College of Engineering, Illinois Institute of Technology. He holds a Ph.D., M.S., and B.S. in Mechanical Engineering from Northwestern University and the University of Illinois-Urbana-Champaign. His research focuses on Intelligent Manufacturing, Computer-Integrated Manufacturing, Simulation, and Operations Research, with expertise in Automation, Robotics, and Lean Manufacturing. Education: Ph.D., Mechanical Engineering, Northwestern University M.S., Mechanical Engineering, University of Illinois-Urbana-Champaign B.S., Mechanical Engineering, University of Illinois-Urbana-Champaign Research emphasizes advanced manufacturing technologies, including optimization via Operations Research and automation systems. His consulting practice since 1998 supports industrial, government, and academic clients in supply chain analysis, statistical process control, and precision gear manufacturing. He has held roles such as Technical Director at IIT Research Institute and Program Manager for the $4M/year Gears program. Awards include the 2022 Dean’s Award for Excellence in Advising. Notable grants include procuring $350K for a Computer Integrated Manufacturing lab (1992) and $1.7M for CNC machine tools (1994). He teaches Industrial Engineering courses and leads initiatives in Intelligent Manufacturing and defense logistics analysis.
Burak Sencer is an Associate Professor of Mechanical Engineering at Oregon State University’s College of Engineering, affiliated with the Mechanical, Industrial, and Manufacturing Engineering department. He directs the Manufacturing Process Control Laboratory and holds the Tom and Carmen West Faculty Scholar title. His expertise lies in advanced manufacturing, precision motion control, and optimal trajectory generation for multi-axis machine tools. B.S., Mechanical Engineering, Istanbul Technical University (2003) M.S., Ph.D., Mechanical Engineering, University of British Columbia (2005, 2009) Postdoctoral Research, Nagoya University, Japan (2009–2012) Assistant Professor, Nagoya University (2012–2015) before joining Oregon State Research focuses on improving manufacturing efficiency through precision control of CNC machines, industrial robots, and machining processes. Key areas include: Vibration suppression in high-speed machining Optimal trajectory generation for multi-axis systems Intelligent process control for challenging materials (e.g., titanium, hardened steel) Robotics for deburring and edge finishing Notable achievements include developing motion control algorithms that boost production speeds by 20–25% for IT products and a chip-pulling device reducing friction in cutting operations. Awards include the JSPE Best Paper Award (2020) and ASME’s Blackall Machine Tool and Gage Award (2019) . Collaborates with industries like Boeing and Japanese machine tool builders for applied projects. Active in teaching graduate students and mentoring through research.
Dr. Derek Covill is a Senior Lecturer at the University of Brighton, affiliated with the School of Architecture, Technology and Engineering and the Advanced Engineering department. He holds roles as Principal Lecturer and serves as an External Examiner for multiple universities, including Robert Gordon University and Sheffield Hallam University. His academic journey includes a BEng in Medical Engineering from Queensland University of Technology and a PhD in Engineering from the University of Brighton. Dr. Covill’s research spans sports engineering, additive manufacturing for medical devices, digital fabrication tools, and engineering education. Notable projects include the Steel Bicycle Project exploring frame design and the development of electrochemical sensors for biomedical applications. He has collaborated with industries like Clarks International and OSET Bikes through Knowledge Transfer Partnerships (KTPs). His recent publications focus on dyslexic student support in design education, bicycle dynamics optimization, and learning analytics tools. Dr. Covill has advanced degrees in Data Analytics (MSc, 2026), an MBA (2023), and a Postgraduate Certificate in Teaching and Learning in Higher Education (2007). His external roles include examiner positions across product design and engineering programs.
Dr. Nuo Xu is an Associate Professor at the Collat School of Business, University of Alabama at Birmingham (UAB), within the Department of Management, Information Systems and Quantitative Methods. He holds a PhD (2007) and MS (2003) in Industrial Engineering from the University of Cincinnati, and a BS in Material Engineering from Shanghai Jiao-Tong University (1997). His research interests span Business Analytics, Applied Mathematics, Statistics, and Manufacturing Engineering. Notable contributions include methodologies in gene expression analysis, feature selection bias reduction, and robust voting machine allocation models. Professional activities include editorial roles for journals like International Journal of Data Science and service on institutional committees such as the IS Search Committee. His academic career at UAB began in 2010, initially in the School of Engineering before transitioning to his current role in the Collat School. He advises students in business honors programs and actively participates in institutional service roles.
Dr. Arivazhagan Anbalagan is an Assistant Professor in Digital Manufacturing at Coventry University's Institute for Advanced Manufacturing and Engineering (AME), leading research in Industry 4.0, IoT integration, and advanced manufacturing systems. He holds a PhD from IIT Roorkee and has over 15 years of experience in CAD/CAM automation, CNC machining, and materials science. Education: Doctorate in CAD/CAPP Systems (IIT Roorkee, 2008) MEng in CAD/CAM (Vellore Institute of Technology, 2003) BEng in Mechanical Engineering (University of Madras, 2001) Research Interests: Focuses on digital twins, STEP-NC machining, machine learning for feature recognition, and sustainable manufacturing. Key areas include: IoT-based Manufacturing Integration High-Entropy Alloys Development 3D Printing & Additive Manufacturing Finite Element Analysis (FEA) for Tool Design Recent Contributions: Published on digital twin implementation, hydrogen embrittlement mitigation, and CFRP machining. Active in collaborative projects like the EU FP7 Toolbox Website and Mindsphere data integration. Awards & Memberships: Chartered Engineer (IMechE) Fellow of the Higher Education Academy (HEA) PhD External Examiner at Staffordshire University Lab & Teams: Leads AME's manufacturing systems research group, specializing in CAD/CAM automation and IoT-driven manufacturing workflows.
