جست‌وجوی استاد و پژوهشگر

Patrick Sladeمشاهده پروفایل

استادیار

• Assistive Robotics
• Biomechanics
• Human-Robot Interaction
• +۶ مورد دیگر

Patrick Slade is an Assistant Professor of Bioengineering at Harvard University's School of Engineering and Applied Sciences (SEAS). His lab, the Slade Lab, focuses on developing assistive devices to enhance mobility through the integration of biomechanics, robotics, and human-centered artificial intelligence. Key research areas include exoskeletons, prosthetics, wearable sensors for health tracking, and navigation aids for visually impaired individuals. Research Interests: The lab emphasizes translating research into practical solutions, such as personalized exoskeletons and robotic systems to improve mobility. Recent work includes optimizing human-robot interaction algorithms and publishing in high-impact journals like Nature . Collaborations with labs like the Biodesign Lab and BIONICs Lab highlight cross-disciplinary efforts. Publications: Over 15 articles since 2017 span topics like exoskeleton design, energy expenditure modeling, and Bayesian reinforcement learning. Notable contributions include a 2022 Nature paper on personalized exoskeleton assistance and a 2021 study on navigation aids for impaired vision. Awards & Grants: Students in his group have received prestigious NSF GRFP fellowships and conference awards, reflecting the lab's emphasis on innovation. The lab actively engages in grant-funded projects to advance assistive technology. Lab & Team: The Slade Lab opened at Harvard in 2023 and includes PhD students and postdocs working on devices like robotic exoskeletons and health-tracking systems. Future work focuses on scalable solutions for mobility challenges through interdisciplinary approaches.

• Textile-based Engineering
• Capacitive Engineering
• Actuator Engineering
• +۳ مورد دیگر

Özgür Atalay (ORCID: 0000-0003-1050-0685) is an Associate Professor at the Department of Textile Engineering , Istanbul Technical University . His research focuses on Textile-based Engineering with emphasis on Capacitive , Actuator , and Soft Robotics Engineering . Current projects include TexSoRVA (Textile-Based Soft Robotics for VR Applications), SMARTWASTE (Agricultural/Natural Waste Textiles), and TEXWEAROTS (Self-powered Wearable Soft Robotics). Collaborations span EU-funded initiatives, Turkish Scientific and Technological Research Council (TUBITAK), and industrial partnerships. His work integrates Internet of Things (IoT) with Electronic Textiles (E-textiles) , focusing on applications in Telerehabilitation , Wearable Robotics , and Smart Textiles . Key technologies include Capacitive Sensors , Conductive Yarns , and Fog Computing Frameworks . Recent publications highlight advancements in auxetic sensor design , cloud-controlled textile gloves , and self-powered wearable systems . His research output (58 publications) demonstrates a focus on practical implementations in Therapeutic Applications and Human-Machine Interaction . Özgür leads 6 active research projects, including: TexSoRVA : 04/2025-09/2026, EU-funded SMARTWASTE : 01/2023-12/2026, TTO-funded TEXWEAROTS : 11/2022-10/2027, EU-funded With over 1623 citations (h-index 15), his work contributes to Textile Electronics , Soft Robotics , and Wearable Technology fields.

• Computer Vision
• Machine Learning
• 3D Human Modeling
• +۴ مورد دیگر

Michael J. Black is a Professor and Honorarprofessor at the University of Tübingen's Faculty of Science, Department of Computer Science, and a founding Director of the Max Planck Institute for Intelligent Systems, leading the Perceiving Systems department. He holds a B.Sc. from the University of British Columbia (1985), M.S. from Stanford (1989), and Ph.D. in Computer Science from Yale (1992). His research focuses on computer vision, 3D human modeling, motion capture, and AI-driven digital humans. Key contributions include the SMPL body model, optical flow algorithms, and datasets like Middlebury Flow and Sintel. He has received major awards such as the PAMI Distinguished Researcher Award, multiple Koenderink and Longuet-Higgins Prizes, and is a member of the German National Academy of Sciences Leopoldina and Royal Swedish Academy of Sciences. His commercial ventures include co-founding Body Labs (acquired by Amazon) and Meshcapade, advancing 3D human generation and interaction technologies. Recent work includes markerless motion capture systems (e.g., MAMMA, PICO), 3D hair and garment synthesis, and AI tools like ChatHuman for 3D human interaction analysis. His research bridges vision, graphics, and robotics, with applications in animation, healthcare, and robotics.

Craig H. Meyerمشاهده پروفایل

استاد

• Medical and Molecular Imaging
• Signal and Image Processing
• Biomedical Data Sciences
• +۲ مورد دیگر

Craig H. Meyer is a Professor in Biomedical Engineering and Radiology & Medical Imaging at the University of Virginia. He holds a Ph.D. from Stanford University and leads the Rapid MRI Research Group, focusing on developing advanced MRI techniques for cardiovascular disease, neural disorders, and pediatrics. His work integrates physics, signal processing, and machine learning to improve MRI acquisition and processing speed. Education: Ph.D. in Biomedical Engineering, Stanford University. Research Interests: Medical and Molecular Imaging, Signal and Image Processing, Biomedical Data Sciences, Biomechanics, and Cardiovascular Engineering. His innovations include fast spiral imaging, conjugate phase reconstruction, and machine learning-enhanced MRI denoising. Awards: Notably includes the Dean’s Award for Excellence in Team Science (2014), Fellowships from NAI (2021), AIMBE (2015), and ISMRM (2013). He also authored two landmark MRI papers recognized as pivotal in the field. Teaching: Courses include BME 6310 (Computation and Modeling in Biomedical Engineering) and BME 8782 (Magnetic Resonance Imaging). He emphasizes translational research, with applications in clinical MRI advancements and collaborative interdisciplinary projects. Labs/Groups: Rapid MRI Research Group focuses on cutting-edge MRI technologies, including real-time cardiac imaging and artifact reduction through deep learning.

• Nuclear Magnetic Resonance (NMR)
• In vivo imaging
• MRI pulse sequence development
• +۷ مورد دیگر

Professor Guy Williams is a leading academic at the University of Cambridge with a focus on imaging science and clinical neurosciences, affiliated with Downing College and the Wolfson Brain Imaging Centre . Holding a PhD in Physics from his initial Natural Sciences degree, he specializes in nuclear magnetic resonance (NMR) and MRI techniques for brain imaging. Education: BA, PhD in Physics His research centers on non-invasive imaging of brain structure and function, particularly in traumatic brain injury (TBI) and dementia. His work involves developing novel MRI pulse sequences and advanced data analysis algorithms, including AI-based diagnostic tools. He leads studies on white matter integrity post-trauma, longitudinal dementia assessment, and applications of MRI in disorders of consciousness and addiction. Recent publications highlight collaborations in traumatic brain injury outcomes, AI-guided dementia prediction, and neuroimaging of post-COVID cognitive deficits. His team's work on ultra-high field laminar fMRI and distortion correction methods has advanced clinical neuroscience applications. Key techniques include diffusion tensor imaging (DTI), 7 Tesla MRI, and positron emission tomography (PET/MR). His research spans from basic NMR physics to clinical translation, with a strong emphasis on multi-site studies and real-world diagnostic implementation.

Simon Goodwillمشاهده پروفایل

پژوهشگر ارشد

• Sports Engineering
• Performance Analysis
• Software Development
• +۳ مورد دیگر

Dr. Simon Goodwill is the Head of Research in Sport and Physical Activity and Head of the Sports Engineering Research Group (SERG) at Sheffield Hallam University's Academy of Sport and Physical Activity. He holds a PhD focused on tennis ball-racket impact modeling and has collaborated with the International Tennis Federation. His expertise includes novel photogrammetry techniques, software development for athlete performance analysis, and camera calibration systems like check2d/check3d. He led projects supporting Team GB athletes in multiple Olympics, contributing to 42 medals at Rio 2016. Currently, he oversees the Advanced Wellbeing Research Centre (AWRC), applying sports performance methodologies to health research. His work integrates machine vision, data acquisition hardware, and elite athlete monitoring systems, with notable contributions to the EIS Innovation Partnership and sports tech exhibits like Le Tour Yorkshire's bike simulator. Education & Research: Simon’s PhD (modeling tennis impacts) and extensive software engineering background underpin his research. His projects span biomechanics, sports engineering, and health tech, with collaborations involving UK Sport, FIFA, and Adidas. He has developed systems used by athletes in London 2012, Rio 2016, and Glasgow 2014 Commonwealth Games. Research Themes: His work emphasizes performance analysis through photogrammetry, real-time athlete tracking, and health-related applications of sports tech. Key projects include court pace rating for the ITF, iBoxer2 boxing data tools, and the AWRC’s health innovations. Grants & Impact: The AWRC, funded by UK DoH and ESIF (£15.7M), reflects his role in translating elite athlete tech to public health. His work is cited in UK government reports on Olympic legacy and has received media attention, including BBC features on GB Boxing’s iBoxer software. Advising & Leadership: Supervised 17 PhD students on topics like machine learning in taekwondo, swimming analysis, and tennis racket dynamics. Served as External/External advisor and led 10+ Olympic cycle projects. Active in the International Sports Engineering Association as Director.

Leonardo Chamorroمشاهده پروفایل

استاد

• Aero/Hydrodynamics
• Wind and Hydrokinetic Energy
• Advanced Flow Diagnostics
• +۵ مورد دیگر

Leonardo Chamorro is a Professor in the Department of Mechanical Science and Engineering at the University of Illinois at Urbana-Champaign (UIUC), with affiliations in Earth Science and Environmental Change, Aerospace Engineering, and Civil and Environmental Engineering. His research focuses on fluid dynamics, renewable energy systems, and turbulence modeling. He holds a Ph.D. in Civil Engineering from the University of Minnesota (2010) and has held academic positions at UIUC since 2013, advancing to Full Professor in 2024. Chamorro's work spans experimental and theoretical investigations of wind and hydrokinetic energy, geophysical flows, and particle dynamics. His research group, the Renewable Energy & Turbulent Environment Group (RE-TE-G), explores topics like tidal flow multifractality, vortex dynamics, and bio-inspired robotics. Key achievements include Nature and Lab on a Chip cover articles, and contributions to turbulence modeling for tidal energy systems. He has received awards such as the Best Paper Award in Energies (2018) and recognition for pandemic-related research (2021). His editorial roles include associate editorships at journals like Journal of Renewable and Sustainable Energy and Frontiers in Energy Research . Chamorro has supervised numerous graduate students and postdocs, contributing to over 150 peer-reviewed publications since 2009.

James Herbert-Readمشاهده پروفایل

دانشیار

• Behavioural Ecology
• Marine Biology
• Collective Animal Behaviour
• +۴ مورد دیگر

Dr James Herbert-Read is an Associate Professor and Whitten Lecturer in Marine Biology at the Department of Zoology, University of Cambridge. He serves as Deputy Head of Department (Postgraduate Education) and leads the Marine Behavioural Ecology Group. His research focuses on understanding how animals, particularly marine organisms, collect and process information from their environments to make behavioral decisions, with emphasis on social interactions, adaptation mechanisms, and ecological constraints. His group employs theoretical frameworks, controlled experiments, and quantitative field studies to investigate behavioral diversity in marine species. Key themes include collective behavior, predator-prey dynamics, camouflage strategies, and the impacts of environmental stressors on animal decision-making. Recent publications highlight work on lionfish vocalization mechanisms, cuttlefish camouflage, citizen science applications in marine research, and behavioral responses to visual and acoustic noise. Scientific awards and affiliations include: Whitten Lecturer in Marine Biology Associate Professor, University of Cambridge He has supervised research projects on topics such as: Social attraction in invasive fish species Evolution of coordinated movement Neurophysiological basis for leadership in shoals Maternal effects on offspring exploration

Aaron M. Dollarمشاهده پروفایل

استاد

• Robotics
• Mechatronics
• Robotic Grasping and Manipulation
• +۵ مورد دیگر

Aaron M. Dollar is the Frederick W. Beinecke Professor of Mechanical Engineering at Yale University, affiliated with the Yale Grab Lab. His research focuses on robotics, mechatronics, robotic grasping, and prosthetics, emphasizing adaptive mechanisms and human-robot interaction. He holds a PhD from Harvard University (2008) and degrees from UMass Amherst. Key research areas include dexterous manipulation, underactuated mechanisms, and assistive devices. His work bridges theory and practical applications, with contributions to prosthetic hands, robotic hands, and modular robotics systems. Recipient of prestigious awards: TR35 Innovator (2010), NSF CAREER Award (2010), DARPA Young Faculty Award (2013), and Air Force Young Investigator Award (2011). Developed the Yale MyoAdapt Hand, a single-actuator prosthetic with high functionality. Pioneered methods in real-to-sim transfer, modular lattice printing, and energy-aware robotic exploration. His lab, the Yale Grab Lab, explores robotics, prosthetics, and human motion analysis. Recent projects include autonomous calibration systems (ARC-Calib) and low-cost robotic hardware (RB5 Explorer).

James W. Navaltaمشاهده پروفایل

دانشیار

• Exercise Physiology
• Outdoor Exercise Physiology
• Wearable Technology Validation
• +۳ مورد دیگر

Dr. James W. Navalta is an Associate Professor in the Department of Kinesiology and Nutrition Sciences at the University of Nevada, Las Vegas. His research focuses on physiological responses to outdoor exercise (hiking, trail running) and the validity/reliability of wearable technology. He earned his B.S. in Physical Education and Biology from Brigham Young University–Hawaii, M.S. in Kinesiology from UNLV, and Ph.D. in Exercise Physiology from Purdue University. Education: B.S. - Physical Education & Biology, Brigham Young University–Hawaii M.S. - Kinesiology, University of Nevada, Las Vegas Ph.D. - Exercise Physiology, Purdue University His research portfolio includes: Wearable technology validation for physiological measurements Comparative studies of indoor vs outdoor exercise environments Impact of gender-inclusive approaches on sports science Metabolic and cardiovascular responses to unconventional workouts Psychological benefits of nature immersion Recent publications demonstrate expertise in: Wearable device accuracy testing VO2max and lactate threshold validation Environmental influence on exercise physiology Methodological improvements in data collection Gender-inclusive research design Outdoor activity impact assessment As co-founder and executive editor of the International Journal of Exercise Science, he contributes significantly to academic discourse. He also serves on editorial boards for journals related to digital health and exercise technology.

Daniel E. Koditschekمشاهده پروفایل

استاد

• Dynamical Systems and Control
• Hybrid Control Systems
• Legged Locomotion
• +۷ مورد دیگر

Daniel E. Koditschek is the Alfred Fitler Moore Professor in the Department of Computer and Information Science at the University of Pennsylvania’s School of Engineering and Applied Science. He also holds primary appointments in the Department of Electrical and Systems Engineering and a research affiliation with the Department of Mechanical Engineering and Applied Mechanics. He is a leading figure in the GRASP Lab, where he leads the Kod*lab, a specialized group focused on physical interaction and locomotion in autonomous robots. His research lies at the intersection of dynamical systems theory and robotics, emphasizing legged locomotion, hybrid control systems, and bio-inspired design. Koditschek's work integrates formal mathematical modeling with empirical testing of physical robots that run, jump, climb, and manipulate objects. He actively explores how biological insights into animal mobility can inform robotic autonomy and control. His group maintains strong collaborations with biologists and emphasizes embodied intelligence in machine behavior. The recent publications reflect a strong trend in applying theoretical control frameworks—such as hybrid dynamical systems, averaging methods, and navigation functions—to practical robotic challenges in unstructured environments. Topics include terrain adaptation, energy-efficient locomotion, reactive planning, and affordance-based interaction. There is a clear focus on bridging abstract mathematical models with real-world robotic performance, particularly in legged and mobile manipulation systems. IEEE RAS Pioneer Award Heilmeier Research Award AFOSR MURI Award (2010) Daniel Koditschek has advised numerous PhD students and postdoctoral researchers, many of whom now hold faculty positions or leadership roles in robotics companies like Ghost Robotics and Boston Dynamics. His research is supported by major grants from the NSF and AFOSR, including the MURI award and REU/RET programs that engage K-12 and undergraduate educators. He has also been involved in international outreach, including activities at the Penn Wharton China Center. Koditschek leads the Kod*lab within the GRASP Lab’s PERCH facility, which houses advanced legged robots such as the Ghost Minitaur, XRHhex, Inu, Delta Hopper, and Jerboa platforms. The lab emphasizes experimental validation of control theories using custom hardware and real-world terrain challenges.

Hyung Jin Changمشاهده پروفایل

دانشیار

• Human-Robot Interaction
• Computer Vision
• Machine Learning/Deep Learning
• +۶ مورد دیگر

Dr. Hyung Jin Chang is an Associate Professor at the School of Computer Science, University of Birmingham, and a Turing Fellow at the Alan Turing Institute. He holds a Ph.D. and B.S. from Seoul National University. His research focuses on human-centered visual learning, particularly in human-robot interaction, with expertise in computer vision, machine learning, and deep learning. He has been involved in organizing conferences like ECCV and ICCV workshops (e.g., VOTS Challenge, HANDS Workshop) and serves on program committees including AAAI and CVPR. His work spans areas like gaze estimation, domain adaptation, 3D pose estimation, and robotic perception for assistive technologies. Key achievements include receiving the Royal Society Research Grant (2019–2020) and Wellcome Trust funding. Notable contributions include frameworks for unsupervised domain adaptation, gaze estimation models (e.g., RT-Gene), and collaborative learning methods for hand-object reconstruction. He has led projects in medical robotics, personalized dressing assistance, and safety-critical systems like driver attention prediction. His 15 most recent articles (2024–2025) emphasize advancements in diffusion models, domain adaptation, 3D reconstruction, gaze-controllable systems, and generative AI for motion and interaction modeling. These reflect a trend toward integrating multimodal data (vision + language) and bridging theoretical foundations with applied robotics. Awards: Royal Society Grant, Wellcome Trust, Turing Fellowship Grants: Active in securing funding for robotics, vision, and healthcare applications He leads the Personal Robotics Lab and collaborates on projects like the VOTS Challenge for visual object tracking. His research bridges academia and real-world applications in healthcare robotics and human-technology interaction.

• Audio Signal Processing
• Psychoacoustics
• Cochlear Implants
• +۵ مورد دیگر

Prof. Bernhard U. Seeber is an Extraordinary Professor at the Technical University of Munich (TUM), leading the Chair of Audio Signal Processing within the TUM School of Computation, Information and Technology. His work bridges auditory neuroscience and engineering, focusing on improving hearing aids, cochlear implants, and virtual acoustic systems. He holds affiliations with the Bernstein Center for Computational Neuroscience, Munich Institute of Biomedical Engineering, and others. Education: Studied and earned his PhD (2003) in Electrical Engineering and Information Technology at TUM. Postdoctoral research included time at UC Berkeley and the MRC Institute of Hearing Research (UK), where he pioneered studies on binaural hearing and cochlear implant optimization. Research Interests: Combines experimental and theoretical approaches to explore auditory scene analysis, binaural unmasking, and spatial hearing. Key areas include signal coding for cochlear implants, virtual acoustics, and non-destructive acoustic monitoring. His work emphasizes interdisciplinary collaboration with industry and academia. Awards: Lothar Cremer Award (2010), Emmy Noether Fellowship (2007), and recognition from the German Acoustical Society. Teaching: Offers courses on audio communication, computational neuroscience, and technical acoustics. Projects: Leads initiatives like HAPPAA and Auralization, advancing sound field synthesis and hearing aid algorithms. Current Roles: Head of Chair of Audio Signal Processing, Board Member of DEGA, and spokesperson for the ITG Technical Committee on Hearing Acoustics.

Zahra Abbasiمشاهده پروفایل

استادیار

• Applied Electromagnetics
• RF/Microwave Sensing
• Chipless Sensors
• +۵ مورد دیگر

Dr. Zahra Abbasi is an Assistant Professor at the Department of Electrical and Software Engineering, University of Calgary (since 2021), with expertise in designing passive and active RF/microwave sensors for non-invasive real-time detection and monitoring. She holds a PhD in Nanosystems and Microsystems from the University of Alberta (2020) and a postdoctoral fellowship at the Waterloo Microfluidics Lab (University of Waterloo). Her research focuses on sensor systems for environmental, biomedical, and industrial applications, including microfluidic sensing, chipless tags, and wearable devices. Dr. Abbasi’s educational background includes degrees from Iran University of Science & Technology (BSc 2014, MSc 2016) and advanced training in Canada. She chairs IEEE MTT-S/AP committees in Alberta and has received notable awards such as the ASTech Finalist (2024) and Alberta Immigrant Impact Award (2023). Her work emphasizes collaboration across disciplines to address challenges in precision agriculture, healthcare, and environmental monitoring. Her sensor research spans diverse fields: microplastic detection in water, hydrocarbon contamination monitoring, real-time medical diagnostics (e.g., fibrinogen levels), and nutrient assessment in agriculture. Recent advancements include disposable sensors for medical implants and non-invasive hydration tracking for aging populations. Awards Finalist: ASTech Early Career Academic Change Maker (2024) Early Research Excellence Award (Schulich School of Engineering, 2023/2024) Alberta Immigrant Impact Award (2023) Advising & Labs Dr. Abbasi leads the Calgary Sensor Laboratory, fostering innovation in microwave and microfluidic sensor technologies. Her team collaborates on industrial and biomedical projects, emphasizing practical applications of novel sensor designs. While no named advisees are listed, her research group actively engages in multidisciplinary projects.

• X-ray Physics
• Synchrotron Radiation
• Medical Imaging
• +۵ مورد دیگر

Benedikt Günther is a research scientist at the Technical University of Munich (TUM) working within the Chair of Biomedical Physics led by Prof. Dr. Franz Pfeiffer. His research focuses on the Munich Compact Light Source (MuCLS), a laboratory-scale inverse Compton X-ray source that provides synchrotron-like radiation for biomedical applications. Günther plays a key role in developing, optimizing, and characterizing this innovative technology, contributing to both its fundamental physics and practical medical applications. His primary research interests center around X-ray physics and imaging techniques, particularly laser enhancement cavities for inverse Compton X-ray sources, X-ray microscopy, dynamic phase-contrast imaging, and X-ray spectroscopy. Günther's work bridges fundamental physics with practical medical applications, developing instrumentation that brings synchrotron-quality imaging to conventional laboratory settings. His research has significant implications for improving medical diagnostics while making advanced imaging techniques more accessible. Analysis of Günther's publication record reveals a consistent focus on advancing compact X-ray source technology and its applications. His work demonstrates expertise in both theoretical modeling and experimental implementation, with publications spanning instrument development, imaging techniques, and specific medical applications. The research shows progression from fundamental source characterization to increasingly sophisticated biomedical applications, particularly in breast imaging, dental diagnostics, and materials science. 2019 Best Poster Award at the combined meeting of the 68th Denver X-ray Conference (DXC) & 25th International Congress on X-ray Optics and Microanalysis (ICXOM) for 'Full-Field Structured Illumination Super-Resolution X-ray Transmission Microscopy' Günther regularly presents his work at major international conferences including the International Particle Accelerator Conference, High-Brightness Sources and Light-driven Interactions Congress, and specialized X-ray imaging meetings. His research is conducted within the Munich Compact Light Source facility, a collaborative project involving physicists, engineers, and medical researchers working to develop laboratory-scale synchrotron technology for widespread biomedical use.