Find Academic Supervisors

Miladin StefanovićView profile

Professor

• Production Engineering
• Industrial Engineering
• Industry 4.0/5.0
• +7 more

Miladin Stefanović is a Professor at the Department of Production Engineering, Faculty of Engineering, University of Kragujevac. His academic role includes research and teaching in production engineering, industrial systems, and advanced manufacturing technologies. He leads initiatives in Industry 4.0/5.0 integration, quality management systems, and smart manufacturing solutions. His research focuses on applying digital technologies like machine learning, computer vision, and IoT for optimizing industrial processes. Notable projects include robotic systems for food processing, OPC UA integration in automation, and cloud-based quality management frameworks. He emphasizes the transition from Quality 4.0 to 5.0, emphasizing human-centric manufacturing advancements. Stefanović has contributed to over 50 peer-reviewed publications since 2014, with recent work addressing real-time defect detection, smart quality control applications, and organizational resilience post-pandemic. His work bridges theoretical advancements with practical implementations in SMEs and public sector organizations. He has been actively involved in educational reforms, developing didactic tools for Industry 4.0 training and prototyping microprocessor-based learning systems. His lab focuses on edge computing solutions for manufacturing efficiency and sustainable resource allocation strategies.

• Production Engineering
• Tribology
• Materials Science
• +5 more

Vladimir Kočović is an Associate Professor of Production Engineering at the Faculty of Engineering, University of Kragujevac. His research focuses on advanced manufacturing processes, tribology, materials science, and optimization of machining techniques. He holds a position in the Department of Production Engineering and has contributed to numerous interdisciplinary studies. His work spans experimental and computational methods, including tool wear analysis, material testing, and automation in manufacturing. He has developed specialized devices for measuring kinetic friction coefficients and optimizing cutting processes. Notable projects include studies on micro-cutting processes, 3D model reconstruction, and the application of AI in defect classification. Despite his prolific research output, no scientific awards are explicitly mentioned. He collaborates on projects involving tribological investigations, reverse engineering, and additive manufacturing. His academic activities include teaching and advising on mechanical engineering and industrial processes, though student names are not listed in available texts.

• Production System Design
• Flexible Manufacturing Systems
• Computer-Aided Design (CAD)
• +5 more

Magdalena BARBU is a Lecturer at the Department of Engineering and Industrial Management, Faculty of Technological Engineering and Industrial Management, Transilvania University of Brașov. Her research focuses on production system design, flexible manufacturing systems, and computer-aided design. She has contributed to advancements in automation, tool management, and 3D printing process optimization. Her work bridges theoretical frameworks with practical applications in manufacturing processes and industrial systems. Key research interests include: Automation of assembly processes and robotics integration 3D printing techniques and process management Tool flow dynamics and manufacturing system perturbations Green manufacturing and eco-friendly lubrication systems Kanban-based inventory and production control methodologies Publications emphasize industrial automation, sustainable manufacturing, and mathematical modeling for technical-economic forecasting. Her work spans journals like RECENT and METALURGIA INTERNATIONAL , with a notable book on manufacturing equipment systems (2020). No scientific awards or grants are explicitly listed in the provided materials. Her advisory role is currently unspecified, though her research themes suggest involvement in industrial collaborations.

• Computational Mathematics
• Numerical Analysis
• Computational Fluid Dynamics
• +4 more

Dr. Arash Ghasemi serves as an Adjunct Faculty member in the Department of Engineering Management and Technology within the College of Engineering and Computer Science at the University of Tennessee at Chattanooga (UTC). His academic role bridges computational mathematics and engineering applications through teaching and research activities focused on advanced numerical methods. His research spans computational mathematics, numerical analysis, and scientific computing with emphasis on high-order spectral/finite element methods, mesh generation, and preconditioning techniques. Key application areas include computational fluid dynamics (particularly compressible flow), structural engineering (crane mechanisms, non-destructive testing), climate modeling for infrastructure, and electromagnetic simulations. His methodological innovations consistently target improved accuracy, efficiency, and stability in engineering computations across civil, mechanical, and aerospace domains. Dr. Ghasemi's publication trajectory from 2006 to 2024 reveals sustained contributions to computational methods. Early work established foundations in wireless sensor networks for infrastructure and high-order ODE solvers, while his 2016 'spectral hull' breakthroughs revolutionized degree-of-freedom reduction in conservation laws. Recent publications (2021-2024) demonstrate expanding applications in polynomial approximation, data interpolation, and climate modeling, maintaining his signature focus on mathematical rigor coupled with practical engineering impact across fluid dynamics, structural mechanics, and environmental systems.

• Manufacturing Engineering
• Materials Science
• Finite Element Analysis (FEM)
• +5 more

Barbara REGGIANI is an Associate Professor at the University of Modena and Reggio Emilia, affiliated with the Department of Engineering Sciences and Methods. Her research focuses on advanced manufacturing processes, particularly extrusion of aluminum alloys, FEM simulation of material behavior, and optimization of industrial processes. She teaches courses in Management Engineering, including Manufacturing Processes and Methods for Product Development and Industrial Technologies and Plants . Her research interests include die design optimization, nitrogen cooling strategies for extrusion dies, and polymer processing. She has extensively studied grain structure evolution, recrystallization modeling, and defect prediction (e.g., PCG formation, charge welds) using FEM tools like Qform and Moldflow. Recent work addresses material characterization (e.g., AA6082/6063 alloys) and surface functionalization for biomedical applications. Dr. REGGIANI collaborates on projects involving additive manufacturing for die cooling channels and laser-based surface treatments. Her work bridges experimental methods (hot torsion tests, micro-CT analysis) with numerical modeling to enhance process efficiency and material performance.

Onat Halis TOTUKView profile

Assistant Professor

• Additive Manufacturing
• Soft Robotics
• Mechanical Engineering Design
• +4 more

Dr. Onat Halis TOTUK is an Assistant Professor at Çankaya University's Faculty of Engineering, Department of Mechatronics Engineering. He holds a PhD from İskenderun Technical University (2019-2023) and earlier degrees from Middle East Technical University (BSc 1982-1987, MSc 1987-1989). His academic career includes roles as a Lecturer and Assistant Professor, with part-time status from 2012-2018 before transitioning to full-time positions. Research Interests : Focus on Additive Manufacturing, Soft Robotics, and Computer-Aided Design. Key areas include 3D printed materials for robotics, SCAMPER methodology in design education, and sustainable engineering solutions aligned with UN SDGs. Recent work explores biomimetic manufacturing and adaptive robotic systems. Recent Trends in Publications : Recent articles emphasize soft robotics actuators, 3D printing applications in biomedical engineering, and innovative design methodologies. Earlier work includes studies on solar collector optimization and machining processes. Grants & Projects : Lead or contributed to projects like 'EBOT Pharmacy Robot Automation' (2021-2022) and 'Waste-to-Active Carbon Conversion' (2023-2024). Active in developing pharmacy automation systems and smart storage solutions. Advising : Supervised 5 master's students focusing on topics like robotic systems for additive manufacturing, tool wear analysis, and AI-driven ERP systems. Courses taught include Additive Manufacturing, Computer-Aided Design, and Mechatronics fundamentals.

Norbert PalzView profile

Professor

• Digital Design
• Additive Manufacturing
• Computer Art
• +3 more

Prof. Dr. Norbert Palz is Professor for Digital and Experimental Design at Berlin University of Arts, where he served as President (2020-2025). His research explores digital fabrication processes, large-format additive manufacturing, and computational design methods. Education includes architecture studies at TU Berlin following a draftsman apprenticeship. Professional experience includes work with UN Studio, NOX Architects, and founding TARGADESIGN (art/architecture practice). Research contributions include EU Horizon 2020 projects on textile architectures and investigations into historical construction geometries for digital pedagogy. Current investigations focus on material behavior in large-scale 3D printing applications and computer art's architectural implications.

Mihai ANDRIESView profile

Associate Professor

• Cognitive Robotics
• Ambient Systems
• Automated Functional Design
• +3 more

Mihai ANDRIES is an Associate Professor in Computer Science (specializing in Artificial Intelligence and Robotics) at IMT Atlantique, Brest, France. He holds a PhD in Artificial Intelligence from the University of Lorraine (2015), an M.Sc. in Software and Data Engineering from the University of Strasbourg (2012), and a B.Sc. in Computer Science from the same institution (2010). His research focuses on cognitive robotics, ambient systems, and automated functional design, emphasizing human-centric technologies such as assistive robots and healthcare applications. He has held postdoctoral positions at Inria Nancy, Institute for Systems and Robotics (Lisbon), and Institute of Intelligent Systems and Robotics (Paris), with industry experience at PSA Peugeot Citroën and Dassault Systèmes. His work integrates artificial intelligence, robotics, and sensor systems to enhance quality-of-life solutions, including robotic rehabilitation assessment and dementia detection through speech analysis. Key projects include the DiscoBot (mental health chatbot), Veggie Breizh Bot (cooking assistance robot), and SUMMA-Sound (sound-based activity recognition). He has secured grants totaling over €1M for projects like HEAP sorting, RoboErgoSum (robotic consciousness), and Mementop (sound-based mental health diagnosis). His software contributions include tools for 3D model conversion (stl2sdf, binvox2sdf) and multi-robot simulators.

Chundeva-Blajer MarijaView profile

Associate Professor

• Metrology
• Electromagnetic Measurements
• Finite Element Method (FEM)
• +5 more

Marija Chundeva-Blajer is an Associate Professor at the Faculty of Electrical Engineering and Computing (FEIT), Ss. Cyril and Methodius University in Skopje, Macedonia. She holds a PhD in Technical Sciences (2004), MSc in Electrical Engineering (2000), and a BEng in Electrical Engineering (1996), all from the same university. Her research focuses on metrology, electromagnetic measurements, finite element method (FEM) applications, and instrument transformer design. She has led and participated in numerous international projects, including the EU TEMPUS IV project for doctoral studies in metrology (2010-2012) and bilateral projects with Croatian institutions. Her work emphasizes developing measurement methods, calibration techniques, and optimizing electrical devices using FEM-3D and genetic algorithms. Dr. Chundeva-Blajer has authored over 40 peer-reviewed articles and conference papers, contributing to journals like International Journal of Applied Electromagnetics and Prezeglad Elektrotechniczny . Her research spans electromagnetic transient analysis, material testing, and instrumentation design. She has received awards for innovations in clean production processes and metrological infrastructure. She serves as a reviewer for major journals and conferences, including Measurement Science and Technology and Journal of Physics D . Her leadership roles include heading FEIT's Metrology Laboratory (2004-2008) and acting as a lead assessor for the Macedonian Accreditation Institute (IARM). She has also trained educators in modeling and simulation tools for vocational schools.

• User Experience Design
• Human-Computer Interaction
• Human-Robot Interaction
• +3 more

Beatrice Alenljung is an Associate Professor of Information Technology at the University of Skövde, Sweden, leading the Interaction Lab. She specializes in human-centered technology research with a focus on user experience (UX) design, human-robot interaction, and decision support systems. Her work bridges theoretical insights with practical applications in fields like healthcare robotics, industrial automation, and educational technology. She teaches in the User Experience Design program and actively contributes to interdisciplinary projects addressing challenges in aging populations, industrial collaboration, and sustainable digital transformation. Key ongoing projects include exploring socially assistive robots for older adults (RoSA and RO-LIV), optimizing human-robot collaboration in manufacturing (KOMPARO and AIHURO), and risk reduction strategies for emergency services through digital simulation. Her research emphasizes empirical studies on UX evaluation frameworks (e.g., ANEMONE), human factors in robotics, and the societal impacts of emerging technologies. Alenljung has authored over 40 peer-reviewed publications, spanning conference papers and book chapters in HCI, robotics, and requirements engineering. She holds a PhD in Decision Support Systems from the University of Skövde and has maintained collaborative ties with industries and institutions across Europe.

• Neuroimaging
• Pediatric Critical Care
• Biomedical Engineering
• +3 more

Mathieu Dehaes is a Professor at the Université de Montréal's Faculté de médecine , specializing in the Département de radiologie, radio-oncologie et médecine nucléaire . His research focuses on developing optical and MRI-based neuroimaging techniques to assess cerebral health in pediatric populations, particularly in preterm infants and children with congenital heart defects. He leads multiple NIH/FRQS-funded projects, including the development of NIRS-EEG methods for neonatal brain monitoring and Raman spectroscopy for disease diagnostics. Education: Ph.D. in Biomedical Engineering (École Polytechnique de Montréal, 2009) M.Sc. in Applied Mathematics (Université de Montréal, 2004) B.Sc. in Mathematics/Computer Science (Université du Québec à Chicoutimi, 2002) Awards: FRQS Senior Researcher Award (2024-2027) Multiple NIH grants for pediatric neuroimaging innovations Goldenson Foundation Fellowship (Harvard Medical School, 2011-2013) Key Projects: Developing bedside neuroimaging tools for neonatal hypoxic-ischemic encephalopathy Optical coherence tomography advancements for murine retinal studies Real-time saliva-based Raman spectroscopy for infectious disease detection Advising & Grants: Supervised 12+ graduate students in biomedical engineering and neuroimaging Total external funding >$5M CAD over 20 active grants Labs & Affiliations: Principal Investigator at CHU Sainte-Justine Research Center Member of the Azrieli Brain Imaging Center

Aymeric HistaceView profile

Professor

• Computer Vision
• Machine Learning
• Computer Aided Diagnosis
• +4 more

Aymeric Histace is a Full Professor at the École Nationale Supérieure d'Électronique et de ses Applications (ENSEA) within CY Cergy Paris University. He leads the CELL research group at the ETIS laboratory, specializing in AI-driven medical diagnostics and embedded systems. His work focuses on computer vision, machine learning, and their applications in healthcare, particularly in capsule endoscopy and disease-carrying insect surveillance. Key roles: Teacher-researcher, CAD-CAP Scientific Council member Research areas: Medical AI, embedded systems, computer-aided diagnosis, and health technologies Notable contributions: Developed algorithms for automated analysis of gastrointestinal imaging and AI systems for vector surveillance His research bridges clinical needs and technological innovation, with over 50 publications since 2018. Recent work includes benchmarking polyp detection systems, improving bowel preparation assessments, and creating datasets for insect species classification using wing interferential patterns (WIPs). Publications: Over 40 peer-reviewed articles in journals like Medical Image Analysis and IEEE Transactions Tools developed: GTCreator annotation tool, AAEGAN image synthesis framework Grants & collaborations: Active in EU-funded projects on medical AI and embedded systems Labs/Teams: ETIS laboratory (Computer Science/Signal Processing), CELL research group (AI in Healthcare)

Martin-Pierre SchmidtView profile

Lecturer

• Topological Optimization
• Multi-physics Optimization
• Approximation Theory
• +3 more

Martin-Pierre Schmidt is a Lecturer at the National Institute of Applied Sciences (INSA) Rouen, affiliated with the Department of Mathematical Engineering. His research focuses on topological/multi-physics optimization, approximation theory, and applications in computer-aided geometric design (CAGD). He completed his PhD in March 2020 under the supervision of Christian Gout, with co-supervisors David Bonner and Auxkin Ortuzar from Dassault Systèmes, funded by Dassault Systèmes. His work integrates machine learning and data science into imaging and design processes. He teaches in the GM5 program at INSA Rouen, emphasizing machine learning and data approximation techniques. His research team is part of the Numerical Analysis, Imaging and Approximation group. Notable contributions include interactive topology optimization tools, biomimetic microstructure design, and robust 3D shape detection algorithms. His thesis defense in 2020 involved a jury of international experts in mechanical engineering and computational design. Key collaborations include Dassault Systèmes, with applications in CAD model optimization and manufacturing process design. His work bridges theoretical optimization methods with practical industrial applications in additive manufacturing and structural engineering.

David CazierView profile

Professor

• Virtual Reality
• Computer Graphics
• Computational Geometry
• +4 more

David Cazier is a **Professor at the University of Strasbourg** and a **Researcher at the ICube Laboratory**, specializing in geometric and graphical computing. He also teaches computer science at the **IUT of Haguenau**. His research focuses on three main axes: multiresolution geometric models, real-time interaction in virtual reality, and tools for adapting such models to simulations and visualization. His work bridges theoretical advancements in geometric modeling with practical applications in medical imaging, crowd simulation, and augmented reality. **Research Interests**: Cazier’s expertise includes virtual reality (VR) immersion, real-time interaction techniques, and the development of efficient geometric models for complex simulations. His projects often involve hierarchical meshes, topological changes during deformations, and applications in surgical AR. Key areas include multiresolution representations, collision detection in dynamic environments, and non-manifold geometry processing. **Publications**: His recent work emphasizes medical applications (e.g., surgical AR with topological changes) and foundational contributions to geometric data structures (e.g., CGoGN, CPH). He explores user interaction challenges in the digital divide era and develops tools for crowd simulation using deformable agents. **Collaborations and Projects**: Active in collaborations with the ICube Lab’s IGG team, Cazier contributes to platforms like CGoGN and InVirtuo. His research spans national and European projects, including IHU, ANR, and CNRS initiatives. He supervises internships on geometric models for VR applications and interdisciplinary projects combining geometry with medical and industrial challenges.

Bruce WolffenbuttelView profile

Professor

• Diabetes Mellitus
• Endocrinology
• Metabolic Disorders
• +3 more

Bruce Wolffenbuttel is a Professor at the University of Groningen, affiliated with the University Medical Center Groningen. His research focuses on diabetes mellitus, metabolic disorders, and endocrinology, contributing to UN Sustainable Development Goals related to health. He has authored over 525 publications, including recent studies on vitamin B12 deficiency, coronary artery disease risk stratification, and lifestyle interventions for weight loss. His work integrates genetic, environmental, and clinical data, such as the Lifelines Cohort Study. He received the Lacqueur Lecture (2021) and Dr. F. Gerritzen Prize (1991) for diabetes research. Education: Not explicitly stated in the text. Affiliations: University of Groningen, CluB12 UK (Member, 2020–2025). Research interests emphasize diabetes pathophysiology, endocrine disruptors, and translational medicine. Recent articles highlight diagnostic innovations for metabolic diseases and public health implications of nutrient deficiencies. He has supervised 25 PhD students, including Sandra Slagter and Walter Kuchenbecker. Collaborations span global institutions, with datasets like the Lifelines Biobank. Media contributions address vitamin B12 deficiency risks linked to vegan diets and mental health.