جستجوی استاد راهنمای دانشگاهی

Arash Aramiمشاهده پروفایل

دانشیار

• Assistive Robotics
• Human-Robot Interaction
• Machine Learning
• +۶ مورد دیگر

Arash Arami is an Associate Professor in the Department of Mechanical and Mechatronics Engineering at the University of Waterloo, cross-appointed in Systems Design Engineering. He directs the Neuromechanics and Assistive Robotics Laboratory and maintains affiliations with Waterloo Robohub, the Centre for Bioengineering and Biotechnology, Waterloo AI institute, and KITE institute at Toronto Rehab Institute. He earned his Doctorate in Electrical Engineering from EPFL (2014), Master of Science from University of Tehran (2009), and Bachelor of Science from University of Tabriz (2006), all in Control Engineering. His research in Assistive Robotics and Rehabilitation Engineering integrates Machine Learning with Neuromechanics to develop intelligent systems for human movement analysis. Key focus areas include exoskeleton control algorithms, wearable sensor systems, and neural control modeling for rehabilitation applications. Recent publications demonstrate interdisciplinary work spanning robotics, biomedical engineering, and materials science, with emphasis on real-time human locomotion prediction, exoskeleton-human interaction, and data-driven health monitoring solutions. Dr. Arami serves as Chair of the NSERC Scholarship Committee (2021-2023) and mentors graduate students through the Mechatronics Exchange Study program. His teaching includes core courses in control systems, robot manipulators, and biomechanical engineering. The Neuromechanics and Assistive Robotics Laboratory fosters collaborations with clinical partners at Toronto Rehab Institute, focusing on translating robotic innovations into practical rehabilitation tools through interdisciplinary teamwork.

Leia Stirlingمشاهده پروفایل

دانشیار

• Robotics
• Biomechanics
• Human Factors
• +۵ مورد دیگر

Leia Stirling is an Associate Professor in Robotics and Industrial Operations Engineering at the University of Michigan, serving as Associate Chair of Undergraduate Studies in Robotics. She is Core Faculty at the Center for Ergonomics and Affiliate Faculty at the Space Institute. Her research focuses on human-system interactions in robotics, biomechanics, and decision support systems. Key areas include wearable motion sensing for decision-making, co-adaptive exoskeleton algorithms, and space mission operations tools. Her group blends human factors, biomechanics, and robotics to design technology that enhances human performance in complex tasks. She leads the Stirling Group, which develops metrics for injury risk assessment, exoskeleton usability, and space crew readiness evaluation. Her lab’s work has applications in industrial safety, healthcare rehabilitation, and astronaut training. Research Thrusts: Wearable Motion Sensing: Creates metrics for musculoskeletal injury risk, balance rehabilitation, and quantitative assessment of agility/coordination. Exoskeleton Usability: Develops co-adaptive control algorithms and studies trust dynamics between users and wearable robots. Space Operations: Designs tools for astronaut readiness, human-aware robotics, and extravehicular activity planning. Recent work includes studies on neonatal ventilation systems, space inspection trajectory optimization, and augmented reality for sensorimotor assessments. She teaches robotics courses including ROB 204: Introduction to Human-Robot Systems. Her work has been featured at IROS 2023 and NASA-related initiatives. Lab Website: stirlinglab.org

Shuran Songمشاهده پروفایل

استادیار

• Computer Vision
• Robotics
• Robot Learning
• +۴ مورد دیگر

Shuran Song is an Assistant Professor of Electrical Engineering at Stanford University, with a courtesy appointment in Computer Science. Previously, she was faculty at Columbia University. She holds a Ph.D. in Computer Science from Princeton University and a BEng from HKUST. Her research focuses on the intersection of computer vision and robotics, particularly in embodied AI, robot manipulation, and sensorimotor learning. Song's work emphasizes learning from physical interactions to enable robots to perform complex tasks autonomously. She leads the Robotics and Embodied AI Lab (REAL@Stanford) and has received prestigious awards, including the NSF Career Award, Sloan Fellowship, and Microsoft Faculty Fellowship. Education: Ph.D., Computer Science, Princeton University; BEng, HKUST Affiliations: Stanford School of Engineering, Department of Electrical Engineering Research interests include deformable object manipulation, visuomotor policy learning, and generalizable robot skills. Her lab develops algorithms for robots to learn through interaction, with applications in household assistance (e.g., TidyBot) and industrial automation. Notable contributions include the TossingBot and Diffusion Policy frameworks. Publications span robotics, computer vision, and AI conferences (RSS, ICRA, CVPR), focusing on policy learning, deformable object handling, and embodied intelligence. Awards highlight her impact in advancing robot learning and perception. Advises doctoral and master's students in robotics and AI, and collaborates on grants from NSF, DoD, and industry partners. Teaches courses on robot perception and embodied AI at Stanford.

Stéphanie P. Lacourمشاهده پروفایل

استاد

• Bioelectronics
• Neuroprosthetics
• Soft Electronics
• +۹ مورد دیگر

Stéphanie P. Lacour is a Full Professor at the School of Engineering, École Polytechnique Fédérale de Lausanne (EPFL), where she holds the Foundation Bertarelli Chair in Neuroprosthetic Technology. She leads the Laboratory of Soft Bioelectronic Interfaces (LSBI) and is affiliated with multiple departments including INX-STI, STI-SMT, SV-SSV, and AVP-DLE-EDOC. Since 2025, she has served as EPFL’s Vice-President for Support to Strategic Initiatives, overseeing institutional research strategy. Her research is centered at Campus Biotech in Geneva, where she was the founding director of the Neuro-X Institute. PhD in Electrical Engineering, INSA Lyon, France (1998–2001) Postdoctoral Research, Princeton University and University of Cambridge Joined EPFL in 2011 Her research focuses on soft bioelectronic interfaces that seamlessly integrate with biological tissues. She pioneers the development of stretchable, compliant electronics for implantable and wearable applications, using techniques from MEMS and microelectronics adapted to elastomeric substrates. Her work enables long-term, minimally invasive neural interfacing for applications in neuroprosthetics, rehabilitation, and health monitoring. Key innovations include soft electrocorticography arrays, liquid metal sensors, and encapsulation methods for chronic implants. Her recent publications span high-impact journals such as Nature , Science Robotics , Advanced Materials , and Nature Nanotechnology , covering topics like neural stimulation, soft robotics, wireless implants, and hydrogel-based interfaces . The work demonstrates a strong trend toward multimodal, closed-loop, and translational neurotechnologies with real-world clinical potential. Scientific Awards: No scientific awards explicitly mentioned in the provided text. She advises a large cohort of PhD students and postdoctoral researchers, many of whom have completed their theses under her supervision. Her team has received funding for projects in neural interfacing, bioelectronics, and soft robotics. She is actively involved in teaching courses such as Soft Microsystems Processing and Devices and Neural Interfaces . Lacour leads the Laboratory of Soft Bioelectronic Interfaces (LSBI) , a multidisciplinary research team focused on the fabrication, characterization, and in vivo evaluation of soft bioelectronic systems. The lab collaborates extensively across EPFL and with clinical partners to translate technologies from bench to bedside.

Gunnar Blohmمشاهده پروفایل

استادیار

• Sensorimotor Neuroscience
• Clinical Medicine
• Neurology
• +۳ مورد دیگر

Gunnar Blohm is an Assistant Professor in the Department of Biomedical and Molecular Sciences at Queen's University, affiliated with the School of Medicine and Faculty of Health Sciences. His research focuses on sensorimotor neuroscience, particularly 3D sensorimotor control, eye-hand coordination, and computational modeling of neural processes. He holds a Ph.D. from Université Catholique de Louvain and has held postdoctoral positions at York University and his alma mater. Cross-appointed to the School of Computing, Department of Psychology, and Department of Mathematics and Statistics, he is also Vice-Director of the Connected Minds initiative. His research integrates behavioral experiments, brain imaging (MEG/EEG), and patient studies to understand how sensory information is transformed into goal-directed actions. Key areas include visuomotor transformations, multisensory integration, and Bayesian processes in neural computations. Blohm leads the Computational Sensorimotor Neuroscience Lab, emphasizing collaborative projects like Neuromatch Academy and contributions to open science initiatives. Affiliated with Queen's Centre for Neuroscience Studies and Ingenuity Labs, his work bridges computational approaches with clinical applications, aiming to develop frameworks for understanding brain dysfunction and clinical tools. His recent articles explore topics like saccade dynamics, pupil responses, and generative adversarial collaborations in scientific discourse.

Timothy H. Murphyمشاهده پروفایل

استاد

• Neuroscience
• Stroke Recovery
• Brain Circuit Mapping
• +۵ مورد دیگر

Dr. Timothy H. Murphy is a Professor in the Department of Psychiatry at the University of British Columbia's Faculty of Medicine. He is also an Associate Member of the School for Biomedical Engineering and a Member of the Djavad Mowafaghian Centre for Brain Health. Dr. Murphy leads the Dynamic Brain Circuits in Health and Disease initiative and the Division of Neuroscience and Translational Psychiatry at UBC. Dr. Murphy received his Ph.D. from Johns Hopkins University in 1989 and his B.Sc. from Saint Mary's College Maryland in 1984. His research focuses on understanding brain circuit structure-function relationships in relation to stroke recovery, psychiatric disorders, and neurological diseases. He specializes in mesoscale imaging techniques to study cortical activity patterns and develop automated approaches for brain imaging and stimulation. His laboratory develops innovative tools including open-source hardware for automated mouse brain imaging, synthetic data generation for behavioral analysis, and chronic recording systems that enable simultaneous mesoscale cortical imaging with subcortical or peripheral nerve activity monitoring. Research from the Murphy Lab has significantly advanced our understanding of how brain circuits reorganize after stroke and in models of psychiatric disorders. Dr. Murphy's recent publications reveal trends in mesoscale cortical imaging, development of synthetic data for behavioral analysis, and exploration of circuit-level changes in neurological and psychiatric disease models. His work bridges basic neuroscience with potential clinical applications for stroke recovery and mental health treatments. Dr. Murphy has mentored numerous students and postdoctoral fellows who have gone on to successful careers in neuroscience and related fields. His laboratory has received funding to support innovative approaches to understanding brain circuit function and recovery mechanisms. The Murphy Lab maintains strong collaborative ties across UBC and develops open-source tools that are widely adopted by the neuroscience community. Their work on automated home-cage imaging systems, synthetic behavioral data generation, and chronic recording technologies represents significant methodological advances in the field.

Fulvio Dominiمشاهده پروفایل

استاد

• 3D Vision
• Perception and Action
• Visual Neuroscience
• +۳ مورد دیگر

Fulvio Domini is a Professor in the Department of Cognitive, Linguistic and Psychological Sciences at Brown University. He joined Brown in 1999 after completing his MSc in Electrical Engineering and PhD in Experimental Psychology at the University of Trieste, Italy. His research focuses on how the human visual system processes 3D information to enable interaction with the environment, combining computational modeling with behavioral experiments. Key areas include perception-action coupling, depth cue integration, and visuomotor adaptation. Education: Masters in Electrical Engineering, University of Trieste, Italy PhD in Experimental Psychology, University of Trieste, Italy Research Interests: 3D vision and depth perception Integration of stereo and motion cues Perception-action link in grasping movements Computational modeling of visual processing Funded Research: Multiple NSF grants including BCS #1827550 ($523,550, 2018) Investigates temporal integration of visual cues and affine shape representations Teaching: Courses include Computational Vision, Perception, and immersive reality simulations. Recent courses: CLPS 1591 (Vision for Action/Perception), CLPS 0540 (Simulating Reality). Lab: Active research on visuomotor control and perception mechanisms, with a focus on dynamic environments and adaptive systems.

• Cellular Neuroscience
• Systems Neuroscience
• Behavioral Neuroscience
• +۳ مورد دیگر

Prof. Laura Busse is a Professor at Ludwig Maximilian University of Munich (LMU), leading the Research Group in the Department of Biology II, Division Neurobiology. She holds roles as a Regular Member of MCN, Full Member of GSN, and Deputy Head of the GSN Examination Board. Her research focuses on cellular and systems neuroscience, particularly investigating how contextual information influences visual perception through neural circuits in mice. Key areas include feedback mechanisms, behavioral state effects, and thalamocortical interactions. Her work employs advanced techniques like high-density extracellular recordings and optogenetics to study active behavior in rodents. Current students include Simon Renner, Gregory Born, and others. Recent research highlights include studies on corticothalamic feedback effects, thalamic spatial integration, and the role of pupil dynamics in neural activity. She leads the Vision Circuits Lab (https://visioncircuitslab.org), exploring how sensory inputs and brain states shape visual processing. Her articles reveal trends in understanding thalamocortical communication, adaptive sensory systems, and the biological basis of neural network models. She coordinates the SPP2411 project on cortico-subcortical loops, emphasizing interdisciplinary neuroscience.

Shinsuke Shimojoمشاهده پروفایل

استاد

• Neuroscience
• Psychophysics
• Cognitive Science
• +۴ مورد دیگر

Shinsuke Shimojo is the Gertrude Baltimore Professor of Experimental Psychology at the California Institute of Technology (Caltech). He holds a B.A. (1978), M.A. (1980) from the University of Tokyo, and a Ph.D. (1985) from MIT. At Caltech, he has served as Associate Professor (1997–98), Professor (1999–2010), and Baltimore Professor (2010–present). His research focuses on perceptual decision-making, implicit cognition, and the neural mechanisms underlying sensory perception and social interaction. His work employs advanced methods like fMRI, EEG, and transcranial stimulation to study topics such as crossmodal integration, visual illusions, and the social brain. Shimojo leads the Shimojo Psychophysics Laboratory, collaborating with institutions like NTT Communication Science Laboratories, Harvard MGH, and MetaModal Inc. His lab investigates phenomena like sensory substitution, team flow dynamics, and human magnetoreception. Notable achievements include pioneering studies on the 'gaze cascade effect' and developing the ePlegona game system for studying team flow. Awards include the Red Dot Design Concept Award (2024) and grants from JST CREST and MEXT gCOE programs. His research bridges cognitive and neuroscience disciplines, emphasizing interdisciplinary approaches to understanding human perception and decision-making. Current projects explore implicit brain functions, social communication, and the neural correlates of emotional decisions. Shimojo also contributes to science communication through his column in Asahi Shimbun and public outreach via YouTube demonstrations of visual illusions.

Constantin A. Rothkopfمشاهده پروفایل

استاد

• Perception and Action
• Computational Neuroscience
• Machine Learning
• +۳ مورد دیگر

Prof. Constantin A. Rothkopf is a W3 Professor at the Department of Psychology, Technische Universität Darmstadt, and a secondary member of the Department of Computer Science. He serves as Founding Director of the Centre for Cognitive Science and founding member of the Hessisches Zentrum für Künstliche Intelligenz (hessian.ai). He is also part of the European Laboratory for Learning and Intelligent Systems (ELLIS) and the DAAD Konrad Zuse Schools of Excellence in Artificial Intelligence (ELIZA). His research focuses on the interplay between perception and action, using computational models and experimental studies in humans. Current work includes eye-tracking studies in naturalistic environments, inverse optimal control models, and developing algorithms for virtual agents. Education: Ph.D. in Neuroscience and Informatics from the University of Rochester, followed by postdoctoral research at Frankfurt Institute for Advanced Studies (FIAS). He has held visiting professorships at Central European University (2017) and Columbia University (2023). Awards include an ERC Consolidator Grant (2022) and SCENE Project Funding (2025). Research Interests: Active vision, decision-making under uncertainty, sensorimotor control, and computational modeling. Key themes include how humans use sensory input to form beliefs, make decisions, and act in dynamic environments. Grants/Awards: ERC Consolidator Grant (2022), SCENE Funding (2025) Labs/Teams: Centre for Cognitive Science, hessian.ai, ELLIS Unit Darmstadt

• Neuroscience
• Cortical Circuits
• Sensory Processing
• +۴ مورد دیگر

Anne-Marie Oswald is an Associate Professor in the Department of Neurobiology within the Biological Sciences Division at the University of Chicago. Her research profile indicates active engagement in neuroscience research with a particular focus on cortical circuits, neural coding, and sensory processing systems. She maintains an active research program with publications spanning from 2011 to the present. Dr. Oswald's research interests span multiple areas of neuroscience, with particular emphasis on cortical circuit function, neural coding mechanisms, and sensory processing. Her work investigates how inhibitory interneurons shape cortical dynamics, how neural assemblies form during learning, and how sensory information is processed across different brain regions. Notably, she has also contributed to discussions on diversity in science through her publication "Curating more diverse scientific conferences" in Nature Reviews Neuroscience (2020). Her research employs a combination of electrophysiological, computational, and behavioral approaches to understand neural circuit function. Analysis of her publication record reveals a strong focus on cortical circuit mechanisms, particularly in the olfactory system. Her work demonstrates expertise in understanding how different interneuron subtypes (particularly parvalbumin and somatostatin-positive cells) regulate cortical dynamics, assembly formation, and sensory processing. Over time, her research has evolved from examining basic circuit mechanisms to investigating how these circuits support complex cognitive functions like odor discrimination and associative learning. The consistent presence of computational and systems neuroscience approaches throughout her publication history indicates a rigorous quantitative approach to understanding neural function. Dr. Oswald appears to be actively mentoring students and postdoctoral researchers, as evidenced by her consistent publication record with multiple collaborators. While specific grant information isn't provided in the available data, her sustained publication output suggests successful funding of her research program. Her work bridges cellular and systems neuroscience, contributing to our understanding of how microcircuit properties shape sensory processing and behavior.

Tim Oatesمشاهده پروفایل

استاد

• Machine Learning
• Artificial Intelligence
• Deep Learning
• +۷ مورد دیگر

Dr. Tim Oates is a Professor in the Department of Computer Science and Electrical Engineering at the University of Maryland, Baltimore County . His research spans machine learning, artificial intelligence, and brain-machine interfaces, with a focus on weakly supervised methods, human-in-the-loop reinforcement learning, and grounded policy development for robotics. Ph.D., Computer Science, University of Massachusetts, Amherst, 2000 M.S., Computer Science, University of Massachusetts, Amherst, 1997 B.S., Computer Science and Electrical Engineering, 1989 Current research threads include: Developing non-invasive brain injury severity assessment via medical time series Modeling human brain development through computational frameworks Designing algorithms for autonomous robotic learning Recent publications highlight AI security mechanisms (backdoor detection via tensor decomposition, matrix factorization) Medical applications (3D artery reconstruction, skin lesion diagnosis, EEG denoising) Neuro-symbolic integration (holographic representations, language-guided reinforcement learning) Mathematical reasoning (schema-based problem solving, subitizing algorithms) Contact: oates@cs.umbc.edu | Office: 336 Information Technology and Engineering (ITE) Building

Jose M. Carmenaمشاهده پروفایل

استاد

• Neuroscience
• Neuroprosthetics
• Sensorimotor Learning
• +۵ مورد دیگر

Jose M. Carmena is the Chancellor's Professor of Electrical Engineering and Neuroscience at the University of California-Berkeley and Co-Director of the Center for Neural Engineering and Prostheses (CNEP). His research focuses on brain-machine interfaces (BMIs), neuroprosthetics, and sensorimotor learning mechanisms. Ph.D., Robotics, University of Edinburgh (2002) M.S., Artificial Intelligence, University of Edinburgh (1998) M.S., Electrical Engineering, University of Valencia (1997) B.S., Electrical Engineering, Polytechnic University of Valencia (1995) Dr. Carmena's work bridges neural engineering and systems neuroscience, investigating corticostriatal plasticity, wireless neural recording systems (e.g., neural dust), and closed-loop BMI adaptation. His publications reveal expertise in Neuroprosthetic Algorithms , Wireless Neural Interfaces , and Sensorimotor Learning with applications in chronic neuroprosthetic systems. McKnight Technological Innovations in Neuroscience Award (2017) IEEE Fellow (2017) NSF CAREER Award (2010) Sloan Research Fellow (2009) Hellman Fellow (2007) His advisees include Paul Botros, Archit Gupta, and Vivek Athalye. Dr. Carmena has published extensively in journals like Nature , Neuron , and Nature Neuroscience , developing technologies such as ultrasonic neural dust for cortical recording and adaptive control algorithms for prosthetics.

Karin H. Jamesمشاهده پروفایل

استاد

• Cognitive Neuroscience
• Developmental Psychology
• Brain and Behavior
• +۵ مورد دیگر

Karin H. James is a Professor and Director of Graduate Studies in the Department of Psychological and Brain Sciences at Indiana University Bloomington's College of Arts and Sciences, actively reviewing applications for Fall 2026 admissions. Her research program investigates how self-generated actions shape cognitive development through neural mechanisms. Her educational background includes: Post Doctoral Fellow, Vanderbilt University (2001-2003) Ph.D. in Psychology, University of Western Ontario (2001) M.A. in Psychology, University of Western Ontario (1998) B.S. in Psychology, University of Toronto (1996) B.A. in History, University of Toronto (1991) Dr. James' research centers on the neural correlates of learning, specifically how motor experience influences visual recognition across domains including object recognition, reading acquisition, language learning, and mathematical understanding. Using fMRI and behavioral methods, she examines how sensorimotor interactions during symbol production (e.g., handwriting) reconfigure brain networks for perception. Her work demonstrates that visual-motor contingency during learning creates lasting neural changes that enhance recognition, with implications for educational practices in literacy and numeracy development. Analysis of her 2018-2021 publications reveals consistent focus on embodied cognition principles, particularly how action-perception loops establish neural representations. Key themes include gesture-based learning in mathematics, visual-motor integration in symbol recognition, and category formation mechanisms, bridging cognitive neuroscience with developmental psychology through innovative methodologies like the MRItab neuroimaging tool. Dr. James maintains active membership in the Society for Research in Child Development (2007-present), Cognitive Neuroscience Society (2004-present), and Vision Sciences Society (2000-present), reflecting her interdisciplinary approach to learning mechanisms. As Director of Graduate Studies, she oversees program development and student mentorship while leading the Cognition and Action Neuroimaging Lab. Her research infrastructure includes specialized neuroimaging tools developed for naturalistic experimental paradigms, supporting investigations into how embodied experiences shape cognitive architecture from childhood through adulthood. The Cognition and Action Neuroimaging Lab develops cutting-edge methodologies like the MRItab touchscreen system to study naturalistic learning during fMRI scanning, focusing on how sensorimotor experiences during symbol production reconfigure neural networks for perception and recognition across developmental stages.

• Perception and Attention
• Meta-science and Research Methods
• Visual Cognition
• +۳ مورد دیگر

Alex Holcombe is a Professor in the School of Psychology at the University of Sydney . His research spans two major domains: perception and attention (investigating visual information bottlenecks and temporal processing) and meta-science (advancing open science and reproducibility through tools like tenzing.club and editorial roles in open-access journals). Education: PhD in Psychology (Harvard), BA in Psychology and Cognitive Science (University of Virginia) Editorial Roles: Associate editor for WikiJournal of Science , Collabra: Psychology , and Meta-psychology His experimental psychology work uses behavioral studies to reveal limits in visual processing speed, feature binding, and attentional resource allocation. Key findings include the role of naps in learning, parietal lobe function in rapid letter processing, and temporal binding dynamics in perception. Recent publications focus on peer review reform (2025 PNAS ), contributorship attribution (2024 Accountability in Research ), and visual cognition (2024 Journal of Vision ). These works reflect his dual commitment to understanding perceptual mechanisms and improving scientific practices. Advising: Mentors PhD students including De-wei DAI, Jye MARCHANT, and Rasmus PEDERSEN Labs: Leads research on visual perception and attentional bottlenecks Grants: 2024 Core Funding Grant for object tracking research