Eero P Simoncelli is a Silver Professor at New York University, holding appointments in the Department of Neural Science, Mathematics, Data Science, and Psychology within the College of Arts & Science. He is affiliated with the Howard Hughes Medical Center and leads a research lab focusing on computational neuroscience and visual/auditory perception. Simoncelli earned his Ph.D. in 1993 from MIT. His research integrates statistical signal processing with neurobiological insights to understand sensory systems. Education: Ph.D. 1993, Massachusetts Institute of Technology. Research interests include computational modeling of visual and auditory perception, statistical image/signal processing, and neural coding mechanisms. His work bridges machine learning, neuroscience, and applied mathematics, with recent focus on motion detection, neural population coding, and hierarchical cortical models. Notable projects involve mapping spatial frequency selectivity in human visual cortex and developing biologically inspired AI architectures. Publications span topics like motion perception, neural circuit dynamics, and generative models for video prediction. His lab's work emphasizes practical applications in neuroscience and AI through tools like the Plenoptic stimulus synthesis platform. Simoncelli collaborates across disciplines to advance neuroAI integration and deep learning theory grounded in biological principles.
جستوجوی استاد و پژوهشگر
استاد راهنما، استاد دانشگاه یا پژوهشگر مناسب برای مسیر پژوهشیتان را پیدا کنید و با او ارتباط بگیرید.
نمایش ۷۲۱-۷۳۵ از ۹۹۹ استاد راهنما
اطلاعات این پروفایلها از صفحات عمومی دانشگاهها جمعآوری شده و ممکن است بهروز نباشد.
Herbert Jaeger is a Professor of Computing in Cognitive Materials at the University of Groningen's Faculty of Science and Engineering, within the Artificial Intelligence department at the Bernoulli Institute. He holds editorial roles, including membership on the Neural Networks journal's editorial board and serving as Secretary General of the Interdisciplinary College. His expertise spans machine learning, dynamical systems modeling, neuromorphic computing, and reservoir computing. Education: PhD in Computer Science (Artificial Intelligence), University of Bielefeld Studies in Mathematics and Psychology, University of Freiburg Research Interests: His work focuses on theoretical and applied aspects of computing across disciplines, including unconventional computing models, neuromorphic systems, and reservoir computing. He explores how physical substrates and dynamical systems can advance computational paradigms, with applications in signal processing and robotics. Publications: Recent work emphasizes formal theories for physics-based computing, timescales in neuromorphic systems, and interdisciplinary computing landscapes. These studies highlight novel approaches to hardware-software integration and cross-disciplinary innovations. Projects & Grants: Leads research through the MINDS group, focusing on funded projects in cognitive materials and computing. Collaborates on initiatives like the AMARSi project, exploring modular architectures for rich motor skills in robotics. Labs/Teams: Active within the Bernoulli Institute and the Artificial Intelligence group, fostering interdisciplinary collaborations in cognitive science and engineering.
Patrick Onck is a Full Professor of Micromechanics at the Zernike Institute for Advanced Materials, University of Groningen. His research focuses on understanding the mechanical and functional behavior of biological materials using computational techniques like molecular dynamics and finite element modeling. He leads a team studying transport through the nuclear pore complex, protein phase separation in neurodegenerative diseases, and bio-inspired soft robotics. Onck holds a PhD in Applied Mechanics from Delft University of Technology (1998) and completed postdoctoral research at Harvard University. He has held positions at TU Delft and the University of Groningen since 2001, advancing to Full Professor in 2012. His work bridges atomistic and macroscopic scales, with applications in medicine and materials science. Key research areas include: Biophysical mechanisms of cellular transport Mechanics of disordered proteins in ALS and Huntington’s disease Magneto-responsive soft materials for microfluidics and robotics His recent articles explore magnetic soft robotics, artificial cilia, and nuclear pore dynamics. He serves on editorial boards of Extreme Mechanics Letters and International Journal of Molecular Sciences , and is an active member of IUTAM. Awards include KNAW Research Fellowships (1998–2000 and 2001–2002). Labs/Groups: Onck Research Group at the Zernike Institute focuses on multiscale modeling and bio-inspired design. Collaborations include the UMCG in Groningen for neurodegenerative disease studies.
Roel Verstappen is a Professor in the Department of Computational and Numerical Mathematics at the University of Groningen's Faculty of Science and Engineering. His expertise spans Scientific Computing and Computational Fluid Dynamics, with a focus on turbulence simulation, large-eddy simulation (LES), and multiphase flows. He actively contributes to advancing numerical methods and models that preserve physical symmetries and conservation laws. Research Interests: His work centers on developing low-dissipation simulation techniques, regularization modeling, and symmetry-preserving discretization for complex fluid dynamics problems. Key areas include turbulent flow analysis, multiphase flow dynamics, and applications in robotics and renewable energy systems. He has pioneered methods to ensure energy and momentum conservation in computational models and explored bio-inspired designs for soft robotic swimmers. Articles Trends: Recent publications highlight innovations in LES for multiphase flows, fluid-structure interaction in biological systems, and robotics. He has also investigated uncertainty quantification in wind-farm simulations and collaborated on projects involving magnetic actuation and natural convection flows. These works reflect a blend of theoretical advancements and practical engineering applications. Advising & Grants: He supervises graduate research in computational fluid dynamics and numerical methods but no specific student names are listed. His funding sources and grants are not explicitly mentioned in the provided texts. Labs/Teams: Verstappen is affiliated with the Bernoulli Institute, which focuses on interdisciplinary research in mathematics, computer science, and engineering. His collaborations include researchers from institutions like TU Eindhoven and the University of Zaragoza, addressing challenges in maritime engineering, soft robotics, and sustainable energy systems.
Michael Manganمشاهده پروفایل
مدرس ارشد
- Machine Learning
- Robotics
- Biorobotics
- +۵ مورد دیگر
Dr. Michael Mangan is a Senior Lecturer in Machine Learning and Robotics at the University of Sheffield's School of Computer Science, and Operations Director of Sheffield Robotics. He holds an MEng in Avionics from the University of Glasgow (2004), an MSc in Neuroinformatics from the University of Edinburgh (2006), and a PhD in Biorobotics (2011). His research focuses on understanding insect navigation and applying these insights to robotics, emphasizing bio-inspired systems for autonomous navigation and smart agriculture. Research interests include modeling insect vision, navigation strategies, and neural mechanisms, with applications to robotics and pest control. Mangan leads the ManganLab, exploring how simple nervous systems enable complex behaviors through computational and robotic models. His work integrates biology, computer science, and engineering to develop robust autonomous systems. Key contributions include tools like CompoundRay for simulating compound eyes and I2Bot for multi-modal insect navigation simulations. He has secured grants such as ActiveAI (£953k) and SkyEye (£25k), focusing on AI transparency, neuromorphic control, and vision-based localization. Professional memberships include the Machine Learning research group and involvement in Living Machines conferences. Current projects explore fruit detection in agriculture, neuromorphic sequence learning, and animal tracking in natural environments.
Professor James Marshall is a faculty member at the University of Sheffield's School of Computer Science, holding the title of Professor of Theoretical and Computational Biology. He leads the Behaviour, Evolution, Theory (BET) Lab and directs the Centre for Machine Intelligence. His research focuses on interdisciplinary studies of collective behavior in social insects, decision theory, and robotics, aiming to bridge biology and engineering. Education and Roles: PhD in Theoretical and Computational Biology Director of the Centre for Machine Intelligence Principal Investigator on grants including EPSRC's Brains on Board and DiODe Research Interests: Collective social insect behavior, evolution of social behavior, robotics applications, decision-making algorithms, and swarm intelligence. His work combines mathematical modeling, computational simulations, and experimental studies with robotics. Grants and Collaborations: ActiveAI (EPSRC): Focuses on robust AI systems Swarm Awareness (ONRG): Enhances swarm state awareness Green Brain Project: Models honeybee brain functions Labs and Teams: The BET Lab, part of the Department of Computer Science, explores interdisciplinary approaches to behavioral mechanisms. Collaborations include Opteran Technologies, a spin-off applying natural intelligence to autonomy.
- Computer Vision
- Robotics
- Cognitive Systems
- +۴ مورد دیگر
Prof. José Santos-Victor is a Full Professor at the Department of Electrical & Computer Engineering, Instituto Superior Técnico, Universidade de Lisboa. He leads the RBCog-Lab research infrastructure and coordinates the international PhD Program RBCog - Robotics, Brain and Cognition. His research focuses on biologically-inspired cognitive vision and humanoid robotics, addressing topics like vision-based navigation, human-robot interaction, and assistive robotics for autism therapy. Education: Ph.D. in Electrical & Computer Engineering, Instituto Superior Técnico (1995) M.Sc. in Electrical & Computer Engineering, Instituto Superior Técnico (1991) Licenciatura in Electrical & Computer Engineering, Instituto Superior Técnico (1988) Research Interests: Computer Vision, Robotics, Humanoid Systems, Biologically-Inspired Algorithms, and Assistive Technologies. Awards: IEEE Fellow (2015) for contributions to biologically-inspired cognitive vision ELLIS Fellow (2021) Correspondent Member of the Academy of Sciences of Lisbon Leadership Roles: President of ISR-Lisboa (2015-2022) Chair, Department of Electrical & Computer Engineering, IST (2021-24) Coordinator of LARSyS and Associated Laboratory Grants & Labs: Leads the RBCog-Lab, part of Portugal's Research Infrastructure Roadmap, and oversees projects like the Copyrobot therapy platform for ASD children.
Dr. Alper Bozkurt is the McPherson Family Distinguished Professor in Engineering Entrepreneurship at NC State University's Department of Electrical and Computer Engineering. He also serves as Co-Director of the NSF-funded ASSIST Center and IConS Institute, leading interdisciplinary research in bionic microsystems. His work integrates bioMEMS, microelectronics, and robotics to create interfaces with biological organisms, including insects, plants, and humans. Bozkurt holds a Ph.D. from Cornell University and master's from Drexel University. His research focuses on implantable biomedical devices, biosensors, and cyber-physical systems. Notable projects include wearable health monitors for stress, asthma, and Alzheimer’s diagnosis, and biohybrid systems like cyborg insects and plant stress sensors. His team’s innovations have spun off six companies and earned global recognition, including Popular Science’s “Brilliant 10” (2015) and NSF CAREER Award (2016). Recent grants include a $4.3M NSF Convergence Accelerator project to develop locust-inspired olfactory robots. Awards: William F. Lane Teaching Award (2014), Chancellor’s Innovation Fund (multiple years), and IBM Faculty Awards. He consults for Disney’s G-Force and collaborates with the White House Smart America Challenge. Labs: iBionicS Lab explores neural interfaces, biophotonics, and biohybrid systems. Current efforts target wearable tech for ecosystem management and medical diagnostics.
- Machine Learning
- AI
- Cyber-Physical Systems
- +۶ مورد دیگر
Edgar Lobaton is a Professor in the Department of Electrical and Computer Engineering at North Carolina State University (NC State). He holds a B.S. in Mathematics and Electrical Engineering from Seattle University (2004) and a Ph.D. in Electrical Engineering and Computer Sciences from UC Berkeley (2009). His research integrates AI, probabilistic modeling, and cyber-physical systems for applications in wearable health monitoring, rehabilitation robotics, agriculture, and biological imaging. He has led projects at Alcatel-Lucent Bell Labs and the University of North Carolina at Chapel Hill. Lobaton is an IEEE Senior Member and advisor to the Embedded Machine Learning Club. Key awards include the NSF CAREER Award (2016), William F. Lane Outstanding Teaching Award (2023), and University Faculty Scholars Award (2024). His work spans grants focused on wearable sensors for asthma monitoring, plant health diagnostics, and automated microscopy systems. He emphasizes interdisciplinary collaboration, with projects involving robotics, environmental sensing, and medical devices. Professional involvement includes leadership roles in IEEE and SACNAS, reflecting his commitment to diversity in STEM. His lab develops innovative solutions for precision agriculture, wearable health systems, and bio-inspired robotics, with a focus on translating research into practical applications for healthcare and environmental sustainability.
Lilian Hsiaoمشاهده پروفایل
دانشیار
Lilian Hsiao is an Associate Professor & University Faculty Scholar at North Carolina State University's Department of Chemical and Biomolecular Engineering within the College of Engineering. Her research focuses on biomimetic materials, complex fluids, and soft matter, particularly exploring colloidal hydrodynamics and their biomedical applications such as cartilage mechanics and elastohydrodynamic lubrication. She leads a lab of ~12 students and collaborates with Duke and UNC-Chapel Hill researchers. Education: B.S., Chemical Engineering, University of Wisconsin-Madison (2008) Ph.D., Chemical Engineering, University of Michigan (2014) Research Interests: Her work bridges fundamental science and industrial applications, using microscopy and rheology to study materials like shaped colloids and functionalized polymers. Recent projects include developing biodegradable electronics, analyzing colloidal gel elasticity, and investigating surface oxides in liquid metals. Her interdisciplinary approach integrates materials science, physics, and mechanical engineering. Awards: 2019 Marion Milligan Mason Award for Women in the Chemical Sciences Lab & Collaborations: The Hsiao Lab focuses on creating novel soft materials with directional properties inspired by biological systems. They emphasize practical applications in healthcare, robotics, and sustainable electronics. Her CAREER grant (2021) supports elastohydrodynamic lubrication research on soft-patterned interfaces.
Dan Charbonneauمشاهده پروفایل
استادیار
Dan Charbonneau is an Assistant Professor of Practice in the College of Information Science at the University of Arizona, specializing in behavioral ecology and data science. His research focuses on social insect behavior, biostatistics, and applying data engineering methods to biological questions. He holds a PhD in Entomology from the University of Arizona and has prior postdoctoral experience at Arizona State University and the University of Pennsylvania. Education: PhD in Entomology, University of Arizona His research explores how decentralized systems like ant colonies allocate tasks, particularly examining 'inactive' workers and their roles in colony efficiency. He develops tools like ABCTracker to analyze collective behavior patterns, integrating biostatistics and computer vision. Research Trends: His articles consistently investigate task allocation mechanisms in social insects, emphasizing spatial interactions, aging effects, and bio-inspired technology applications. Key themes include colony resilience, sensor networks, and modeling collective behavior. Grants & Advising: His work bridges ecological studies with data science, though specific grants or advised students are not detailed here. He contributes to the Environmental, Health and Biological Sciences program within the College of Information Science. Labs/Teams: Engages in collaborative projects applying data engineering to biological systems, though specific lab affiliations are unspecified.
Angeles Sallesمشاهده پروفایل
استادیار
Angeles Salles is an Assistant Professor in Biological Sciences at UIC's College of Liberal Arts and Sciences, directing research on auditory neuroethology using bat models. Her lab investigates neural mechanisms of complex sound processing through electrophysiological and behavioral approaches. Research explores: Auditory processing hierarchies in mammalian brains Neurobiological basis of social behaviors Vocal learning mechanisms in echolocating species Publications demonstrate consistent focus on acoustic signal processing across behavioral contexts, with recent emphasis on computational neuroethology and biomimetic applications. Fieldwork complements laboratory studies examining bat communication in natural habitats.
William Shih is a Professor at Harvard Medical School and the Dana-Farber Cancer Institute, and Founding Core Faculty at the Wyss Institute for Biologically Inspired Engineering. His research focuses on DNA nanotechnology, molecular robotics, and their biomedical applications. He pioneers DNA origami and hierarchical self-assembly methods to create nanostructures for drug delivery, bioimaging, and molecular manufacturing. His work includes programmable DNA devices capable of shape-shifting and mechanical actuation, with applications in diagnostics and therapeutics. Shih's lab develops tools like DNA nanoswitch calipers for single-molecule proteomics and DNA-corralled nanodiscs for membrane protein analysis. He collaborates widely, including with groups at BCH, BWH, and HMS. Recognitions include awards from NIH, Blavatnik Institute, and Foresight Institute. He leads the Shih Laboratories at both Dana-Farber and Wyss Institute, advancing programmable biomaterials and nanotechnology-based solutions for healthcare challenges.
- Photochromic Materials
- Polymer Chemistry
- Catalysis
- +۴ مورد دیگر
Javier Read de Alaniz is a Professor of Chemistry & Biochemistry and Associate Director of the California NanoSystems Institute (CNSI) at the University of California, Santa Barbara (UCSB). He holds a B.S. from Fort Lewis College (1999) and a Ph.D. from Colorado State University (2006), followed by postdoctoral research with Larry Overman at UC Irvine. His research focuses on synthetic chemistry, functional materials, and stimuli-responsive polymers, with interdisciplinary applications in soft robotics, 3D printing, and photopolymerization. Affiliations: UCSB Department of Chemistry & Biochemistry, CNSI Education: B.S., Fort Lewis College (1999) Ph.D., Colorado State University (2006) Postdoc, UC Irvine (2006–2009) Research interests include cascade rearrangements, photochromic materials, and high-strain-rate sensors. His lab develops light-responsive polymers, functional soft materials, and biomaterials with adaptive properties. Notable contributions include tunable degradable polymers, dynamic covalent networks, and photoactivatable liquid crystal elastomers. Recent work highlights include scalable synthesis of degradable copolymers, self-healing materials, and photothermal actuators. Collaborations span polymer physics, bioengineering, and materials science. Lab members include graduate students and postdocs working on projects like dynamic hydrogels, azobenzene-functionalized networks, and bio-inspired materials. Javier has advised over 15 graduate students, many now in academic and industry roles.
Yoonsuck Choe is a Professor in the Department of Computer Science and Engineering at Texas A&M University and Director of the Brain Networks Laboratory. He has held roles including Corporate Vice President at Samsung Research (2017–2019) and served as a Fellow in the College of Engineering. His expertise spans computational neuroscience, brain imaging, neuroevolution, and deep learning, with a focus on temporal brain dynamics, sensorimotor learning, and AI-driven neuroimaging analysis. Education : Ph.D. (2001), M.A. (1995) from University of Texas at Austin; B.S. (1993) from Yonsei University. His research interests include predictive neural dynamics, consciousness, thalamocortical function, and biologically inspired AI systems. Recent publications emphasize energy-efficient neural networks, tool-use evolution, and connectomics. He has received awards for teaching excellence and research innovation, including the 30th Anniversary Distinguished Alumni Award from Yonsei University (2013). Advising and grants: Prof. Choe has guided over 20 students in their theses and dissertations, focusing on topics like motor learning, neural integration, and medical imaging. His Samsung tenure involved AI core team leadership and high-throughput brain dynamics automation. Grants include work on KESM brain atlas development and neurovascular modeling. Lab and teams: Directs the Brain Networks Lab (Choe Lab) at Texas A&M, exploring brain networks, predictive systems, and AI applications. Collaborates with interdisciplinary teams in neuroscience and biomedical engineering.
فقط ۷۵۰ نتیجه اول نمایش داده میشود. برای رسیدن به نتایج دقیقتر، جستوجو را با فیلترها محدودتر کنید.