جست‌وجوی استاد و پژوهشگر

• Renewable Energy
• Wind Turbine Technology
• Hydrokinetic Energy
• +۵ مورد دیگر

Antonio Couce Casanova is a Professor in the Department of Industrial Engineering at the Ferrol Engineering Polytechnic University College, part of the University of A Coruña (UDC) in Spain. His teaching spans multiple engineering programs including Automation and Industrial Electronics Engineering, Electrical Engineering, and various Master's degrees in Energy Efficiency, Occupational Risk Prevention, and Textile Technology. His research interests focus on renewable energy systems , particularly hydrokinetic and wind turbine technologies, energy efficiency certification, and building energy simulation. His work bridges theoretical engineering principles with practical industrial applications, especially in marine energy and sustainable manufacturing processes. Analysis of his publication record reveals a strong focus on biomimetic approaches to energy generation , with significant contributions to vertical axis wind turbine design and hydrokinetic energy systems. His more recent work (2022-2024) emphasizes meteorological data processing for building energy simulation and optimization of renewable energy systems using computational methods. Earlier work (2010-2015) focused on control systems and foundational renewable energy technologies. Dr. Couce Casanova has supervised numerous final degree and master's theses since 2013, with projects spanning energy rehabilitation, facility design, and industrial process optimization. His research has been supported by entities including Siemens Industry Software, the Galician regional government (Consellería de Economía e Industria), and NORVENTO INGENIERÍA S.L. He is actively involved in the INNOVACIONES MARINAS research unit, focusing on marine energy applications and sustainable industrial processes. His work demonstrates a consistent trajectory from theoretical control systems toward practical renewable energy solutions with marine applications.

• Computational Intelligence
• Optimization Algorithms
• Educational Technology
• +۳ مورد دیگر

Zervoudakis Konstantinos is a Researcher at the School of Production Engineering and Management, Technical University of Crete. His work focuses on computational intelligence, optimization algorithms, and their applications in education and product design. He holds a fixed-term research position and is based in Office G3.0.01, Building G3. Research Interests: His primary areas include developing nature-inspired optimization algorithms (e.g., flying fox, mayfly, and bees algorithms), applying computational methods to educational challenges like student psychological fitness assessment and group formation, and optimizing product line design using metaheuristics like Tabu Search and Differential Evolution. He also investigates the impact of ICT on education and special education teacher efficacy. Publications Trends: Recent works emphasize hybrid optimization algorithms for real-world problems (maintenance scheduling, product design), AI-driven educational tools for mental health assessment and learning grouping, and algorithmic solutions for multi-objective decision-making. His research bridges computational innovation with practical applications in education and engineering. Awards: None explicitly mentioned in the provided texts. Advising & Grants: No student advisees listed. No grants disclosed in the data.

• Wearable Robots
• Virtual Reality
• Soft Robotics
• +۴ مورد دیگر

Mark Minor is a Researcher in the Department of Mechanical Engineering at the University of Utah. His research focuses on wearable robots, virtual reality, soft robotics, haptics, and automated ground vehicles. He has contributed to projects like the MeLLO Data Library and developed haptic terrain display technologies. Key articles include work on augmented RF propagation modeling and digital spectrum twins, reflecting his interdisciplinary approach spanning robotics, control systems, and human-robot interaction. His recent work emphasizes autonomous vehicle control systems, soft robotic materials, and safety mechanisms in human-robot collaboration. Collaborations include contributions to the POWDER platform for radio dynamic zones and advancements in multi-sensory VR interfaces. Notable research themes include terrain modeling for robotics, bio-inspired mechanisms, and improving mobility technologies for assistive devices. His work integrates both hardware development and algorithmic innovation, particularly in haptic feedback and modular robotic systems.

Pamela Abshireمشاهده پروفایل

استاد

• VLSI Circuit Design
• Bioengineering
• Information Theory
• +۷ مورد دیگر

Pamela Abshire is a Professor in the Department of Electrical and Computer Engineering and the Institute for Systems Research at the University of Maryland, College Park. She holds the rank of Fischell Institute Fellow and is affiliated with the Maryland Robotics Center, Brain and Behavior Institute, and Robert E. Fischell Institute for Biomedical Devices. Her work bridges VLSI circuit design and bioengineering, focusing on performance-resource tradeoffs in natural/engineered systems. Education: B.S. Physics (Caltech, 1992), M.S. and Ph.D. in Electrical Engineering (Johns Hopkins University, 1997 and 2001). Pre-UMD career included R&D roles at Medtronic (1992-1995). Research focuses on CMOS biosensors, low-power microsystems, and bio-inspired designs for applications like cell-based sensing, robotics, and medical devices. Notable projects include nose-on-a-chip odor detection systems, ant-like microrobots, and lab-on-CMOS platforms for real-time cell monitoring. Awards include IEEE Fellow (2018), NSF CAREER Award (2003), and 2021 University Distinguished Scholar-Teacher honor. Active in academic leadership roles including ADVANCE Professor (2020-2021) and editorial work for IEEE Transactions on Circuits and Systems. Grants include NSF funding for olfactory sensing, AFOSR bio-inspired flight tech, and DARPA CogniSense initiatives. Her Integrated Biomorphic Information Systems Lab collaborates on semiconductor innovation through partnerships like the Mid-Atlantic Semiconductor Collaborative. Labs/Teams: Leads the Integrated Biomorphic Information Systems Lab and contributes to Microelectronics at Maryland group. Co-develops biohybrid systems integrating CMOS, MEMS, and biological components.

Elio Tuciمشاهده پروفایل

استاد

• Bio-inspired Robotics
• Computational Intelligence
• Collective Decision-Making
• +۷ مورد دیگر

Elio Tuci is a Professor at the Faculty of Computer Science , University of Namur , Belgium (since 2022). Prior roles include Senior Lecturer at Middlesex University London (2016–2018) and Lecturer at Aberystwyth University (2010–2016). He holds a PhD in Computer Science and Artificial Intelligence from the University of Sussex (2004) and a Master in Experimental Psychology from Sapienza University of Rome (1996). His research lies at the intersection of bio-inspired robotics , computational intelligence , and collective decision-making . He designs control mechanisms for autonomous agents to operate in complex environments, drawing inspiration from biological systems. Key themes include agent-environment interaction, communication in multi-robot systems, and the relationship between morphological structure and behavior. Recent work involves robot swarming models for Caenorhabditis elegans behavior; synchronization mechanisms in e-puck2 robots; evolutionary dispersal strategies under information costs. He co-organizes the WIVACE workshops and leads projects like BABOTS (swarming biological robots) and AUTOMATic (urban traffic management). His research has been featured in media outlets discussing robotics and self-driving technology. He advises PhD students and collaborates with teams at the Namur Digital Institute (NADI) and Namur Institute for Complex Systems (naXys) . Grants and projects focus on autonomous systems, transgenic organisms, and complex network synchronization.

Malte von Schevenمشاهده پروفایل

پژوهشگر

• Adaptive structures
• Fluid-structure interaction
• Software Engineering
• +۳ مورد دیگر

Malte von Scheven is a Senior Researcher and Deputy Director at the Institute of Structural Analysis and Dynamics at the University of Stuttgart. He holds a Dr.-Ing. degree (2009) and specializes in adaptive structures, fluid-structure interaction, and computational mechanics. Research Focus: Redundancy matrices for structural assessment, high-performance computing, actuator placement optimization Teaching: Finite element methods, computational mechanics, nonlinear structural analysis Leadership: Deputy Director since 2006, conference organizer for ECCOMAS and SMART symposia His work bridges structural mechanics with bio-inspired design, including studies on sea urchin skeletons as models for segmented shells. He has supervised numerous theses on SFRP composites, topology optimization, and adaptive systems. Scientific Engagement: Published 15+ papers on redundancy matrices and FSI Organized mini-symposia at international conferences (ECCOMAS 2024, SMART 2023) Active in university governance through Faculty Council and TIK committee Recent research investigates mechanical modeling of adaptive structures, with applications in civil engineering and architectural geometry. His redundancy matrix framework provides novel performance indicators for robust design and assemblability assessment.

• Evolutionary Algorithms
• Machine Learning
• Optimization
• +۷ مورد دیگر

Giovanni Iacca is an Associate Professor at the University of Trento's Department of Information Engineering and Computer Science (DISI), where he serves as Coordinator of the Master's Degree in Computer Science and Deputy Director of the Information Engineering and Computer Science Doctoral School. He leads the Distributed Intelligence and Optimization Lab (DIOL) and teaches courses including Computer Architectures, Introduction to Machine Learning, Bio-Inspired Artificial Intelligence, and Optimization Techniques across multiple academic programs. PhD in Computer Science, University of Jyväskylä, Finland (2011) MSc in Computer Engineering, Technical University of Bari, Italy (2006) Professor Iacca's research focuses on the intersection of evolutionary computation, machine learning, and optimization with applications in distributed systems and robotics. His work spans from theoretical foundations of memetic computing and multi-objective optimization to practical implementations in soft robotics, embedded systems, and healthcare applications. Recent efforts emphasize interpretable AI, particularly in reinforcement learning contexts, where his team develops methods to make decision processes transparent while maintaining performance. His research bridges the gap between fundamental algorithmic development and real-world engineering challenges, with over 15 years of industrial experience in optimization applied to engineering, logistics, and scheduling. Analysis of his recent publications reveals a strong trend toward interpretable AI systems, particularly in reinforcement learning contexts, with significant contributions to federated learning optimization, evolutionary neural architecture search, and applications in healthcare scheduling. His work consistently combines evolutionary algorithms with modern machine learning techniques to solve complex optimization problems across diverse domains including soft robotics, batteryless edge computing, and supply chain management. Scientific Awards: EvoApplications Best Paper Award (2017) UKCI AWARENESS Best Paper Award (2012) IEEE CIS Outstanding Student-Paper Award (2011) Professor Iacca actively supervises a large research group with numerous PhD students across multiple doctoral programs, including Information Engineering and Computer Science, Industrial Innovation, and the National PhD in Artificial Intelligence for Society. His lab has secured significant research funding through collaborations with industry partners and international research consortia. Recent grants support work on interpretable reinforcement learning, federated optimization, and applications of evolutionary computation in healthcare and robotics. He has also been appointed to editorial roles for prestigious journals including IEEE Transactions on Evolutionary Computation and Evolutionary Intelligence. The Distributed Intelligence and Optimization Lab (DIOL) under Professor Iacca's leadership comprises over 30 researchers including postdocs, PhD students, and master's students. The lab maintains strong international collaborations and has developed specialized expertise in evolutionary computation, interpretable AI, and optimization for embedded systems. Current projects include work on the EIC Pathfinder Challenge "Awareness Inside," development of methods for batteryless edge intelligence, and applications of evolutionary algorithms to healthcare scheduling problems.

• Biomedical Engineering
• Wearable Systems
• Neural Networks
• +۷ مورد دیگر

Paolo Motto Ros is a Researcher specializing in biomedical engineering, wearable systems, and low-power electronics. He has extensive experience in event-driven signal processing , functional electrical stimulation , and biocompatible sensor design , with a focus on human-machine interfaces and implantable devices. His research interests include: Biomedical instrumentation Wireless power/data transmission Surface electromyography (sEMG) Low-complexity embedded systems Plant impedance monitoring Neuroprosthetics Recent publications highlight collaborations with institutions on piezoelectric skin sensors , CMOS neural implant circuits , and plant health monitoring systems . His work spans applications in healthcare, robotics, and environmental technology.

Silvia Curteanuمشاهده پروفایل

استاد

• Neural Networks
• Bio-Inspired Computing
• Chemical Engineering Applications
• +۶ مورد دیگر

Silvia Curteanu is a Professor at the Faculty of Chemical Engineering and Environmental Protection of the Gheorghe Asachi Technical University of Iasi, Romania. Her academic career spans over 40 years, with roles ranging from researcher to PhD supervisor in chemical engineering and applied informatics. She holds a PhD in Chemical Engineering (1998) and a License in Chemical Engineering (1981). University: Gheorghe Asachi Technical University of Iasi School: Faculty of Chemical Engineering and Environmental Protection Department: Department of Chemical Engineering Academic Rank: Professor Research Interests: Specializing in artificial intelligence applications for chemical processes, Silvia Curteanu has developed methodologies using neural networks , genetic algorithms , and hybrid models for tasks like process modeling, optimization, and inverse problem solving. Her work addresses polymerization , bio-processes , electrochemical treatments , and molecular design , with notable contributions to soft sensors and multi-objective optimization . Scientific Output: With over 192 papers (133 ISI-indexed), 23 books/chapters, 14 patents, and 32 research grants, her articles focus on neural network topology , biologically inspired algorithms , and chemical process optimization . Her work has been published in journals like Journal of Chemical Engineering , Environmental Science and Pollution Research , and Applied Soft Computing . Scientific Awards: Best Paper Award (2016) for 'Performance Comparison of Different Regression Methods for a Polymerization Process with Adaptive Sampling' Grants & Projects: 32 research grants, including international collaborations 11 projects as director (1 international) Advising: Acted as PhD supervisor since 2005, mentoring students in chemical engineering and AI applications. Her laboratory collaborates with institutions like Oxford University and Aristotle University of Thessaloniki.

• Applied Mechanics
• Tribology
• Viscoelasticity
• +۴ مورد دیگر

Giuseppe Carbone is a Full Professor at the Department of Mechanics, Mathematics & Management, Politecnico di Bari, Italy. His research bridges theoretical and experimental mechanics, specializing in tribology, contact mechanics, viscoelastic materials, adhesion phenomena, and biomimetic engineering. He employs advanced numerical simulations and experimental methodologies to address complex mechanical challenges. Primary research domains include: Fundamentals of viscoelastic contact mechanics and friction dynamics Surface engineering for tribological optimization Biomimetic approaches for material and system design Advanced lubrication systems and bearing technologies Analysis of his 15 most recent publications (2024-2025) reveals a consistent focus on viscoelastic material behavior under dynamic contact conditions. Key trends include: Integration of numerical and experimental techniques for contact mechanics Innovations in adhesion/friction modeling for rough surfaces Applications in robotics, automotive systems, and bio-inspired engineering Development of novel computational methods for tribological systems

• Electromagnetic
• Microwave and Antenna Technologies
• Artificial Intelligence
• +۱ مورد دیگر

Erhan KURT is a Lecturer at the Faculty of Engineering and Architecture , Kırşehir Ahi Evran University , since 2024. Previously, he worked as a Research Assistant at Nuh Naci Yazgan University from 2012 to 2024. PhD in Electrical and Electronics Engineering, Erciyes University (2023) MSc in Electronic Engineering, Erciyes University (2014) BSc in Electrical and Electronics Engineering, Erciyes University (2011) His research focuses on Electromagnetic Field Analysis , Microwave Engineering , and Artificial Intelligence Applications in antenna design. He has contributed to optimization algorithms for antenna array synthesis, sidelobe suppression, and pattern nulling. A review of his 15 most recent articles reveals trends in Antenna Array Optimization using bio-inspired algorithms (e.g., Ant Lion, Salp Swarm, Differential Evolution) and applications of AI in microwave engineering. Key subfields include Computational Electromagnetics , Beamforming , and Algorithmic Antenna Design . He has collaborated extensively with researchers such as Kerim Güney , Suad Başbuğ , and Mustafa Türkmen on interdisciplinary projects involving signal processing and antenna systems.

Seungwoo JEمشاهده پروفایل

استادیار

• Human-Computer Interaction
• User Experience
• Interactive Design
• +۳ مورد دیگر

Seungwoo JE is an Assistant Professor at the School of Innovation and Creative Design at Southern University of Science and Technology (SUSTech). A maker, User Experience (UX), and Human-Computer Interaction (HCI) researcher, he leverages emerging technologies to create novel user interactions. Education : Ph.D., Master’s, and BS in Industrial Design from KAIST, Korea. Research interests span UX innovation, haptic interfaces, and maker technologies. His work integrates tactile feedback, shape-changing systems, and augmented reality to redefine human-computer engagement. Articles in ACM CHI , UIST , and IEEE Transactions on Haptics highlight his contributions to wearable haptics and immersive design. Awards include the prestigious Global Ph.D. Fellowship (Korean Ministry of Education), Red Dot , iF , and IDEA Awards . He holds international patents in Korea and the U.S. and has secured industry funding from Samsung and Hyundai , alongside national grants from National Research Foundation (NRF) Korea .

Konstantin Fackeldeyمشاهده پروفایل

پژوهشگر

• Drug Discovery
• Computational Biology
• High-Performance Computing
• +۷ مورد دیگر

Konstantin Fackeldey is a researcher at the Technical University of Berlin and heads the Efficient Large Scale Computing group at the Zuse Institute Berlin (ZIB) . His roles include Deputy Director of the Central Institute SETUB and leadership in the Activity Group Mathematics of Data Science at MATH+. He also serves as a high school mathematics teacher and contributes to the Q-Master program. His research spans drug discovery using high-performance computing and machine learning , with a focus on Protein-Ligand Docking (VirtualFlow Project) and Markov State Models . Collaborative projects include Quantum Skills in Teacher Education and co-organizing the Workshop on Tensor Methods for Quantum Simulation . He holds a habilitation in Applied Mathematics from TU Berlin (2015). Key contributions include developing algorithms for adaptive virtual screening and non-equilibrium molecular dynamics . His work bridges mathematical theory with practical drug design , involving interdisciplinary collaborations across institutions.

Ray Fertigمشاهده پروفایل

استاد

• Dislocation Dynamics Simulations
• Multiscale Constitutive Modeling
• Physics-Based Modeling of Composite Fatigue and Failure
• +۶ مورد دیگر

Dr. Ray Fertig is the Department Head and Professor of Mechanical Engineering at the University of Wyoming, where he has held academic roles since 2011. He received his Ph.D. (2010) and M.S. (2005) in Materials Science from Cornell University, and M.S. (2003) and B.S. (2001) in Mechanical Engineering and Mathematics from the University of Wyoming. Department Head, 2024–present Professor, 2023–present Faculty, Materials Science and Engineering Program His research focuses on physics-based multiscale modeling of composite fatigue and failure, with specific interests in dislocation dynamics simulations , bio-inspired composite design , and microcracking in porous ceramics . He investigates how microstructural randomness affects composite reliability and develops stochastic models for failure prediction. Key publication trends include multiscale fracture mechanics , stochastic microstructure modeling , and applications of bio-inspired algorithms to composite optimization. His work spans material characterization, computational modeling, and integration into commercial finite element codes. Dr. Fertig advises graduate students in the Fertig Research Group , which combines virtual experiments , in-situ observations , and macroscale testing to validate failure models. Current projects link composite processing variations to microstructural and property distributions.

Kouros Zanbouriمشاهده پروفایل

پژوهشگر

• Cloud Computing
• Fog Computing
• Internet of Things
• +۲ مورد دیگر

Kouros Zanbouri is a CONNECT PhD researcher at University College Cork , supervised by Prof. Dirk Pesch and Prof. Cormac Sreenan. Education : BSc in Information Technology (IT) engineering (2016) MSc in IT engineering – specialization in Computer Networks (2018) Research Interests : Wireless Time-Sensitive Networking (TSN) Cloud and Fog Computing Internet of Things (IoT) Engineering Optimization Metaheuristics Research Trends : His recent publications focus on integrating TSN with 5G for industrial settings, optimizing blockchain-based IoT systems using bio-inspired algorithms, and designing energy-efficient IoT solutions for industrial applications. His work spans theoretical modeling, algorithm development, and real-world implementation in smart cities and dependable networks. Academic Contributions : Guest reviewer for multiple journals Active in interdisciplinary research combining IoT, optimization algorithms, and network engineering