Find Academic Supervisors

Emma WilsonView profile

Lecturer

• Systems and Control Theory
• Digital Health Applications
• Adaptive Treatments
• +5 more

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 SaïghiView profile

Lecturer

• Neuromorphic Engineering
• Artificial Neural Networks
• Green Computing
• +7 more

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 FajenView profile

Professor

• Perception and Action
• Visual Control of Locomotion
• Perceptual-Motor Learning
• +5 more

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)
• +5 more

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 JunkerView profile

Associate Professor

• Material Science
• Computational Mechanics
• Phase Transformations
• +3 more

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
• +6 more

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 LagoView profile

Assistant Professor

• Computer Vision
• Image Analysis
• Artificial Intelligence
• +4 more

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 VIDALView profile

Professor

• Computer Vision
• Image Processing
• Machine Learning
• +5 more

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 CluneView profile

Professor

• Artificial Intelligence
• Machine Learning
• Neuroevolution
• +5 more

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
• +5 more

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 LaytonView profile

Associate Professor

• Machine Learning
• Computational neuroscience
• Neural Modeling
• +4 more

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 KellyView profile

Professor

• Geometric Mechanics
• Robotic Locomotion
• Nonlinear Dynamics
• +3 more

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.

Orit PelegView profile

Associate Professor

• Biological Communication Systems
• Collective Behavior in Insects
• Firefly Synchronization
• +6 more

Orit Peleg is an Associate Professor at the University of Colorado Boulder in the Department of Computer Science , BioFrontiers Institute , and holds a courtesy appointment in the Department of Ecology and Evolutionary Biology . She is also an External Faculty member at the Santa Fe Institute . Her interdisciplinary lab investigates biological communication signals using insect swarms as model systems, focusing on fireflies and honeybees. Research Interests: The lab explores universal principles of biological communication across modalities (chemical, sound, light), emphasizing spatiotemporal integration, signal optimization, and collective decision-making. Current projects include firefly flash synchronization, honeybee aggregation dynamics, honeycomb construction mechanics, and deep-sea temporal structures. Scientific Awards: Cottrell Scholar Award Sloan Fellow in Physics National Geographic Explorer Collaborations: Partners include Prof. G.J. Stephens (Okinawa Institute of Technology/Vrije Universiteit Amsterdam), Prof. K. Jayaram (CU Boulder), Prof. F. López Jiménez (CU Boulder), Prof. L. Mahadevan (Harvard), and Prof. M. Dacke (Lund University).

Aboozar TaherkhaniView profile

Senior Lecturer

• Artificial Intelligence
• Data Science
• Big Data
• +12 more

Dr. Aboozar Taherkhani is a Senior Lecturer in the School of Computer Science and Informatics at De Montfort University, UK, within the Faculty of Computing, Engineering and Media. His research integrates computer science and neuroscience, focusing on artificial intelligence, deep learning, and spiking neural networks. He is affiliated with the Institute of Artificial Intelligence (IAI) at DMU and has previously served as a full-time Research Fellow at Nottingham Trent University. His research interests include: Artificial Intelligence and Machine Learning Deep and Spiking Neural Networks Multimodal Data Analysis Image and Nonlinear Signal Processing Robotics, IoT, and Natural Language Processing Activity Recognition and Computational Neuroscience The recent publications highlight a strong trend in deep learning applications across domains such as healthcare (breast ultrasound segmentation, bone scaffolds), agriculture (hydroponics), robotics (3D reconstruction, gesture recognition), and privacy-preserving AI. His work emphasizes both theoretical advancements in neural models and practical implementations on edge devices and multimodal systems. Dr. Taherkhani has secured research funding through the Leverhulme Trust Research Project Grant RPG-2016-252 on multimodal data spaces. While no specific awards are listed, his extensive publication record in top journals reflects scholarly impact. He teaches courses such as Intelligent Mobile Robots, Natural Language Processing, Deep Neural Networks, and programming in C++, Python, and C#. He leads a research lab at DMU and supervises graduate students, though specific advisee names are not provided. His lab focuses on AI, robotics, and embedded intelligent systems.

Carsten BehnView profile

Professor

• Robotics
• Biomechanics
• Control Systems
• +3 more

Carsten Behn is a Professor at Hochschule Schmalkalden, specializing in Engineering Mathematics within the Faculty of Mechanical Engineering. He holds a habilitation from TU Ilmenau in biologically inspired motion systems and has served as a lecturer at Hochschule Merseburg and TU Ilmenau. Education: Diplom-Mathematiker (2001), Dr.-Ing. (2005), Dr.-Ing. habil. (2013) His research focuses on tactile sensors for surface texture and object contour detection, adaptive control in compliant robotics, and mathematical modeling of biomimetic systems. Publications emphasize sensor dynamics, mechatronic design, and applications of vibrissae-inspired engineering. Recent articles explore tactile sensor signal tuning, flow detection using artificial vibrissae, and adaptive control in snake-like locomotion systems. His work bridges mechanical modeling, control theory, and bioinspired robotics. Behn has served on technical program committees for conferences like ICINCO 2018 and IEEE IRC 2019. He supervises PhD students Moritz Scharff and Lukas Merker in Mechanical Engineering at TU Ilmenau.