جست‌وجوی استاد و پژوهشگر

• Lean Product Development
• Systems Engineering
• Platform Development
• +۳ مورد دیگر

Dag Henrik Bergsjö serves as an Assistant Professor in Product Development at Chalmers University of Technology. His academic work focuses on integrating lean methodologies with systems engineering approaches to optimize product development processes. Dr. Bergsjö's research spans several interconnected domains of engineering management and systems design. His primary interests include Lean Product Development, Systems Engineering, and Platform Development (covering technology, product, and production platforms). He is actively working to develop the research area of Platform-based Product Development and explores the combination of Lean Product Development with Product Data Management (PDM/PLM). His work particularly emphasizes Lean Product Development tools such as Pulse, visual planning, and checklists. His recent publications (2019-2025) demonstrate a consistent focus on human-centric manufacturing systems, knowledge management in engineering contexts, and the application of lean principles to complex product development challenges. The research trends show increasing attention to socio-technical aspects of digitalization in industrial engineering processes and the development of frameworks for designing human-centric manufacturing systems for novel products. Dr. Bergsjö has secured significant research funding through multiple projects, primarily supported by VINNOVA and other Swedish research agencies. His projects span various domains including digital product development centers, AI analysis in construction projects, knowledge sharing in digital collaborative projects, and sustainable manufacturing methods. He leads and participates in several research initiatives including the Wingquist Laboratory: Digital Center for Product Development (2024-2024), Smart Module for AI Analysis during the Design Phase in Safety-Critical Complex Construction Projects (2024-2025), and previously led projects such as KIDSAM: Knowledge and Information Sharing in Digital Collaborative Projects (2018-2021), TechMo: Technology Modeling of Sustainable Manufacturing Methods in the Electronics Industry (2017-2018), and several others focused on platform-based development, digitalization, and lean methodologies.

• Wind Energy
• Aerospace Engineering
• Turbulence
• +۳ مورد دیگر

Dominic A. von Terzi is a Professor in the Faculty of Aerospace Engineering at Delft University of Technology, specializing in Wind Energy through the TU Delft Wind Energy Institute (DUWIND). His work bridges fundamental fluid dynamics research with practical wind turbine engineering applications, focusing on enhancing operational reliability and performance in challenging environments. His research centers on Wind Energy and Aerospace Engineering, with deep expertise in Turbulence modeling, Large Eddy Simulation, and Wind Turbine Aerodynamics. He investigates critical phenomena including rain erosion on blade leading edges, transonic flow effects at turbine tips, and innovative concepts like floating offshore wind systems and airborne wind energy. His approach combines advanced computational modeling with real-world validation to address industry challenges in turbine durability and energy yield optimization. Recent publications reveal strong trends toward solving operational challenges in extreme conditions (erosion, transonic flow) and system-level innovations (wind-storage integration, airborne energy). These works emphasize computational rigor while exploring frontier concepts like hydrogen production from offshore wind and floating turbine platforms, reflecting a strategic shift toward holistic energy system design beyond standalone turbine optimization. Professor von Terzi chairs the European Research Community on Flow Turbulence and Combustion (ERCOFTAC) and leads research within the EU-funded MERIDIONAL project on multiscale wind farm modeling. He has supervised two students and maintains active industry engagement through media discussions on floating wind technology and grid integration. Embedded within DUWIND's collaborative ecosystem, his work leverages partnerships with institutions like ERCOFTAC and industry stakeholders to advance wind energy technology. Current efforts focus on erosion-safe operational modes, transonic flow management, and scaling airborne wind energy systems, positioning him at the forefront of next-generation wind energy solutions.

• Control and optimization
• Epidemic processes over networks
• Network inference
• +۵ مورد دیگر

Carolyn L Beck is a Professor in the Department of Industrial and Enterprise Systems Engineering at the University of Illinois at Urbana-Champaign . She holds affiliations with multiple departments, including Electrical and Computer Engineering (since 2014) and Mechanical Science and Engineering (since 1999). Beck is also a Research Professor at the Coordinated Science Laboratory (since 2019) and has served as Associate Head for Undergraduate Programs since 2020. Education : Ph.D. in Electrical Engineering from California Institute of Technology M.S. in Electrical & Computer Engineering from Carnegie Mellon University B.S. in Electrical & Computer Engineering with a Physics minor from California State Polytechnic University Research Interests focus on control and optimization , epidemic processes over networks , network inference , and dynamic network data clustering . Her work spans mathematical systems theory to real-world applications in bioengineering and smart grid optimization . Article Trends show a progression from system identification and network inference to complex epidemic modeling over time-varying networks and grid optimization. Recent works emphasize finite-sample analysis , distributed subgradient methods , and multi-layer contagion dynamics , reflecting her expertise in control theory and network science . Scientific Awards : IEEE Fellow (2023) Arthur Davis Faculty Scholar Award (2016) ONR Young Investigator Award (2001-2004) NSF CAREER Award (1998-2003) ORAU Junior Faculty Award (1997) Alcoa Foundation Award (1997) Advising and Grants include mentoring former PhD students like Puneet Sharma (AIMBE Fellow) and Philip Pare' (Purdue ECE) . Her research has been funded by the NSF , ONR , and IEEE , with a $500,000 grant for wind turbine efficiency. Labs and Teams : Beck is affiliated with the Coordinated Science Laboratory and collaborates with interdisciplinary teams in bioengineering , network control , and grid optimization . She also contributes to IEEE as a Guest Editor and Associate Editor .

• Renewable Energy
• Thermal Engineering
• Supercritical CO2 Power Cycles
• +۶ مورد دیگر

David Tomás Sánchez Martínez is a Professor in the Department of Energy Engineering at the University of Seville, specializing in advanced energy systems with a focus on supercritical CO2 cycles, concentrated solar power (CSP), and hybrid renewable energy technologies. His work spans thermodynamic modeling, techno-economic analysis, and system optimization. University Professor at University of Seville Researcher in Thermal Machines and Engines group Coordinator of International ORC Power Systems seminars Research Interests include: Supercritical CO2 power cycles for solar and hydrogen applications Micro gas turbine hybridization with ORC and fuel cells Thermal energy storage and desalination integration Computational fluid dynamics for turbomachinery Techno-economic assessment of renewable systems Recent Publications demonstrate expertise in CO2-based power cycles, hybrid fuel cell-turbine systems, and off-grid energy solutions. Key trends include hydrogen integration, solar thermal optimization, and advanced compressor design. Advising includes PhD theses on solar micro gas turbines, energy storage roadmaps, and CO2 cycle commercialization. He collaborates on major EU projects like StreamSTEP, ASTERIx-CAESar, and REMIND.

Bernhard Saskeمشاهده پروفایل

پژوهشگر

• Virtual Reality
• Augmented Reality
• Product Lifecycle Management
• +۳ مورد دیگر

Bernhard Saske serves as a Research Associate at the Chair of Virtual Product Development within Dresden University of Technology, where he has been affiliated since completing his mechanical engineering studies in 2002. Holding a doctorate (Dr.-Ing.) earned in 2008 for research on 'Augmented Reality in Maintenance,' he specializes in virtual and augmented reality applications integrated with product lifecycle management systems. His academic credentials include: Master's degree in Mechanical Engineering from Dresden University of Technology (2002) Doctorate (Dr.-Ing.) from Dresden University of Technology (2008) focusing on Augmented Reality in Maintenance Saske's research centers on digital transformation in engineering workflows, with core expertise in virtual/augmented reality implementation, product lifecycle management (PLM), and model-based systems engineering (MBSE). Recent investigations address generative AI applications in CAD processes, sustainable product development frameworks, and component reuse optimization in industrial plant design. His work consistently bridges theoretical methodologies with practical industry implementation challenges. Analysis of his 2023-2025 publications reveals a strategic shift toward artificial intelligence integration in engineering design, particularly generative models for CAD and computer vision systems. Concurrently, his research maintains strong emphasis on sustainability-driven PLM strategies and MBSE adaptation for circular economy principles, reflecting evolving industry priorities in resource efficiency and digitalization. Scientific Awards: No documented awards, fellowships, or major honors were identified in the source materials. Dr. Saske actively contributes to collaborative research projects within the Chair of Virtual Product Development, frequently co-authoring with Prof. Paetzold-Byhain and interdisciplinary teams. While specific student supervision is unrecorded, his publications indicate mentorship roles in conference papers and journal articles. Project funding appears aligned with German academic-industry partnerships focused on digital engineering solutions, though grant details remain unspecified. As a core member of the Chair of Virtual Product Development, Saske operates within a research ecosystem dedicated to advancing virtual prototyping, digital twin technologies, and immersive maintenance solutions. The chair maintains active industry collaborations to implement VR/AR methodologies in real-world manufacturing and product development contexts across European industrial partners.

• Aircraft Reliability Engineering
• Data-Driven Maintenance Optimization
• Reliability Engineering
• +۳ مورد دیگر

Dr. Hang Zhou serves as a Lecturer in Electrically Powered Aircraft and Operations specializing in Autonomous Systems & Connectivity at the University of Glasgow. His academic work focuses on enhancing reliability and maintenance strategies for complex engineering systems, particularly civil aircraft engines and critical infrastructure. His research encompasses: Aircraft Reliability Engineering Data-Driven Maintenance Optimization Bayesian Reliability Evaluation Risk Analysis in Complex Systems Condition Monitoring Systems Competing Risk Identification Analysis of his 2021-2023 publications reveals a consistent emphasis on integrating statistical modeling with machine learning for aerospace and power systems. Key contributions include copula-based airworthiness frameworks, reliability contour mapping for engine life prediction, and bivariate cluster analysis for maintenance prioritization. His work demonstrates cross-domain applicability from aircraft engines to power grid infrastructure through advanced probabilistic methods. Scientific Awards: No awards or fellowships documented in available sources Academic engagement shows active collaboration with researchers including Ajith Kumar Parlikad and Alexandra Brintrup, though specific advising roles or grant funding details remain unreported in current documentation.

Yuvin Adnarain Chinniahمشاهده پروفایل

استاد

• Occupational Health and Safety
• Industrial Safety
• Machine Safety
• +۵ مورد دیگر

Dr. Yuvin Adnarain Chinniah serves as a Full Professor and Department Director in the Department of Mathematical and Industrial Engineering at Polytechnique Montreal. His expertise spans occupational health and safety, industrial safety engineering, and machinery risk assessment. He actively contributes to the Research Group on Globalisation and Management of Technology (GMT) and Laboratoire Poly-Industries 4.0. Dr. Chinniah's research focuses on occupational health and safety with particular emphasis on machinery safety, risk assessment methodologies, human-robot collaboration, and safety standards implementation. His work bridges theoretical frameworks with practical applications in industrial settings, addressing critical issues like confined space safety, lockout/tagout procedures, and safety in Industry 4.0 environments. His research integrates ISO and CSA standards into practical safety solutions for industrial machinery. His recent publications demonstrate a clear trajectory from traditional machine safety toward advanced applications involving robotics, digital transformation, and human-robot collaboration. The research consistently addresses safety optimization in manufacturing processes, with increasing focus on cyber-physical systems, AI integration for hazard detection, and safety-driven production planning. His work maintains strong connections to industrial standards while pushing boundaries in collaborative robotics safety. Dr. Chinniah has successfully supervised 9 Ph.D. students and 10 Master's students, with thesis topics covering confined space safety, lockout/tagout procedures, human-robot collaboration safety, and machinery risk assessment. His teaching portfolio includes key courses in safety engineering, ergonomics, and maintenance engineering. He leads significant research projects related to occupational safety in industrial settings, with particular focus on machinery safety standards implementation and risk assessment methodologies.

Massimo Callisto De Donatoمشاهده پروفایل

استادیار

• Internet of Things
• Digital Twin
• Machine Learning
• +۶ مورد دیگر

Massimo Callisto De Donato is an Assistant Professor specializing in Internet of Things, Digital Twin, and Machine Learning applications for real-world systems. His research addresses critical challenges in environmental management, workplace safety, and disaster response through advanced computing solutions. His primary research domains include: IoT infrastructure for real-time industrial and environmental monitoring Digital Twin development for process simulation and prediction Machine Learning frameworks for safety-critical applications Human behavior analysis using community detection algorithms ICT systems for earthquake rescue operations Analysis of his 2020-2025 publications reveals a consistent trajectory toward integrating Digital Twin and IoT technologies with machine learning for predictive capabilities. Key application areas include wastewater management (decanter centrifuge modeling), smart living environments, and earthquake disaster response systems, with increasing emphasis on real-time simulation and human activity recognition. No scientific awards are documented in the available information. Details regarding student supervision, research grants, and laboratory affiliations are not provided in the source materials.

Jack Rechciglمشاهده پروفایل

استاد

• Soil Science
• Water Quality
• Agricultural Waste Management
• +۳ مورد دیگر

Jack Rechcigl is a Professor and Center Director at the University of Florida/IFAS Gulf Coast Research and Education Center in Balm and Plant City, as well as the Fort Lauderdale Research and Education Center in Davie. His work focuses on the beneficial uses of organic wastes and industrial by-products as fertilizers for agricultural crops, with a particular emphasis on pasture grasses and reducing fertilizer runoff into waterways. Dr. Rechcigl collaborates extensively on hop production in Florida , especially under subtropical conditions, developing innovative trellis systems and harvesting methods with colleagues at UF/IFAS.

• Process Systems Engineering
• Chemical Process Optimization
• Hybrid Modeling
• +۷ مورد دیگر

Vladimir Mahalec is a Professor in the Department of Chemical Engineering within the Faculty of Engineering at McMaster University. With a career spanning over four decades, his scholarly activity shows consistent publication output from 1977 through 2025, with particular intensity in recent years. He maintains an active teaching schedule, offering graduate courses including Systems Modeling and Optimization (CHEMENG 753, SEP 752), Leadership for Innovation (SEP 773), and M.Eng. Project courses. Professor Mahalec's research interests focus on the intersection of chemical engineering process optimization, hybrid modeling techniques, and sustainable energy systems. His work bridges traditional chemical engineering with modern computational approaches, particularly in refinery planning, distillation tower modeling, and carbon footprint reduction. He has developed innovative methodologies such as inventory pinch algorithms for gasoline blend planning and hybrid models combining first-principles with data-driven approaches for process monitoring and optimization. Analysis of his recent publications reveals a strong trend toward integrating machine learning with traditional process engineering. His work increasingly focuses on sustainability challenges, particularly zero-emission energy systems and greenhouse gas reduction strategies. The publications show a progression from purely process engineering topics toward interdisciplinary work combining chemical engineering, computer science, and environmental science. Professor Mahalec has maintained a productive research program with consistent publication output across multiple high-impact journals including Computers and Chemical Engineering , AIChE Journal , and Energy . His co-author network includes notable researchers such as Prashant Mhaskar (8 publications), Robert Fleisig, and Christopher Swartz. In the classroom, Professor Mahalec teaches advanced courses focused on systems modeling, optimization, and innovation leadership. His teaching portfolio demonstrates commitment to both technical depth in chemical engineering systems and broader skills development for engineering leadership. He has supervised numerous capstone design projects and M.Eng. projects, guiding students through complex process engineering challenges.

• Supply Chain Management
• Information Fusion in Manufacturing/Maintenance
• Multi-Agent Systems in Logistics
• +۳ مورد دیگر

Sandor Ujvari is a Senior Lecturer in Logistics at the University of Skövde , associated with the School of Business and the Department of Commerce and Entrepreneurship. His research focuses on Supply Chain Management , Information Fusion in Manufacturing/Maintenance , Multi-Agent Systems (MAS) in Logistics , and AGV Modeling . His scholarly work spans interdisciplinary collaborations, particularly in healthcare quality improvement, where he explores Trust dynamics in management-initiated reforms System reliability in service delivery Cross-sectoral knowledge transfer He has published extensively on simulation-based optimization, stochastic transportation models, and institutional entrepreneurship. Recent trends in his publications highlight Integration of multi-agent systems for logistics Sustainability in supply chains Adaptation of industrial methods to healthcare His teaching involves Bachelor-level logistics courses and training programs, emphasizing ERP systems and digital transformation in supply chains. He currently leads the ongoing project "Labour Market Challenges of Green Transition in West Sweden" (2023–2029), analyzing societal impacts of automotive industry transformation. His co-authors include prominent researchers like Thomas Andersson , Nomie Eriksson , and Per Hilletofth . No scientific awards are explicitly mentioned in the provided texts.

• Process Systems Engineering
• Production Planning and Scheduling
• Waste Supply Chain Management
• +۳ مورد دیگر

Professor Iiro Harjunkoski is affiliated with Aalto University, School of Chemical Engineering, Department of Chemical Engineering and Metallurgy. His research focuses on advanced optimization techniques in Process Systems Engineering. The top fields of interest for Professor Harjunkoski include: Process Systems Engineering Production Planning and Scheduling Waste Supply Chain Management Mixed Integer Linear and Non-Linear Programming Hybrid Algorithms with Data Analytics Process and Operational Optimization His recent work emphasizes: Energy systems optimization under uncertainty Bike-sharing logistics modeling Machine learning integration in chemical production scheduling Stochastic programming for energy storage operations Surrogate-based optimization techniques Hybrid algorithm development Scientific awards and recognitions: Computers and Chemical Engineering Best Paper Award (2014) Award or recognition for output from Department of Chemical Engineering and Metallurgy (Nov 2015)

• Vascular Surgery
• Surgical Education
• Aortic Surgery
• +۲ مورد دیگر

Cali E. Johnson, MD, EdD serves as an Assistant Professor (Clinical) in the Department of Surgery, Division of Vascular Surgery at the University of Utah School of Medicine, practicing at the Cardiovascular Center in Salt Lake City. Her clinical expertise spans the full spectrum of vascular disease with specialized focus on complex aortic endovascular surgery and multidisciplinary limb preservation strategies. Her educational journey includes: B.S. in Pharmacology and Biopsychology from University of California, Santa Barbara M.D. with Distinction from University of California, San Francisco School of Medicine Certificate in Biomedical Research (UCSF) General Surgery Residency at Keck School of Medicine, USC EdD in Organizational Change from USC Rossier School of Education Vascular Surgery Fellowship via Early Specialization Program (Keck/USC) Dr. Johnson's academic mission centers on integrating surgical education research with healthcare system optimization to enhance patient care quality. Her work bridges clinical vascular practice with educational innovation, particularly examining how training methodologies impact real-world surgical outcomes and system efficiency. She maintains active scholarship in vascular surgery outcomes, surgical education frameworks, and quality improvement initiatives. Analysis of her 15 most recent publications reveals consistent research trajectories in three domains: vascular surgery outcomes (particularly in elderly/frail populations), surgical education methodology, and technical innovations in endovascular procedures. Her work demonstrates increasing emphasis on patient-centered metrics, health services research, and the intersection of educational theory with clinical practice improvement. Patient feedback consistently highlights her exceptional clinical skills (4.9/5 from 63 reviews), with recurring themes of professionalism, empathetic communication, and life-saving surgical expertise. Comments describe her as a "phenomenal surgeon" who creates "everlasting impact" through meticulous care and patient advocacy.

• Precision Agriculture
• Agricultural Machinery
• Viticulture Mechanization
• +۴ مورد دیگر

Pietro Catania serves as a Full Professor in the Department of Agricultural, Food and Forestry Sciences at the University of Palermo's Polytechnic School. His office is located in Room No. 135 of the SAAF Department, where he holds regular office hours on Mondays and Wednesdays from 11:00 to 13:00, as well as at the Viticulture and Enology Degree Course Headquarters. Professor Catania has maintained a consistent academic presence since at least 2009, teaching specialized courses in agricultural mechanization with particular expertise in viticulture systems and precision farming technologies. Professor Catania's research spans several critical areas of modern agricultural engineering: Precision Agriculture and Smart Farming Systems Drone and Remote Sensing Applications in Agriculture Viticulture Mechanization and Oenological Plants Agricultural Machinery Design and Ergonomics Sustainable Resource Management in Mediterranean Agriculture Post-harvest Technology and Processing Systems His recent scholarly output demonstrates a clear focus on cutting-edge technological applications in agriculture, particularly the integration of drones, sensors, and AI in vineyard and olive orchard management. Professor Catania's work bridges traditional agricultural practices with modern technological innovations, addressing practical challenges in irrigation management, precision spraying, yield mapping, and sustainable resource use across Sicilian agricultural landscapes. His research methodology often combines field studies with advanced data analytics to develop practical solutions for farmers. Professor Catania maintains an active teaching schedule for the 2025/2026 academic year, instructing courses such as 'Viticulture Mechanisation and Oenological Plants,' 'Mechanics and Agricultural Mechanisation,' 'Use of Drones and Machines for Precision Agriculture,' and 'Green Landscape Systems and Maintenance.' His student evaluations over multiple academic years (2014-2024) consistently reflect strong engagement with students across various agricultural technology programs.

• Graph Algorithms
• Network Analysis
• Scientific Workflow Scheduling
• +۳ مورد دیگر

Henning Meyerhenke is a Professor at the Institute of Computer Science within the Faculty of Mathematics and Natural Sciences at Humboldt University of Berlin. He serves as Deputy Director of Teaching and Studies, focusing on graph algorithms , network analysis , and scientific workflow scheduling . His research spans complex systems modeling and parallel computing. Ranks: Professor Institution: Humboldt University of Berlin Research Interests include energy-efficient computing, heterogeneous systems, and scalable graph algorithms. Recent work explores network sparsification , workflow mapping , and graph robustness under edge deletions. His group also investigates climate science applications via climate networks . Publication Trends reflect advancements in parallel algorithms , distributed systems , and adaptive scheduling for scientific workflows. Key subfields include memory-aware computing , harmonic centrality , and edge sampling techniques. Student Advising : Michael Piechotta (PhD candidate, defended September 15, 2025)