جست‌وجوی استاد و پژوهشگر

Scott Noklebyمشاهده پروفایل

استاد

• Robotics Engineering
• Mechatronics Systems
• Automation Technologies
• +۷ مورد دیگر

Dr. Scott Nokleby is an Associate Dean, Academic and Professor in the Department of Automotive and Mechatronics Engineering at the University of Ontario Institute of Technology. He holds a PhD in Mechanical Engineering from the University of Victoria (2003), and has over two decades of academic leadership and research experience. His primary roles include academic administration and advancing robotics and mechatronics research. Education: PhD (Mechanical Engineering, UVic, 2003), MASc (Mechanical Engineering, UVic, 1999), BEng (Mechanical Engineering with Co-op, UVic, 1997). Research interests focus on advanced robotics topics including parallel manipulators, mobile-manipulator systems, kinematic redundancy analysis, and autonomous systems. His work emphasizes practical applications such as radiation mapping robots, perching drones, and robotic hazard management. Notable contributions include optimal design methodologies for mechanisms and control systems for human-robot interaction. Publications reflect expertise in robotics systems, mechatronics, and nuclear engineering applications. Recent work explores multi-robot task allocation, autonomous navigation, and advanced control algorithms. Awards: Fellow of ASME (2022) Fellow of CSME (2016) CSME Best Paper Award (2014) UOIT Research Excellence Award (2008) CSME I.W. Smith Award (2007) Teaches graduate courses in advanced robotics, mobile robotic systems, and mechanism design. Active in academic administration, he bridges teaching innovation with engineering education through projects like tablet computing integration in design courses. Labs/Teams: Leads robotics research initiatives focused on autonomous systems development, with collaborations spanning nuclear safety, mining automation, and aerospace applications.

Martin v. Mohrenschildtمشاهده پروفایل

دانشیار

• Control Systems
• Signal Processing
• Simulation
• +۵ مورد دیگر

Dr. Martin v. Mohrenschildt is an Associate Professor in the Department of Computing and Software at McMaster University's Faculty of Engineering. He holds academic positions as Undergraduate Advisor for Mechatronics and Mechatronics Coordinator. His expertise spans control systems, signal processing, hybrid systems, and immersive simulation. He earned a Dr. sc. math. ETH and Dipl. math. ETH (Swiss Federal Institute of Technology), and is a Professional Engineer (P.Eng.). Research focuses include Model Predictive Control, vibration analysis for industrial machinery, and multisensory integration in motion simulation. His Motion Simulator Laboratory features a 6-DOF simulator with advanced visualization and physiological measurement capabilities. The Embedded Systems Laboratory explores mechatronics and robotics, including alternative fuel injection systems. Teaching includes courses like CAS-748 (Time Series Analysis) and SFWR ENG 2SO3. Recent work emphasizes sensor fusion (LiDAR/camera/thermal), biofeedback systems for muscle interventions, and cognitive effects of motion cues in virtual environments. Collaborations with Dr. Shedden investigate perceptual neuroscience in immersive simulators. His lab facilities support interdisciplinary projects combining engineering, computer science, and cognitive science. Publications span 30+ years, covering hybrid systems theory, control algorithms, and applied sensor technologies. Current research directions include autonomous vehicle perception systems and aging-related changes in multisensory integration.

Fabien Moutardeمشاهده پروفایل

استاد

• Machine Learning
• Deep Learning
• Computer Vision
• +۸ مورد دیگر

Fabien Moutarde is a Full Professor and Director of the Center for Robotics at MINES ParisTech (PSL University, Paris, France). He holds a PhD in Physics and an Habilitation to Direct Research in Engineering Sciences. Dr. Moutarde coordinates French engineering education at ParisTech_Shanghai (SPEIT) in China. Research Areas Deep Learning & Reinforcement Learning Computer Vision for Intelligent Vehicles Collaborative Robotics Traffic Analysis & Forecasting Human Gesture Recognition Recent Article Trends His work focuses on autonomous driving using Deep Reinforcement Learning, pedestrian trajectory prediction with spatio-temporal attention, and multi-modal localization techniques combining vision with Wi-Fi. Key applications include urban traffic analysis, collaborative robotics, and end-to-end driving systems. Leadership & Teaching Co-created specialized Machine Learning courses Pioneered Deep Reinforcement Learning lectures Led French-Chinese academic coordination Former UML/Java curriculum developer Publications With 28 h-index, his research includes 30+ IEEE/ACM publications on autonomous vehicles, gesture recognition, and traffic mining. Representative conferences: CVPR, NeurIPS, IROS, ITSC.

Alina Bialkowskiمشاهده پروفایل

مدرس ارشد

• Medical Imaging
• Biomedical Engineering
• Computer Vision
• +۶ مورد دیگر

Dr Alina Bialkowski is a Senior Lecturer at the School of Electrical Engineering and Computer Science , part of the Faculty of Engineering, Architecture and Information Technology at The University of Queensland. Her research focuses on interpretable machine learning and computer vision to enhance AI transparency and solve real-world challenges. Prior to joining UQ in late 2017, she held postdoctoral positions at University College London (2015–2017), where she studied human perception in driving, and Disney Research Pittsburgh (2014), analyzing team sports using spatiotemporal data. Dr Bialkowski earned her PhD and Bachelor of Engineering (Electrical Engineering) from Queensland University of Technology, Australia. Her doctoral research centered on group behavior analysis from visual and spatiotemporal data, with applications in sports analytics and intelligent surveillance systems. Her research interests span medical imaging (especially electromagnetic imaging of strokes), human attention modeling in driving, intelligent transport systems , surveillance systems , and sports analytics . She emphasizes explainable AI to bridge the gap between technical systems and human understanding, employing methods like feature visualization and attribution. Her work also explores sensors for non-invasive imaging and machine learning frameworks to ensure ethical AI. Dr Bialkowski has received significant recognition, including the Best Paper Prize at the 2017 IEEE Winter Conference on Applications of Computer Vision (WACV) . Her research has led to 6 international patents with collaborators such as Disney Research, Toyota Motor Europe, and The University of Queensland, focusing on electromagnetic imaging and AI-driven solutions. She actively contributes to interdisciplinary projects like The Lanyard Project (traffic sensor fusion) and co-authored a SmartSat CRC-funded research report on machine learning for satellites. Dr Bialkowski is available for supervision and advocates for AI systems that integrate human-centric principles into their design and evaluation.

Mary Stoddardمشاهده پروفایل

استاد

• Sensory Ecology
• Avian Vision
• Animal Coloration
• +۲ مورد دیگر

Mary Stoddard is Professor in Princeton University's Department of Ecology and Evolutionary Biology. Her research explores animal coloration, avian vision, and evolutionary processes using multidisciplinary approaches combining computer science, optics, physiology, and genomics. Fieldwork is conducted at the Rocky Mountain Biological Laboratory (Colorado) and Mountain Lake Biological Station (Virginia). Research investigates visual communication, color perception in hummingbirds, pattern recognition in eggshells, and the biomechanics of structural coloration. Develops open-source optical tools and software for quantifying animal coloration. Leads the Princeton Better for Birds Project to reduce bird-window collisions through community engagement and architectural solutions.

Peter Hallمشاهده پروفایل

استاد

• Computer Vision
• Computer Graphics
• Medical Imaging
• +۵ مورد دیگر

Professor Peter Hall is a faculty member in the Department of Computer Science at the University of Bath, affiliated with the Centre for Digital Entertainment (CDE), Centre for the Analysis of Motion, Entertainment Research & Applications (CAMERA), Visual Computing, and the Bath Institute for the Augmented Human. His research focuses on computer vision applications in computer graphics, including style transfer, tactile interfaces for visual impairment, and medical imaging techniques. He has led and collaborated on projects funded by EPSRC and EU Horizon 2020, such as the CAMERA initiative and studies on multisensory interaction. His expertise spans computer vision fundamentals like image segmentation, object recognition, and generative adversarial networks (GANs), alongside interdisciplinary work in medical imaging, robotics, and accessibility technologies. Notable contributions include deep learning-based MRI reconstruction, geometric style transfer algorithms, and tactile image generation for visually impaired users. Education details not explicitly stated in provided texts Projects include IAA tactile display systems, CAMERA motion analysis, and generative adversarial network research Advising and grants involve leadership roles in EPSRC-funded projects like 'Acquiring Complete and Editable Outdoor Models' and EU initiatives. His work aligns with UN SDGs related to health innovation and accessibility. Current research emphasizes domain adaptation techniques and cross-depiction problem solutions in computer vision.

Thecla Schiphorstمشاهده پروفایل

استاد

• Embodied Cognition
• Movement Knowledge Representation
• Wearable Technology
• +۳ مورد دیگر

Thecla Schiphorst is Professor and Director of the School of Interactive Arts and Technology at Simon Fraser University. Her research bridges dance, computing, and embodied interaction, focusing on movement knowledge representation, wearable technologies, and aesthetics of interaction. With interdisciplinary MA (Dance and Computing Science) from SFU and PhD from University of Plymouth, she applies somatic models like Laban Movement Analysis to technology design. Schiphorst co-developed Life Forms, the choreographic composition tool used by Merce Cunningham for his creations (1990-2005). Her work expands embodied theory applications in HCI through research in tangible interfaces, natural interaction, and experience design. She teaches courses exploring artificial intelligence applications and ethical challenges.

• Geomorphology
• Fluvial Processes
• Sediment Transport
• +۳ مورد دیگر

Mark Schmeeckle is a Professor at Arizona State University's School of Geographical Sciences and Urban Planning, with an affiliation to the Water Institute. His research focuses on landscape mechanisms, particularly sediment transport and environmental fluid dynamics. He develops advanced numerical models for turbulence in environmental flows, including LES and RANS techniques, to simulate bedload transport and morphodynamics in rivers and aeolian systems. Educated at the University of Colorado-Boulder (Ph.D., 1998), University of Washington-Seattle (M.S. 1992; B.S. 1988), he has led major grants from NSF, USGS, and industry partners. His work integrates experimental and computational approaches to study fluvial processes, turbulence-structure interactions, and sediment dynamics. Courses taught include GIS programming and statistical methods for geography. Key research interests include aeolian and fluvial sediment transport, bedform evolution, and the effects of vegetation on sediment movement. His publications analyze turbulence-driven bedload, riverbank stability, and ancient organism-environment interactions. He has advised numerous projects on Grand Canyon sediment dynamics and coastal aquifer modeling. Recent projects include modeling thermal erosion of lava channels and statistical mechanics of bedload transport. His contributions span environmental engineering, geomorphology, and paleontology, emphasizing interdisciplinary approaches to Earth surface processes.

Yehuda Bockمشاهده پروفایل

مدرس ارشد

• Geodesy
• Lithospheric Deformation
• Seismology
• +۴ مورد دیگر

Yehuda Bock is a Senior Lecturer and Research Geodesist at the University of California San Diego (UCSD), affiliated with the Scripps Institution of Oceanography and its Institute of Geophysics and Planetary Physics (IGPP). He directs the Scripps Orbit and Permanent Array Center (SOPAC), a key facility for geodetic data management and analysis. His roles include advancing seismogeodetic techniques for natural hazard mitigation and improving observational networks. Education: B.A. from New York University, B.S. from Technion-Israel Institute of Technology, M.S. and PhD from Ohio State University. Research focuses on crustal deformation, geodetic instrumentation, and integrating GNSS with seismic data for earthquake and tsunami warning systems. He explores applications of GNSS in meteorology, structural health monitoring, and climate studies. Recent work emphasizes real-time data fusion, machine learning for geophysical analysis, and understanding tectonic processes in regions like the San Andreas Fault and Cascadia Subduction Zone. His publications highlight advancements in deformation modeling, early warning systems, and interdisciplinary approaches to geoscience data.

Debi Kilbمشاهده پروفایل

پژوهشگر

• Crustal Seismology
• Earthquake Source Physics
• Earthquake Early Warning Systems
• +۴ مورد دیگر

Debi Kilb is a Researcher at the Institute of Geophysics and Planetary Physics (IGPP) and Science Director of the Scripps Institution of Oceanography (SIO) Visualization Center. She holds a B.A. from UCSD, M.A. from UCLA, and Ph.D. from the University of Memphis. Her research focuses on crustal seismology, earthquake source physics, and early warning systems. Kilb has pioneered work on dynamic earthquake triggering mechanisms and the application of scientific visualization techniques to geophysical data analysis. Her research interests span tectonics, structural geology, and volcanology, with a strong emphasis on developing real-time seismic monitoring systems like the PLUM algorithm for earthquake early warning (EEW). Kilb’s contributions include advancing understanding of fault zone dynamics, submarine avalanche seismology, and lithospheric deformation processes. Publications highlight innovation in EEW system testing, seismic network optimization, and interdisciplinary approaches to hazard mitigation. While no formal awards are listed, her work has significantly impacted disaster preparedness strategies and educational outreach through initiatives like the Earthquake! game and sonification projects. Her professional roles include managing SIO’s visualization facilities and collaborating on NSF-funded projects exploring icequake dynamics, glacier hydraulics, and seismic data interpretation. Kilb actively engages in public education through apps like Tilt Trivia and participatory science platforms like the Quake-Catcher Network.

William C Heindelمشاهده پروفایل

استاد

• Cognitive Neuroscience
• Neuroscience
• Memory Disorders
• +۴ مورد دیگر

William C. Heindel is a Professor of Cognitive and Psychological Sciences at Brown University and currently serves as Chair of the Department of Cognitive, Linguistic, and Psychological Sciences. He holds a B.S. in Engineering from the University of Wisconsin-Madison (1980) and a Ph.D. in Neurosciences from the University of California, San Diego (1989). His research focuses on cognitive neuroscience, particularly the neural mechanisms underlying memory, attention, and perception in both healthy individuals and those with neurocognitive disorders such as Alzheimer's disease. He has been funded by NIH grants and the Falk Medical Research Trust, among others. Heindel's research interests include the perceptual basis of semantic memory, neuropsychological substrates of category learning, and the role of arousal and attention in Alzheimer's disease. He collaborates with researchers in neurology, biostatistics, and psychiatry. His teaching includes courses on cognitive neuropsychology, memory, and research methods. His recent work explores sensory integration deficits in preclinical Alzheimer's, EEG markers of cognitive decline, and driving performance in older adults. He has published extensively in journals like Neuropsychologia , Alzheimer's & Dementia , and Cortex .

Konrad Paul Kordingمشاهده پروفایل

استاد

• Neuroscience
• Machine Learning
• Computational Neuroscience
• +۶ مورد دیگر

Konrad Paul Kording is the Nathan Francis Mossell University Professor at the University of Pennsylvania's School of Engineering and Applied Science, holding primary appointments in Bioengineering and Neuroscience, and a secondary appointment in Computer and Information Science. His research focuses on computational neuroscience, machine learning, and their applications to understanding neural systems and human behavior. He leads a research group located in Room 404 Richards and maintains an active research website and personal academic page. His work explores topics such as neural decoding, causal inference, and the alignment of artificial neural networks with biological systems. He has pioneered methods for analyzing neural activity in macaques, developing large-scale facial analysis resources like PrimateFace. His interdisciplinary approach integrates computer vision, medical informatics, and robotics to address challenges in neurology and developmental disorders. Recent research highlights include advancing techniques for early prediction of cerebral palsy using motion tracking and automated segmentation of synchrotron-scanned fossils. His contributions to causal discovery methodologies and neural network interpretability have been influential in both neuroscience and machine learning communities.

• Computer Vision
• Machine Learning
• Artificial Intelligence
• +۳ مورد دیگر

Dr. Jiayan Qiu is a Lecturer (Assistant Professor) at the University of Leicester's College of Computing and Mathematical Science. Previously, he was a postdoctoral research fellow collaborating with Prof. Zhou Wang at the University of Waterloo's Department of Electrical & Computer Engineering. He holds a Ph.D. from the University of Sydney (USYD), advised by Prof. Dacheng Tao, and completed his MPhil and Honorable B.S. at the Australian National University (ANU). His research focuses on computer vision, machine learning, and artificial intelligence, with notable contributions to visual relationship modeling, image outpainting, depth estimation, and generative models. His work has been published in top-tier venues like IEEE TPAMI, CVPR, ECCV, and ACM KDD. Professional service activities include serving as a reviewer for prestigious journals (e.g., IEEE T-PAMI, T-IP) and conferences (CVPR, ICCV, NeurIPS), as well as a member of program committees for leading AI conferences. He also contributes to academic leadership as a Guest Editor for Frontiers in Signal Processing and MDPI-Electronics .

Beatriz Calvo Merinoمشاهده پروفایل

استاد

• Cognitive Neuroscience
• Neuroaesthetics
• Sensorimotor Processing
• +۷ مورد دیگر

Professor Beatriz Calvo Merino is a Cognitive Neuroscientist at City St George's, University of London, where she is affiliated with the Department of Psychology in the School of Health Sciences. She serves as Programme Director for the MSc Clinical, Social and Cognitive Neuroscience and the Joint PhD Programme in Psychology and Social Neuroscience with Sapienza University, Italy. Her academic journey includes training at University College London and Universidad Complutense de Madrid, with postdoctoral work at the Institute of Cognitive Neuroscience. Research Interests: Her research explores the neural basis of action observation, sensorimotor expertise, and emotion perception, with a strong emphasis on dance and performing arts. She investigates how sensorimotor experience modulates aesthetic and emotional processing, contributing significantly to the field of neuroaesthetics. Her work integrates EEG, TMS, behavioral, and physiological methods to study embodiment and social cognition. Recent Research Trends: Her recent publications (2020–2025) reflect a sustained focus on embodiment in autism, emotion perception, multisensory integration, and the cognitive neuroscience of dance. She employs ERP and SEP methodologies to dissect somatosensory contributions to social perception, particularly in clinical populations. Her editorial and review work also highlights her leadership in methodological advancements in dance neuroscience. Scientific Awards: Alexander Gottlieb Baumgarten Award (2018) British Association of Cognitive Neuroscience Early Career Award (2019) Grants and Collaborations: Her research has been supported by the ESRC, Leverhulme Trust, Wellcome Trust, Ramon y Cajal Fellowship, and City University funding schemes. She collaborates widely with the dance community, including the Royal Opera House Ballet, Laban Dance Centre, and choreographers such as Wayne McGregor, bridging science and the arts. Labs and Teams: She leads a research group focused on sensorimotor processing and neuroaesthetics within the Department of Psychology, contributing to the Cognitive and Social Neuroscience research theme at City St George's.

Katherine Storrsمشاهده پروفایل

مدرس ارشد

• Visual perception
• Deep learning
• Psychophysics
• +۷ مورد دیگر

Katherine Storrs is a Senior Lecturer in the School of Psychology at the University of Auckland, New Zealand. She leads the Computational Perception Lab, where she combines computational modeling and psychophysical experiments to study visual perception. Her research is supported by a Marsden Fast Start grant, and she is actively involved in teaching and academic service. She earned her PhD in Psychological Science from the University of Queensland in 2015 and has held postdoctoral positions at Justus-Liebig University (Germany) and the MRC Cognition and Brain Sciences Unit (Cambridge, UK). She also worked as a Data Scientist at Twitter in London. Dr. Storrs' research focuses on how the visual system interprets material properties such as gloss, shape, and reflectance. She uses unsupervised deep learning models to simulate and predict human perception, particularly in ambiguous or complex visual environments. Her work bridges cognitive science, neuroscience, and artificial intelligence. Her most recent publications explore topics such as gloss perception, mental rotation, face similarity, and the role of statistical learning in shape encoding. These works frequently appear in high-impact journals like Nature Human Behaviour , PNAS , and Current Biology , demonstrating a strong trend toward using computational models to explain perceptual phenomena. Marsden Fast Start Grant (2021) Humboldt Research Fellowship (2019) UK National Finalist, FameLab (2017) Editorial Board Member, Nature Communications Psychology (2023–) Editorial Board Member, OpenMind (2022–) Social Media Editor, Perception and i-Perception (2020–) She supervises graduate students and teaches courses including PSYCH 306 (Research Methods), PSYCH 775 (Visual Perception in Brains and Machines), and PSYCH 109. She also mentors students in honours, master's, and PhD programs. Her lab is actively involved in interdisciplinary collaborations, particularly with researchers in machine learning and computational neuroscience. The lab is funded by the Marsden Fund and supported by access to high-performance computing resources for training deep neural networks.