جست‌وجوی استاد و پژوهشگر

Shigang Yueمشاهده پروفایل

استاد

• Artificial Intelligence
• Computer Vision
• Robotics
• +۴ مورد دیگر

Professor Shigang Yue is a Professor of Computer Science at the University of Leicester's Computing and Mathematical Sciences department. His research focuses on artificial intelligence, computer vision, robotics, neuroscience, and bio-inspired systems. He has published over 200 papers and led EU-funded projects. He holds a PhD from Beijing University of Technology (1996) and was an Alexander von Humboldt Research Fellow (2000-2001). Research interests include bio-inspired visual neural networks, autonomous robotics, medical image analysis, machine learning, and swarm intelligence. He has coordinated EU FP7 and Horizon 2020 projects and examined over 20 PhD theses. His work bridges biological systems and robotics, emphasizing collision avoidance, motion detection, and swarm robotics. Notable contributions include the I2Bot platform for insect navigation simulation, bio-inspired collision detection models (e.g., LGMD), and frameworks for small target tracking. He is an EPSRC peer reviewer and editorial board member for international journals. Labs and teams: Active in developing bio-inspired robotics systems and collaborative platforms like Colcos φ for swarm robotics. His group welcomes PhD and visiting students in AI and robotics.

Jim Portegiesمشاهده پروفایل

استادیار

• Mathematical Analysis
• Machine Learning
• Artificial Intelligence
• +۴ مورد دیگر

Jim Portegies is an Assistant Professor in the Applied Analysis group at TU/e's Centre for Analysis, Scientific Computing and Applications (CASA). He holds affiliations with EAISI Foundational and EAISI Mobility within the Eindhoven Artificial Intelligence Systems Institute (EAISI). His research focuses on applying mathematical analysis, geometry, and measure theory to develop universal learning algorithms that mimic human learning processes. Education: MSc in Industrial & Applied Mathematics and Applied Physics (TU/e, 2009); PhD in Mathematics from NYU's Courant Institute (2014). Postdoc at Max Planck Institute for Mathematics in Sciences (Leipzig, 2014–2016) before returning to TU/e. Member of TU/e Young Academy of Engineering. Research Interests: Mathematical foundations of machine learning Geometric data analysis Design of biologically-inspired learning systems Nonlinear dimensionality reduction techniques Notable Achievements: Member of TU/e Young Academy of Engineering Recipient of multiple grants for AI/ML research Labs/Teams: Active in EAISI Foundational (theoretical AI) and EAISI Mobility (applied AI for mobility systems).

• Artificial Intelligence
• Machine Learning
• Neuroscience
• +۳ مورد دیگر

Mia-Katrin Ose Kvalsund is a Doctoral Research Fellow in Condensed Matter Physics at the University of Oslo, affiliated with the Faculty of Mathematics and Natural Sciences. She holds a Master's degree in Informatics: Robotics and Intelligent Systems from the University of Oslo (2022). Her research interests span interdisciplinary fields including Artificial Intelligence, Machine Learning, Neuroscience, Evolutionary Computing, Biologically-inspired Computing, and Robotics. She contributes to projects such as COCOMO (Co-evolution of Control and Morphologies) and is part of the BioAI – Biologically inspired Artificial Intelligence research group at Simula Research Laboratory. Currently based at the Physics Building (Room Ø456), her work bridges computational methods with biological principles to advance AI and robotics. No specific awards or grants are listed in the provided information.

Kathryn Daltorioمشاهده پروفایل

دانشیار

• Biologically-Inspired Robotics
• Robot Locomotion
• Soft Robotics
• +۳ مورد دیگر

Kathryn Daltorio is an Associate Professor in the Department of Mechanical and Aerospace Engineering at Case Western Reserve University's Case School of Engineering. Her research focuses on developing biologically-inspired robots that navigate complex environments, drawing insights from animal behaviors such as earthworm locomotion and cockroach decision-making. She leads the Biologically-Inspired Robotic Lab, where her team designs robots using advanced materials like soft polymers, shape-memory alloys, and gecko-inspired adhesives. Education: PhD in Mechanical & Aerospace Engineering (Case Western Reserve University, 2013) MS in Mechanical & Aerospace Engineering (Case Western Reserve University, 2007) BS in Mechanical & Aerospace Engineering (Case Western Reserve University, 2005) Research Interests: Robotics inspired by animal locomotion (e.g., worms, crabs, insects) Neurobiologically-inspired control systems Soft robotics and compliant materials Adaptive legged systems for amphibious environments Publications highlight advancements in peristaltic robots, heteroclinic channel-based control, and crab-inspired leg designs. Recent work emphasizes energy-efficient traversal in unstructured terrain and multimodal locomotion enabled by metamaterials. Awards include the NSF CAREER Award (2021) and ONR YIP Award (2019). She is a member of ASME and IEEE, contributing to both academic and industry-oriented robotics projects. Labs/Teams: Biologically-Inspired Robotic Lab (BIRL) focuses on prototyping robots that integrate biological principles with cutting-edge engineering to solve real-world challenges in search-and-rescue, environmental monitoring, and disaster response.

Roger Quinnمشاهده پروفایل

استاد

• Biorobotics
• Control Systems
• Robotics
• +۴ مورد دیگر

Roger D. Quinn is the Arthur P. Armington Professor of Engineering at Case Western Reserve University's Department of Mechanical and Aerospace Engineering, part of the Case School of Engineering. He also serves as Director of the Biologically Inspired Robotics laboratory. His research focuses on developing robots and control strategies based on biological principles, modeling animal neuromechanical systems, and creating bioinspired devices such as exoskeletons and soft robots. Quinn has authored over 300 publications and holds 9 patents, including innovations in robotic locomotion and neuroprosthetics. Education: PhD in Engineering Science and Mechanics (Virginia Tech, 1985), MS and BS in Mechanical Engineering (University of Akron, 1983 and 1980). Research interests include biorobotics, autonomous systems, neural control, and animal locomotion. Notable achievements include 1st place in the 2019 ION Autonomous Snow Plow Competition and the 2019 CWRU Distinguished Research Award. His lab has developed dozens of robots inspired by insects and other animals, such as the Mini-Whegs climbing robot and the MantisBot. Key grants and collaborations involve NSF-funded projects on synthetic nervous systems and neuromechanical modeling. Over 100 graduate students have graduated under his mentorship, many achieving leadership roles in academia and industry. Labs/Teams: Biologically Inspired Robotics Lab, collaborations with Professors Roy Ritzmann and Hillel Chiel (biologists).

• Microfluidics
• Nanotechnology
• Biomedical Engineering
• +۳ مورد دیگر

Jia Song is an Eberly Research Fellow and Postdoctoral Researcher at the Department of Statistics, Pennsylvania State University. Their research focuses on interdisciplinary areas at the intersection of materials science, biomedical engineering, and chemical engineering, with a strong emphasis on enzyme-driven systems, micro/nanomotors, and smart materials. Key research interests include the design and application of self-propelled micromotors, enzyme-catalyzed fluid dynamics, and hydrogel-based sensors. Their work explores topics like biomimetic collective behavior, photothermal actuation, and 4D printing for morphogenesis visualization. Recent studies have addressed collective cargo transport, light-powered propulsion systems, and surfactant-free microgel fabrication. Publications reflect a trend toward integrating biophysics and engineering principles to solve challenges in targeted drug delivery, environmental monitoring, and biointerface engineering. Their work combines experimental and theoretical approaches to understand active matter systems, microfluidic control mechanisms, and responsive material design. No scientific awards are explicitly listed. Advising and grants are not detailed in the provided text. Research activities likely involve collaborations within the Department of Statistics and affiliated labs focusing on interdisciplinary material systems.

Stefan Pulverمشاهده پروفایل

مدرس ارشد

• Neuroethology
• Neuroscience
• Locomotion
• +۱۲ مورد دیگر

Stefan Pulver is a Senior Lecturer at the School of Psychology and Neuroscience, University of St Andrews, where he leads research in the neuroethology of movement in small animals. He is affiliated with the Centre for Biophotonics, Centre for Higher Education Research, and the Institute of Behavioural and Neural Sciences. He is currently accepting postgraduate research students and supervising PhD projects in insect movement neurobiology. BA, Colby College, USA (1999) PhD, Brandeis University (2009) His research centers on understanding how insect brains control complex locomotion across varied terrains, using integrative methods spanning genetics, anatomy, electrophysiology, live imaging, biomechanics, and field behavior. He works with species such as flies, beetles, and aquatic invertebrates, with findings relevant to vertebrate neuroscience and bio-inspired robotics. His lab emphasizes sustainable and accessible science practices. The recent publications reflect a strong focus on motor control in Drosophila and Tribolium larvae, with themes including neural circuit motifs, locomotor variability, force sensing technologies, and computational modeling of neuronal memory. His work frequently combines cutting-edge optical and genetic tools to decode movement at neural and biomechanical levels. Stefan Pulver has been involved in multiple research projects funded by BBSRC and NERC, including those on neural network resilience, open-source microscopy (STRÏMM), and rapid imaging technologies. He serves as Principal Investigator and Co-Investigator on several grants, supporting students and collaborative research. He is actively engaged in teaching and academic leadership: he founded and coordinates the MRes in Neuroscience program and advises the Students Teaching Teachers Teaching Students (ST3S) initiative. He has also co-directed major training workshops such as the Neurobiology of Drosophila Summer Course at Cold Spring Harbor and the CrawFly neurophysiology workshop. His lab collaborates with external partners including BugLife Scotland and Cairn Research, and his work contributes to UN Sustainable Development Goals in areas like sustainable science and biodiversity. He has served as an editor for Scientific Reports and is a member of the Education Committee for the Faculty for Undergraduate Neuroscience.

• Polymer Chemistry
• Materials Science
• Biomaterials
• +۳ مورد دیگر

Prof. Andrij Pich is the Lichtenberg Professor for Functional and Interactive Polymers at RWTH Aachen University and holds a part-time professorship in Bio-Based Polymers at Maastricht University. His research focuses on the synthesis of stimuli-responsive polymers, nano/microgels, and their applications in catalysis, biomaterials, and coatings. He obtained his doctorate from TU Dresden in 2001, followed by postdoctoral work at the University of Toronto. Notable awards include the Lichtenberg Professorship (2009), Georg Manecke Prize (2007), and Innovation Award (2018). Education: Bachelor’s/Master’s in Chemical Technology, Lviv Polytechnic National University PhD in Chemistry, TU Dresden (2001) Postdoctoral Research, University of Toronto (2006–2007) Habilitation, TU Dresden (2008) Research Interests: Prof. Pich designs polymers inspired by biological systems, emphasizing responsive materials that adapt to stimuli like temperature or pH. His group explores applications in drug delivery, soft robotics, and sustainable materials. Recent work includes microgel-based catalysts and bio-based flame-retardant coatings. Recent Work Trends: Publications highlight advancements in microgel synthesis, interfacial catalysis, and functional biomaterials. Key themes include programmable degradation, adhesive pesticide delivery, and nanomedicine for tumor therapy. Awards & Grants: Lichtenberg Professorship (Volkswagen Foundation, 2009) Innovation Award (BioRegions Germany, 2018) Leadership in EU-funded projects like EcoGuard and Oxyfilter Lab & Collaborations: His working group at RWTH Aachen collaborates widely, with projects on smart nanomedicines, microgel-based catalysis, and sustainable agriculture. The lab includes 15+ researchers and students, driving interdisciplinary innovation in polymer science.

Ali Alazmaniمشاهده پروفایل

دانشیار

• Soft Robotics
• Healthcare Technologies
• Smart Materials
• +۱۲ مورد دیگر

Dr. Ali Alazmani is an Associate Professor of Soft Robotics at the School of Mechanical Engineering, University of Leeds. He serves as co-Director of the Healthcare Mechatronics Laboratory and leads the Soft Robotics research theme across the university. His work bridges engineering and healthcare, focusing on novel robotic systems using elastomeric materials for medical applications. His research interests lie at the intersection of soft robotics, smart materials, and healthcare technologies . He explores soft sensing and actuation, morphable soft-bodied robots, smart fabrication methods, and implantable or wearable medical devices. His designs are inspired by biological systems and aim to reduce reliance on external sensors and actuators through intrinsic material intelligence. Dr. Alazmani's current research is supported by UKRI and NIHR, with projects including soft robotic cardiac assistance, bioactuator development for cardiac disease models, soft cell stretching platforms for mechanobiology, and multi-material additive manufacturing. He also contributes to initiatives in robotic surgery and colonic disease investigation. He leads the Institute of Design, Robotics and Manufacturing research group and mentors postgraduate researchers such as Hongxin Liao. As module leader for Mechatronics and Measurement Systems (MECH2650), he emphasizes hands-on, research-led teaching with integration of cutting-edge lab demonstrations.

Kolja Kühnlenzمشاهده پروفایل

استاد

• Computer Vision
• Robotics
• Human-Robot Interaction
• +۳ مورد دیگر

Kolja Kühnlenz is a Professor of Electrical Engineering and Computer Science at Coburg University of Applied Sciences and Arts since 2014. Previously, he held roles as Senior Research Scientist, Senior Lecturer, and Director of the Dynamic Vision Research Laboratory at the Technical University of Munich (TUM) until 2012. He leads research in cognitive technology and has been a Carl von Linde Junior Fellow. His academic journey includes a Doctor of Engineering from TUM (2007) and a Bachelor's degree in Electrical Engineering from TU Berlin (2002). Research interests focus on computer vision , robotics , human-robot interaction (HRI) , and intelligent automation systems . Notable contributions include work on anthropomorphism perception, adaptive robot controllers, and proactive HRI systems. He has led projects within the Munich Cluster of Excellence CoTeSys and the Bernstein Center for Computational Neuroscience Munich. His publications emphasize motor interference effects , cognitive load impacts , and trust in autonomous systems . Key awards include the CoTeSys Junior Research Group Leadership Award and a Student Research Award from Humboldt Universität Berlin. His work spans applications in Emotion-aware robotics, Biologically inspired vision systems, Autonomous vehicle communication, Human-robot collaboration ethics. Current research trends highlight advancements in bio-inspired motion control and explainable AI for HRI .

Changhong Caoمشاهده پروفایل

استادیار

• Nanomanufacturing
• Materials Science
• Mechanics of Advanced Materials
• +۴ مورد دیگر

Changhong Cao is an Assistant Professor at McGill University, specializing in nanomanufacturing, materials science, and advanced material applications. His research focuses on developing scalable technologies for advanced materials characterization and production, including MEMS device fabrication, in-situ TEM testing, and novel printing techniques. He holds a PhD from the University of Toronto, an M.S. from Stony Brook University, and completed a postdoctoral fellowship at MIT. Research interests include mechanics of 2D/1D materials, interfacial interactions, and translating nanoscale material properties into large-scale manufacturing solutions. His work explores applications in flexible electronics, energy storage systems, and bio-hybrid devices. Key areas involve optimizing material adhesion for micro/nanotransfer printing and enhancing the mechanical properties of composite materials through innovative synthesis methods. Recent publications (2023-2025) highlight breakthroughs in transfer printing technologies, lithium/sodium battery interface design, and bio-inspired AFM probe development. His lab (Cao Research Group) emphasizes interdisciplinary approaches combining mechanical engineering, materials science, and nanotechnology. No notable awards are listed in current texts, though his contributions to nanomanufacturing are widely cited.

Gautam Reddyمشاهده پروفایل

استادیار

• Machine Learning
• Neuroscience
• Evolutionary Biology
• +۴ مورد دیگر

Gautam Reddy is an Assistant Professor of Physics at Princeton University, leading the Reddy Lab. He holds a B.Tech in Engineering Physics from the Indian Institute of Technology, Bombay, and a Ph.D. in Physics from UC San Diego. His research bridges physics, biology, and machine learning to study information processing in natural and artificial systems. He previously served as an NSF-Simons Fellow at Harvard and a research scientist at NTT Research's Physics and Informatics Labs. His work investigates how biological and artificial systems learn and solve goal-oriented tasks through the lens of physics-inspired theory. Key areas include high-dimensional learning, evolutionary epistasis, olfactory processing, and reinforcement learning. The Reddy Lab collaborates with experimental biologists and machine learning researchers to develop phenomenological models and test theoretical frameworks using computational tools. Current projects explore in-context learning in transformers, modular structure in genotype-phenotype maps, and the interplay between decision-making and information theory in biological systems. He advises two graduate students (Tsai-Chun Pan and Ravin Ramaraj) and maintains active collaborations across disciplines.

• Neural Computation
• Spatial Cognition
• Neuroscience
• +۳ مورد دیگر

Dr. Andrej Bicanski is a Research Fellow and group leader of the Neural Computation Research Group at the Max Planck Institute for Human Cognitive and Brain Sciences in Leipzig, Germany. His work focuses on computational models of spatial cognition, locomotion, and neuromechanical systems. He integrates neuroscience, robotics, and artificial intelligence to study neural mechanisms underlying spatial navigation, grid cells, and motor control. Research interests include: Neural coding of spatial orientation and navigation Computational models of head direction cells and grid cells Neuromechanical simulations of animal locomotion (e.g., salamander spinal networks) Integration of sensory feedback and central control in movement His recent articles explore topics such as adaptable locomotor patterns in salamanders, path integration in humans, and large-scale spatial cognition models. He has contributed to understanding how grid cells and place cells function in complex environments, with applications to robotics and cognitive science. No scientific awards or grants are explicitly mentioned in the provided text. He leads the Neural Computation Research Group, which develops biologically inspired computational models to bridge neural mechanisms and behavior.

Talia Mooreمشاهده پروفایل

استادیار

• Robotics
• Animal Behavior
• Biomimetic Design
• +۴ مورد دیگر

Talia Moore is an Assistant Professor in Robotics at the University of Michigan, specializing in robot-animal interactions and the ecological, evolutionary, and control aspects of arrhythmic motion in animals and robots. Her research bridges robotics engineering with biological studies to create bio-inspired robots for ecological and evolutionary hypothesis testing. She leads the EMBiR lab, which focuses on designing robots to explore how traits influence survival in natural environments. Key research areas include modular robotics, biomimetic design, and the biomechanics of animal locomotion. Dr. Moore has pioneered studies on tail functions in mammals and robots, as well as the application of machine vision for behavioral analysis in animals like jerboas. Her work integrates computational modeling (e.g., ArborSim for musculoskeletal systems) with experimental robotics to address challenges in dynamic environments. Recent projects include developing the Robot of Theseus modular platform and exploring predator-prey dynamics through robotic mimicry. Her scientific accolades include the Robotics Faculty Award. She actively mentors undergraduate and graduate students in robotics and biomechanics through independent research opportunities. Collaborative efforts in open-source tools for natural history research and virtual expeditions aim to broaden student participation in ecological studies. Dr. Moore’s lab emphasizes interdisciplinary approaches, blending biomechanics, material science, and computer vision to advance robotics while deepening biological understanding. Current focuses include tail-assisted control mechanisms, soft robotics actuators (e.g., HASEL), and the evolutionary drivers of morphological adaptations in desert rodents and snakes.

Cloud Coppolaمشاهده پروفایل

پژوهشگر

• Robotics
• Biomimetics
• Fish Behavior Analysis
• +۳ مورد دیگر

Cloud Coppola is a Researcher in the Department of Computer Science at Aberystwyth University. His work focuses on bio-inspired robotics, with a particular emphasis on developing robot controllers based on fish behavior and movement analysis. He has contributed to interdisciplinary research spanning robotics, biomimetics, and control systems. Key research interests include fish trajectory analysis, bio-inspired algorithms, and autonomous navigation systems. His recent publications (2022-2023) explore applications of robotic systems modeled after biological systems, emphasizing practical implementations in unconstrained environments. He completed a Master of Philosophy (MPhil) thesis titled "Towards developing a fish-inspired robot controller" under the supervision of Prof. O. Akanyeti, Dr. F. Labrosse, and Dr. P. Shaw. His research has been presented at conferences like UKRAS22 and published in journals like Biomimetics . No scientific awards or grants are explicitly mentioned in the provided text.