جست‌وجوی استاد و پژوهشگر

Jiri Wiedermannمشاهده پروفایل

استاد

• Theoretical computer science
• Computational complexity
• Models of sequential and parallel computational systems
• +۷ مورد دیگر

Jiri Wiedermann is a Professor of Computer Science at Charles University and has served as Director of the Institute of Computer Science at the Academy of Sciences of the Czech Republic since 2000. His academic journey includes an Assoc. Prof. position at Charles University (2000) and degrees from Comenius University (RNDr., M.Sc.) and Czechoslovak Academy of Sciences (CSc., DrSc.). Education : DrSc. in Computer Science (Comenius University, Bratislava, 1993) CSc. (equiv. to PhD) in Computer Science (Czechoslovak Academy of Sciences, Prague, 1980) RNDr. and M.Sc. in Computer Science (Comenius University, Bratislava, 1974) His research spans Theoretical Computer Science , focusing on computational complexity, neurocomputing, and non-standard computing. He explores embodied cognition, mirror neurons, and autopoietic automata, bridging neural models with algorithmic frameworks. The 15 most recent publications highlight his work on interactive computation, fuzzy Turing machines, evolving artificial living systems, and cognitive architectures. Key trends include machine learning inspired by biological systems , computational limits of cognition , and formal models of neural processes . Scientific Awards : Member of Academia Europaea (since 2006) Member of the Czech Learned Society (since 2003) Board of Directors, ERCIM (since 1997) Leadership roles in EATCS (Vicepresident 1997-2002)

• Robotics
• Artificial Intelligence
• Evolutionary Computing
• +۱۲ مورد دیگر

Kyrre Harald Glette is a Professor in the Department for Informatics at the University of Oslo , affiliated with the Robotics and Intelligent Systems Research Group and the RITMO Centre for Interdisciplinary Studies in Rhythm, Time and Motion . His research focuses on the co-design of robot morphology and control using evolutionary and bio-inspired artificial intelligence methods. Research Interests: Robotics and Intelligent Systems Evolutionary Robotics and Co-Design of Morphology and Control Artificial Intelligence and Machine Learning Evolvable Hardware and Embodied Computation Computational Creativity and Music-AI Interaction Human-Robot Interaction and Swarm Robotics His recent publications (2023–2025) reflect a strong interdisciplinary trend, combining robotics, evolutionary computation, and music technology. Key themes include evolutionary design of modular robots , real-time adaptation in bio-inspired systems , interactive sonification , and AI-driven music generation . His work often involves the DyRET robotic platform, emphasizing real-world evolution and embodied learning. Scientific Contributions: Extensive publications in top venues like Frontiers in Robotics and AI , IEEE ICRA , GECCO , and Nature Machine Intelligence . Development of open-source robotic platforms and frameworks for evolutionary robotics. Interdisciplinary work bridging AI, neuroscience, and music. Advising and Projects: He supervises MSc students in evolutionary robotics, robot locomotion, and musical robot swarms. He is involved in several research projects including Predictive and Intuitive Robot Companion (PIRC) , Modeling and Robots , Multimodal Elderly Care Systems (MECS) , Musical Human-Machine Interaction , and Neurophysiological Mechanisms of Human Auditory Predictions (AudioPred) . Labs and Research Groups: He is a key member of the Robotics and Intelligent Systems (ROBIN) group, the RITMO Centre of Excellence , and the Creative Computing Hub Oslo (C2HO) . These groups support interdisciplinary research in AI, robotics, music, and human interaction.

Falk Tauberمشاهده پروفایل

پژوهشگر

• Bioinspired Materials
• Soft Robotics
• Plant-Inspired Actuators
• +۳ مورد دیگر

Dr. Falk Tauber is a postdoctoral researcher and coordinator of the liv MatS Demonstrator Project at the University of Freiburg's Plant Biomechanics Group and the Freiburg Center for Interactive Materials and Bioinspired Technologies (FIT). His work focuses on developing bioinspired materials systems, soft robotics, and biomimetic actuators. He coordinates interdisciplinary projects integrating innovations from multiple research areas, collaborating with industrial partners to demonstrate technological feasibility across applications. Under the supervision of Prof. Dr. Thomas Speck, Tauber's research explores plant-inspired mechanisms such as snap-trapping systems, peristaltic pumping, and shape-memory materials. His projects aim to bridge biological principles with engineering solutions for soft robotics, medical devices, and sustainable materials. Key collaborations include work on artificial Venus flytrap actuators, biomimetic valves, and pressure-sensing capsules for gastrointestinal monitoring. Tauber actively contributes to academic discourse through editorials, conference proceedings, and peer-reviewed articles, emphasizing future directions in soft robotics and biohybrid systems. His publications span journals like Bioinspiration & Biomimetics , Science Robotics , and MRS Bulletin , reflecting his expertise in biomaterials and interdisciplinary engineering. He leads the development of demonstrators in the liv MatS cluster, focusing on three series of devices that showcase bioinspired technologies. These projects emphasize practical applications, such as adaptive actuators for industrial use and medical tools inspired by biological systems. His work is funded by the German Research Foundation (DFG) under the Excellence Strategy.

Emma Wilsonمشاهده پروفایل

مدرس

• Systems and Control Theory
• Digital Health Applications
• Adaptive Treatments
• +۵ مورد دیگر

Dr Emma Wilson is a Lecturer in the Computing and Communications department at Lancaster University, focusing on systems and control theory applied to healthcare and biological systems. Her interdisciplinary research integrates engineering principles with biomedical challenges to improve health outcomes, including adaptive treatments, bio-inspired robotics, and muscle modeling. Her research spans multiple areas such as control theory, bio-inspired control mechanisms, brain-based robotics, and computational modeling of biological systems. A key theme is translating insights from biological systems into engineered solutions and vice versa, particularly in digital health applications like personalized treatment decisions and dynamic health modeling. Recent work includes developing robust control algorithms for anticoagulant therapies and neuro-inspired adaptive systems for robotics. She leads projects like DCQ (Cyber Security of Digital Medical Devices) and collaborates on initiatives like the Health Behavior Change research group. Her publications reflect a blend of theoretical control systems research with practical healthcare applications. Dr Wilson is affiliated with the Lancaster Intelligent, Robotic and Autonomous Systems Centre (LIRA) and the Data Science Centre (SCC), emphasizing her role in cutting-edge interdisciplinary research.

Sylvain Saïghiمشاهده پروفایل

مدرس

• Neuromorphic Engineering
• Artificial Neural Networks
• Green Computing
• +۷ مورد دیگر

Sylvain Saïghi is a lecturer and researcher in electronics at the University of Bordeaux, affiliated with the IMS laboratory (Intégration du Matériel au Système), a joint unit of CNRS, the University of Bordeaux, and Bordeaux INP. He specializes in neuromorphic engineering and low-power artificial intelligence systems. His research focuses on developing hardware-based artificial intelligence solutions inspired by the human nervous system. He designs electronic circuits and chips that mimic neurons and synapses using memristors and spiking neural networks, enabling energy-efficient 'intelligent' sensors for edge computing applications such as speech and pedestrian recognition. His work lies at the intersection of electronics, neuroscience, and machine learning, aiming to reduce the energy footprint of AI technologies. The trends in his publications reveal a sustained focus on neuromorphic hardware, particularly in implementing plasticity and learning mechanisms in solid-state devices. His work spans from fundamental analog neuron modeling to advanced spintronic neural networks, consistently targeting energy-efficient, brain-inspired computing systems. Sylvain Saïghi leads the 5-year Green AI chair at the University of Bordeaux, launched in 2021, dedicated to designing frugal and sustainable AI solutions. He has secured significant research funding through this initiative and collaborates across disciplines and institutions. Multilayer spintronic neural networks with radiofrequency connections (Nature Nanotechnology, 2023) Learning through ferroelectric domain dynamics in solid-state synapses (Nature Communications, 2017) Plasticity in memristive devices for spiking neural networks (Frontiers in Neuroscience, 2015) Neuromorphic silicon neuron circuits (Frontiers in Neuroscience, 2011) A Library of Analog Operators Based on the Hodgkin-Huxley Formalism (IEEE TBioCAS, 2011) Sylvain Saïghi has advised several students in the fields of neuromorphic engineering and AI hardware, though specific names are not listed in the provided text. He actively participates in public science outreach, including events like the European Researchers’ Night, and has been featured in media outlets such as TV7, Sud Ouest, and Science et Vie. He is a key member of the IMS laboratory team, where he leads research in neuromorphic systems and contributes to interdisciplinary projects linking electronics, neuroscience, and sustainable computing. His lab focuses on designing and testing novel hardware architectures for intelligent edge devices.

Brett Fajenمشاهده پروفایل

استاد

• Perception and Action
• Visual Control of Locomotion
• Perceptual-Motor Learning
• +۵ مورد دیگر

Brett Fajen is a Professor and Associate Dean for Academic Affairs at the School of Humanities, Arts, and Social Sciences (HASS) at Rensselaer Polytechnic Institute. He directs the Perception and Action (PandA) Laboratory, where he investigates perception-action coupling, locomotion control, and perceptual-motor learning through immersive virtual environments and motion capture technology. His research bridges ecological psychology, dynamical systems theory, and computational neuroscience. Key projects include studying optic flow in steering tasks, gaze-action coordination during obstacle avoidance, and neural models of self-motion perception. His work has applications in robotics, motor skill training, and sensory-motor rehabilitation. Recent publications span topics including optical flow and aging curvilinear motion perception neural modeling of perceptual-motor learning adaptive sensory encoding mechanisms affordance-based decision making perceptual stability during locomotion . Fajen serves as Associate Editor for the Journal of Experimental Psychology: Human Perception and Performance and has secured NIH funding for visual locomotion guidance studies.

• Biomimetic Architecture
• Artificial Intelligence in Design
• Extended Reality (XR)
• +۵ مورد دیگر

Mauro Costa Couceiro is a Professor and Senior Researcher at ISTAR-Iscte (Research Center in Information Sciences, Technologies and Architecture), University Institute of Lisbon. His research integrates biomimetic principles, AI, XR, and robotics into architectural design, emphasizing sustainability and human-nature interaction. He leads the FCT-funded project Generative Architectural Design: Promoting Human-Biome Interaction through Traditional Approaches and Emerging Technologies and previously co-directed the Santa Cruz Research Project at the University of Coimbra, focused on UNESCO heritage preservation. Education: PhD in Architecture (Universitat Internacional de Catalunya, 2009), Master's degrees in World History of Architecture/Urbanism and Bio-digital Architecture/Genetics, and a six-year Architecture degree from Technical University of Lisbon. Research Interests: Biomimetic architecture, AI/XR applications in design, generative methodologies, sustainable solutions through robotics (Industry 4.0), and digital manufacturing (CAD/CAM). His work bridges biological systems with technological innovation for adaptive environments. Publications: His recent works (2017–2024) explore biomimicry, VR/AR heritage reconstruction, and urban innovation. Trends include algorithmic modeling, sustainable material use, and cognitive extensions via technology. Advising & Grants: Supervised 2 PhD and 17 Master’s students. Current grant leadership includes FCT projects on generative architecture. Collaborations span institutions like Hongik University, University of São Paulo, and IAAC Barcelona. Labs/Teams: Affiliated with ISTAR-Iscte’s Digital Living Spaces group, focusing on human-machine-nature interactions and computational design.

Philipp Junkerمشاهده پروفایل

دانشیار

• Material Science
• Computational Mechanics
• Phase Transformations
• +۳ مورد دیگر

Priv.-Doz. Dr.-Ing. Philipp Junker is an Associate Professor at the Chair of Mechanics-Material Theory at Ruhr-Universität Bochum. His research focuses on variational methods in material modeling, particularly applications of Hamilton’s Principle to describe load-dependent microstructure evolution in solids and solve inverse problems like topology optimization through bio-inspired growth approaches. Research Interests : Variational methods in material modeling Phase transformations in solids Energy-based modeling strategies Topology optimization via biological growth processes He is also a managing partner at ComMaSIM UG (hb.), indicating industry-academia collaboration beyond his university role.

• Embedded Systems
• Internet of Things (IoT)
• Smart Mobility
• +۶ مورد دیگر

Vannel Fabien is a Full Professor at the Haute école du paysage, d'ingénierie et d'architecture de Genève (HEPIA), part of the HES-SO University of Applied Sciences and Arts. He is affiliated with the Technical and IT School and the Department of Computer Science and Communication Systems. His research focuses on embedded systems, IoT, FPGA-based architectures, neuromorphic computing, and quantum communication technologies. Education: PhD in Bio-inspired Computing (2007), École Polytechnique Fédérale de Lausanne (EPFL), supervised by Daniel Mange Research Interests: Development of self-organizing neuromorphic hardware architectures (SOMA project) High-performance FPGA-based platforms for IoT security and random number generation Cellular computing inspired by biological systems 3D Network-on-Chip (NoC) architectures and dynamic resource allocation Quantum key distribution (QKD) systems for secure communication His work combines hardware design with bio-inspired algorithms, aiming to create adaptive, energy-efficient computing systems. Recent projects include SCALPsim (a 3D NoC modeling tool) and FPGA-based validation platforms for TRNGs. Grants & Projects: Principal investigator for SOMA (2018-2021, SNSF-funded CHF 461,238) Co-applicant for iNUIT-2014 ArchSensor (2014-2015, HES-SO-funded CHF 220,000) Contributor to heterogeneous computing platforms (AcceleRation, 2013-2014) Labs & Teams: Lead researcher in the SOMA team at HES-SO, collaborating with institutions like Université de Nice and INRIA.

Raquel Dosil Lagoمشاهده پروفایل

استادیار

• Computer Vision
• Image Analysis
• Artificial Intelligence
• +۴ مورد دیگر

Raquel Dosil Lago is an Assistant Professor at the University of Santiago de Compostela, affiliated with the Department of Electronics and Computing within the Higher Technical School of Engineering. Her research focuses on Artificial Vision, Computer Vision, and Robotics, with applications in environmental monitoring and medical imaging. She holds a PhD in Computer Science from the University of Santiago de Compostela (2005), supervised by Dr. José Ramón Fernández Vidal and Dr. José Manuel Pardo López. Her research interests emphasize multisensory systems, drone-based environmental surveillance, visual attention models, and feature detection in 3D medical imaging. Recent work includes drone payloads for maritime pollution detection and biologically inspired vision systems. Earlier contributions span saliency detection, photogrammetry, and composite feature integration for motion analysis. Publications reflect a progression from early medical imaging and 3D pattern partitioning (2000s) to modern drone and environmental applications (2020s). Key themes include sensor fusion, CNN-based detection, and human-like visual attention mechanisms. She is part of the Artificial Vision research group, collaborating on projects like BIVSEE and AVSS challenges. No scientific awards are explicitly mentioned. Her academic advising includes her doctoral thesis committee. Research grants and future work details are not provided in the source text.

XOSE RAMON FERNANDEZ VIDALمشاهده پروفایل

استاد

• Computer Vision
• Image Processing
• Machine Learning
• +۵ مورد دیگر

Xosé Ramón Fernández Vidal is a Professor at the University of Santiago de Compostela, affiliated with the Department of Applied Physics within the Higher Polytechnic School of Engineering. His research focuses on Computer Vision, Image Processing, and Machine Learning, with applications in robotics, medical imaging, and environmental analysis. He holds a Doctorate from the same university (1996), specializing in geometric recognition methodologies. His work bridges computational models of visual attention and practical systems like UAV navigation, wireframe modeling for 3D reconstruction, and synthetic image generation for AI training. He is part of the Artificial Vision group at the Center for Research in Intelligent Technologies (CITIUS). Key research themes include visual saliency modeling, robust feature matching in low-textured environments, and algorithmic approaches to scene recognition. His contributions span over 40 publications since 1997, emphasizing interdisciplinary applications such as flour quality assessment via neural networks and environmental variable analysis in agricultural settings. While no formal awards are listed, his sustained output reflects impactful contributions to computational vision systems. His current projects involve developing biologically inspired vision systems (e.g., BIVSEE) and advancing datasets like Sid4vam for attention modeling. He collaborates with industry and academic partners in robotics, medical imaging, and environmental monitoring. No doctoral students are explicitly listed, though his research groups likely involve postgraduate researchers. His address is in Compostela, Galicia, Spain.

Jeff Cluneمشاهده پروفایل

استاد

• Artificial Intelligence
• Machine Learning
• Neuroevolution
• +۵ مورد دیگر

Jeff Clune is a Professor in the Department of Computer Science at the University of British Columbia (UBC), Canada, and a Canada CIFAR AI Chair at the Vector Institute. He also serves as a Senior Research Advisor at DeepMind. His work focuses on advancing artificial intelligence through evolutionary computation, neuroevolution, and open-ended systems. Clune's research explores topics such as continual learning, generative models (e.g., Genie), and automated scientific discovery. He is known for developing algorithms like Go-Explore and pioneering methods in neuroevolution to create robust and adaptable AI systems. His academic affiliations include the UBC Faculty of Science and collaborations with industry leaders like DeepMind. Clune teaches courses on machine learning and data mining, emphasizing practical applications and theoretical foundations. His awards include the SIGEVO Impact Award and recognition for outstanding publications in AI research. Notable projects include the development of the Go-Explore algorithm and contributions to AI safety and ethical frameworks. Clune's work bridges biological inspiration with machine learning, aiming to create systems that evolve and learn like natural organisms. Research interests span AI safety, generative AI, robotics, and scalable learning algorithms. He has published extensively on topics like neural network dynamics, open-endedness, and automated experimentation. Current projects include enhancing AI's ability to self-improve and exploring ethical implications of advanced AI systems.

• Cloud Computing
• Distributed Systems
• High-Performance Computing
• +۵ مورد دیگر

Raja Appuswamy is an Assistant Professor in the Department of Data Science at EURECOM, focusing on data management on modern hardware and molecular information storage. His research integrates cutting-edge storage technologies with bioinformatics, particularly in DNA-based data storage. He teaches courses in cloud computing, distributed systems, and databases. His work spans Optimizing storage hierarchies with DNA archival systems Hardware-conscious algorithms for GPUs and heterogeneous architectures Error correction in molecular storage Long-term database preservation strategies Key research interests include Cross-architecture data joins (e.g., OneJoin, XJoin) Cold storage innovation with CMOSS and OligoArchive Integration of bio-inspired storage with traditional computing and explores interdisciplinary challenges at the intersection of computer science and molecular biology. Publications emphasize scalable solutions for DNA storage density, error tolerance, and archival systems. Awards highlight contributions to DNA-based image encoding, storage reliability, and page cache checksums. Current projects focus on enzymatic DNA ligations for storage density improvement, motif-based error correction, and hardware acceleration for knowledge graphs. His work targets both theoretical advancements and practical implementations in storage systems.

Oliver Laytonمشاهده پروفایل

دانشیار

• Machine Learning
• Computational neuroscience
• Neural Modeling
• +۴ مورد دیگر

Oliver Layton is an Associate Professor and Associate Chair of the Computer Science Department at Colby College, Maine. His research bridges computational neuroscience and machine learning, focusing on neural modeling of visual perception and self-motion estimation. He teaches courses in Mathematical Data Analysis and Visualization (CS252), Neural Networks (CS343), and Deep Learning (CS444). Postdoctoral scholar, Rensselaer Polytechnic Institute Ph.D., Cognitive and Neural Systems, Boston University B.A., Mathematics and Computational Neuroscience, Skidmore College His expertise spans computational neuroscience, neural modeling, and visual perception, with emphasis on optic flow processing and its applications. Research explores how biological systems (like primate MSTd) estimate heading and self-motion, using biologically inspired neural networks and dynamic sensory encoding models. Recent publications focus on deep learning approaches to optic flow analysis, heading perception stability, and curvilinear motion modeling. Key trends include applying convolutional neural networks to simulate MSTd tuning, investigating sparseness and ReLU activation impacts, and comparing human and AI performance in self-motion estimation tasks.

Scott David Kellyمشاهده پروفایل

استاد

• Geometric Mechanics
• Robotic Locomotion
• Nonlinear Dynamics
• +۳ مورد دیگر

Scott David Kelly is a Professor of Mechanical Engineering and Engineering Science at the University of North Carolina at Charlotte (UNC Charlotte), affiliated with the William States Lee College of Engineering. He holds an Honors Faculty position until June 2026. His research focuses on geometric mechanics, nonlinear dynamics, and control systems, particularly in bio-inspired robotics and fluid dynamics. Kelly earned his B.S. from Cornell University (1991), M.S. and Ph.D. from Caltech (1992, 1998), followed by a postdoc at Caltech and industry experience at Entelos before joining UNC Charlotte in 2007. Education: B.S., Mechanical & Aerospace Engineering, Cornell University, 1991 M.S., Mechanical Engineering, California Institute of Technology, 1992 Ph.D., Mechanical Engineering, California Institute of Technology, 1998 Research interests include differential geometric methods in mechanics, bio-inspired robotic locomotion, and nonlinear control systems. His work often explores energy-efficient systems inspired by nature, such as aquatic propulsion via vortex shedding and multi-vehicle coordination. Recent publications span topics like inertial particle transport in fluids and HIV prevalence modeling. Teaching involves courses on mechanical engineering and applied mathematics. He contributes to labs and teams focused on fluid dynamics and robotics. Contact details include email addresses and his office at Duke Centennial Hall.