Find Academic Supervisors

• Quality Management
• Production Technologies
• Machine Learning
• +3 more

Aleksandar Jovicic is an Assistant Professor at the Department of Mechatronics, Faculty of Technical Sciences in Čačak, University of Kragujevac. With a PhD in Mechanical Engineering (2016) and dual Master's degrees in Quality Management and Mechanical Engineering, he specializes in production technologies and quality systems within manufacturing processes. Education : PhD in Mechanical Engineering (2016), University of Kragujevac MA in Quality Management (2009), University of Belgrade MA in Mechanical Engineering (2018), University of Kragujevac BA in Technics & Informatics (2008), University of Kragujevac His research interests focus on quality management systems, production technologies, and machine learning applications in manufacturing. He explores how AI and digital tools can optimize casting processes and implement circular economy principles in foundries. Recent publications demonstrate his work in abrasive water jet machining analysis, CAD/CAE integration in casting, and AI-driven metal melting control. His research spans 2012-2025 with significant contributions to wear prediction modeling and sustainable manufacturing. Scientific awards include multiple grants from Serbian development agencies and participation in EIT RawMaterials' DustREC-II project. He serves as project manager for EU-funded initiatives in automation and zero-waste processing. As a certified Lead Auditor for ISO 9001, 14001, and 45001 standards, he bridges academic research with industrial quality systems implementation.

Jeff GladstoneView profile

Associate Professor

• Mechanical Engineering
• Structural Analysis
• Computer-Aided Design (CAD)
• +5 more

Jeff Gladstone is an Associate Professor of Engineering at Dordt University. He teaches courses in mechanical engineering structures, CAD, and computer-aided engineering (FEA), including Statics, Dynamics, Materials Science, Machine Design, and Structural Mechanics. Education : BS in Aeronautical Engineering (California Polytechnic State University, San Luis Obispo, 1985), MS in Engineering/Structural Mechanics (University of California, Davis, 1989), PhD in Engineering/Structural Mechanics (University of California, Davis, 1995). Jeff’s research and professional interests include mechanical engineering , structural analysis , CAD/CAE , aerospace engineering , and engineering consulting . He has contributed to international engineering education development through a partnership with Northrise University in Zambia. Jeff is a licensed Professional Engineer in California, with extensive experience in structural engineering analysis and consulting.

• Machine Tools
• Flexible Technological Systems
• Automatization of Design Processes
• +5 more

Cvijetin Mlađenović is an Assistant Professor at the Faculty of Technical Sciences, University of Novi Sad , specializing in machine tools, technological systems, and CAD/CAE/CAM integration. His research focuses on machining process optimization, thermal behavior modeling of machine components, and vibration analysis for manufacturing stability. Department: Chair of Computer Aided Technological Systems and Design His work leverages neural networks and machine learning to address challenges in machining parameter optimization and predictive maintenance. Recent publications (2022-2025) highlight applications in Ti-6Al-4V alloy machining, spindle thermal modeling, and small dataset-driven optimization. Key trends in his research include integrating artificial intelligence with traditional manufacturing methods, improving geometric accuracy via laser systems, and advancing hybrid mechanism design for machine tools. Notable projects include stability lobe diagram modeling and development of workpiece manipulation devices (patent 2012).

• Machine Learning
• Surrogate Modeling
• Data Augmentation
• +5 more

Tobias Lehrer is a Doctoral Candidate at the Chair of Computational Solid Mechanics at the Technical University of Munich since 2023. His research focuses on integrating machine learning with computational mechanics for manufacturing optimization. 2023 - Present: Doctoral Candidate, Chair of Computational Solid Mechanics, TU Munich 2020 - 2023: Doctoral Candidate, Laboratory of Finite-Element-Method, OTH Regensburg 2018 - 2020: M.Sc. in Mechanical Engineering, OTH Regensburg His research interests span machine learning, surrogate modeling, data augmentation, synthetic data, generative AI, sheet metal forming, and sensitivity analysis. His publications emphasize deep drawing processes , parametric CAD modeling , and surrogate-based optimization for manufacturability assessment. Key projects include AMEDEO and eEgO, aiming to enhance early-stage prediction of sheet metal part feasibility through simulation-driven machine learning frameworks. In teaching, Tobias has led courses on structural optimization , computational mechanics for car body design , and structural mechanics modeling . His work bridges computational methods with industrial applications, particularly in automotive manufacturing.

Marko PopovićView profile

Associate Professor

• Structural Engineering
• Machine Elements Design
• CAD/CAE Design
• +6 more

Dr. Marko Popović serves as an Associate Professor at the Department of Mechanical Engineering, Faculty of Technical Sciences in Čačak, University of Kragujevac, Serbia. His academic position focuses on Structural Engineering, where he teaches Machine Elements, Fundamentals of Design, CAD/CAE Design, and Modeling and Numerical Analysis of Mechatronic Structures. Dr. Popović earned his Bachelor's degree in Mechanical Engineering from the Faculty of Mechanical Engineering, University of Belgrade (2003), followed by his Master of Technical Sciences (2007) and Doctor of Technical Sciences (2012), both from the Faculty of Technical Sciences, University of Kragujevac. His research spans structural optimization, machine elements design, and computational methods in mechanical engineering. A significant portion of his work addresses excavator component design, particularly cutting teeth for bucket chain excavators. More recently, his research has incorporated artificial intelligence applications for machine elements design, optimization of 3D printing processes, and advanced diagnostics for mechanical systems. His work demonstrates a progression from traditional mechanical design toward computational and AI-enhanced approaches. Analysis of Dr. Popović's publication history reveals consistent contributions to mining equipment design, manufacturing processes, and machinery valuation. His recent work shows increasing integration of machine learning techniques to solve traditional mechanical engineering challenges, with applications in predictive maintenance, material optimization, and precision manufacturing. RICS certificate for machinery valuation (No. 6855771) License as responsible designer (No. 333 D73506) License as responsible contractor (No. 434 D41309) Accredited member of National Association of Appraisers of Serbia (NUPS-a M703) Permanent member of TEGoVA's international committee for machinery standards With 22 years of professional experience, Dr. Popović has served as lead designer for 19 major projects in production machinery and technology. He actively participates in machinery valuation across Serbia and the EU, working with financial institutions, audit firms, and insurance companies. His expertise extends to serving as an authorized court expert in mechanical engineering and as a lecturer for the Serbian Chamber of Engineers. Dr. Popović contributes to international standardization through TEGoVA, helping develop European standards for machinery valuation (EVSB-PME). His work bridges academic research with practical industry applications, particularly in the mining sector where his excavator component designs have improved operational efficiency and equipment longevity.

• Mechanical Engineering
• Computer-Aided Engineering (CAE)
• Simulation
• +4 more

Prof. Dr.-Ing. Joachim Villwock is a faculty member at the Berlin University of Applied Sciences (BHT) within Department VIII , which focuses on Mechanical Engineering, Event Technology, and Process Engineering. He leads the CAE and Simulation - CAVE laboratory, contributing to interdisciplinary research networks like HARMONIK (humanoid robotics) and Data Science +X . His research interests span computer-aided engineering , simulation technologies , and human-technology interaction , with involvement in applied projects such as MINT-VR Labs , Vitalab , and GINSODA . These initiatives emphasize practical applications in mechanical systems, virtual reality, and data-driven solutions. The CAVE laboratory , under his leadership, collaborates on projects addressing urban technologies and sustainable solutions, aligning with BHT’s focus on application-oriented research. While no specific scientific awards are listed, his work integrates into broader university research priorities like AI, communication technologies, and life sciences.

Bert BrasView profile

Professor

• Sustainable Design
• Sustainable Manufacturing
• Additive Manufacturing
• +9 more

Dr. Bert Bras is a Brook Byers Professor of Sustainability and Professor of Mechanical Engineering at the George W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology. He has served as Associate Chair for Administration (since 2016) and Interim School Chair (2018). His 25-year career spans sustainable design, manufacturing, and energy systems research with industry applications in automotive, aerospace, and alternative energy sectors. Ph.D. in Operations Research, University of Houston (1992) M.S. in Mechanical Engineering, University of Twente, Netherlands (1987) Research Focus: Sustainable Systems and Manufacturing, with emphasis on: Design for Recycling/Remanufacturing Life-Cycle Analysis Computer-Aided Engineering (CAE) Biomimetic Design Electric Vehicles and Energy Systems His work has been funded by National Science Foundation , Ford Motor Company , General Motors , and Boeing , including the CES-featured MyEnergi Lifestyle and C-Max Solar Energi concept car projects. Georgia Tech Outstanding Interdisciplinary Activity Award (2007) Woodruff Faculty Fellow (2002-2007) SAE Ralph R. Teetor Educational Award (1999) NSF Early Career Development Award (1996-2000) Georgia Society of Professional Engineers Metro-Atlanta Engineer of the Year in Education (1996) Dr. Bras leads the Sustainable Design and Manufacturing Lab (SDM), which focuses on energy-efficient manufacturing systems and mobility solutions through interdisciplinary collaboration with industry partners.

Darren WattsView profile

Senior Lecturer

• Additive Manufacturing
• CAD/CAE Software Development
• Design Optimization
• +7 more

Dr Darren Watts is a Senior Lecturer and Senior Teaching Fellow in CAD & CAE at the Wolfson School of Mechanical and Manufacturing Engineering, Loughborough University. He serves as Director of Professional Training and IMechE Academic Liaison Officer. His expertise spans Additive Manufacturing, CAD/CAE software development, and design optimization. Education: BEng (Hons) Mechanical Engineering and MSc(Eng) Product Design & Management from the University of Liverpool, followed by a PhD in Topology Optimization for Rapid Manufacturing at Loughborough University. Research interests include Bespoke CAE software, Genetic Algorithms, Virtual Assembly Methods, and Medical Applications of Additive Manufacturing. He has led projects such as the EPSRC-funded 'Topologically Optimised Street Furniture for Concrete Printing' and 'Exploitation of Sinus Surgery Simulation Phantoms'. Awards include the Loughborough University Enterprise Award for Cultural Impact (2013) and a Royal Academy of Engineering Industrial Secondement Award (2013-2014). He is a Chartered Engineer and Fellow of the Higher Education Academy. Key roles: Co-Investigator on multiple EPSRC grants, Principal Investigator for surgical simulation projects, and industrial collaboration through Majenta PLM Ltd secondment. Labs/Teams: Core academic member of the Additive Manufacturing Research Group (AMRG), contributing to customized assembly and medical device prototyping advancements.

Ran JinView profile

Professor

• Manufacturing Systems Engineering
• System Informatics and Control
• Data Science and Visualization
• +6 more

Ran Jin is a Professor in the Department of Industrial and Systems Engineering at Virginia Tech, leading the Data Science and Visualization Lab. He holds academic appointments in the College of Engineering. His research focuses on integrating data science with manufacturing systems engineering, emphasizing system informatics, quality control, and process optimization. He has contributed to advancements in profile modeling, defect detection, and statistical process monitoring in industries like additive manufacturing. Education : Ph.D., Georgia Institute of Technology, 2011 M.A. and M.S., University of Michigan, 2009 and 2007 B.Eng., Tsinghua University, 2005 Research Interests : Jin's work bridges statistical methodologies with engineering systems, particularly in high-definition profile data analysis, ensemble modeling for manufacturing scale-up, and cybermanufacturing challenges. He develops algorithms for process variation reduction and real-time monitoring. His recent focus includes AI-driven solutions for manufacturing resilience and distributed data systems. Recognition : Jin has received awards such as the Best Applied Paper Award (IIE Transactions) and NSF grants for projects like 'EAGER: AM: CoFedAI' and 'QQ Models' for mixed quality responses. His contributions span academic journals and industry partnerships, including collaborations with JSME Co. Ltd. and the Commonwealth Center for Advanced Manufacturing. Grants & Projects : Key initiatives include 'Distributed Data Filtering for Fog Manufacturing' and 'AI Incubation in Manufacturing.' He has served as PI or Co-PI on NSF-funded projects addressing experimental design, anomaly detection, and thermal spray process modeling. Labs & Teams : Directs the Data Science and Visualization Lab, fostering innovation in AI applications for smart manufacturing and system informatics. Engages in interdisciplinary research through roles like Co-Chair of the Commission on Research at Virginia Tech.

Lih-Sheng TurngView profile

Professor

• Injection Molding
• Bio-based Polymers
• Tissue Engineering
• +7 more

Professor Lih-Sheng (Tom) Turng holds the Consolidated Papers Foundation Endowed Professorship at the University of Wisconsin–Madison's Mechanical Engineering Department within the College of Engineering. His expertise spans advanced manufacturing, polymer processing, and biomedical applications. He has pioneered research in injection molding, microcellular foaming, bio-based polymers, and tissue engineering. Education: B.S. (1981, National Taiwan University), M.S. (1987), and Ph.D. (1990, Cornell University). Prior to academia, he worked in industry developing simulation software for 10 years. Research Interests: Injection molding innovations, bio-based materials, nanocomposites, medical device design, and CAE simulation. He leads the Polymer Engineering Center and Wisconsin Institute for Discovery (WID) groups, advancing sustainable manufacturing and biomedical solutions. Awards: Over 20 awards including the 2023 WID Faculty of the Year, WARF Innovation Award (2018), and numerous SPE honors. Recognized as a Fellow of ASME, SME, and SPE. His work bridges academia and industry, with 320+ journal papers, 24 patents, and an h-index of 79. He advises over 100 students and researchers, emphasizing sustainable materials and smart manufacturing.

• Materials Science
• Engineering Mechanics
• Design Fundamentals
• +1 more

Professor Hogg is a Lecturer at Mannheim University of Applied Sciences. He teaches core engineering courses including Materials Science (WK), Engineering Mechanics (TM), Design Fundamentals (KG), and Computer-Aided Engineering (CAE). His professional focus aligns with applied engineering disciplines. Research interests are implied by his teaching portfolio, emphasizing practical engineering solutions in materials, mechanics, design methodologies, and digital engineering tools. No specific research grants or publications are listed in the provided text. Office located in Building L, Room 157. Contact via m.hogg@hs-mannheim.de or +49 621 292 65 15.

Denis DorozhkinView profile

Lecturer

• Computer-Aided Engineering
• Design Optimization
• Mechanical Engineering
• +3 more

Denis Dorozhkin is a Lecturer at the Georgia Institute of Technology. He is affiliated with the School/College associated with the 'me' email domain (likely the College of Engineering), though specific department details are not explicitly stated. His primary research area focuses on Computer-Aided Engineering (CAE) and Design, emphasizing simulation-driven design methodologies and advanced engineering systems. While no educational background or formal grants are detailed in the provided text, his role as a Lecturer suggests involvement in teaching and applied research within mechanical or aerospace engineering disciplines. No advising activities or scientific awards are noted here.

Jonathan RoweView profile

Academic

• Product Design
• Sustainable Product Development
• Generative Design
• +4 more

Jonathan Rowe is the Associate Head (Curriculum and Partnerships) in the School of Electrical and Mechanical Engineering at the University of Portsmouth. He holds the academic rank of Senior Teaching Fellow, specializing in Design Engineering, Product Design, and Advanced Manufacturing. His current research focuses on sustainable product development through generative design and topology optimization methods, pursued via a PhD investigation. He oversees curriculum development, partnerships, and is the Disability Coordinator and Admissions Tutor for Product Design and Mechanical Postgraduate courses. Teaching responsibilities include Product/Industrial Design, CAD/CAM Modelling, Technical Drawing, and Product Design methodologies. He coordinates modules like 'Research Methods for Product Designers' and 'Preparation for Product Launch.' Professional memberships include the Institution of Engineering Designers (IED), Institution of Engineering and Technology (IET), and FHEA. Previous roles include Course Leader for the Product Design and Innovation BSc program.

Fiammetta CaccavaleView profile

Researcher

• Chemical Engineering
• Engineering Education
• Artificial Intelligence
• +3 more

Fiammetta Caccavale is a Researcher at the Department of Chemical and Biochemical Engineering at Technical University of Denmark (DTU), affiliated with the PROSYS - Process and Systems Engineering Centre. Her work focuses on integrating artificial intelligence and digital technologies into chemical engineering education, with contributions to sustainable development goals related to quality education and industry innovation. Education: She completed her PhD in Chemical Engineering at DTU (2021-2025), supervised by Prof. Ulrich Krühne and Dr. Carlos Gargalo. Her doctoral research centered on digitalization strategies in chemical engineering education, including AI chatbots and Python programming integration. Research Interests: Her work spans AI-driven educational tools (e.g., chatbots, virtual tutors), machine learning applications in bioprocess monitoring, and curriculum modernization. She emphasizes ethical considerations in AI implementation and Industry 4.0 readiness. Publications: Her recent work explores AI chatbots for automating educational tasks (ChatGMP), machine learning for cell cycle analysis, and Python course frameworks for engineers. These contributions highlight her dual focus on pedagogical innovation and technological application in engineering. Lab/Team: As part of PROSYS, she collaborates on process systems engineering projects, contributing to educational technology development and bioprocess modeling initiatives.

Jens EkengrenView profile

Senior Lecturer

• Mechanical Engineering
• Materials Engineering
• Additive Manufacturing
• +3 more

Jens Ekengren is a Senior Lecturer in Mechanical Engineering at Örebro University since 2013, affiliated with the School of Science and Technology and Department of Natural Sciences and Technology. His research focuses on materials engineering, additive manufacturing, and statistical evaluation of defects in steels. He teaches courses in mechanics, materials engineering, and computational methods like FEA/CFD. Education includes a Doctoral Dissertation (2011) on extreme value analysis of steel defects and a Licentiate Thesis (2008) on inclusion content in steels. Key research projects include ATOAM (Additive Manufacturing tooling) and NASCA (agricultural systems). Research interests span statistical defect evaluation (rooted in his PhD work), electrical agricultural vehicles, and additive manufacturing applications in tooling and structural design. Recent publications emphasize 3D printing process optimization, tool cooling design via AM, and material property analysis using computed tomography. No scientific awards explicitly stated. Advising and grants details not provided in text. Active in the Mechanics and Materials research group. Current projects involve data-driven engineering design and agricultural automation.