Find Academic Supervisors

• Neuroscience
• Psychology
• Visual Perception
• +3 more

Jonathan Winawer is an Associate Professor of Psychology and Neural Science at New York University (NYU). He leads the Winawer Laboratory for Human Visual Perception and Neuroscience, which is affiliated with the NYU Psychology Department, NYU Center for Neural Science, NYU Neuroscience Institute, and collaborates with the NYU Comprehensive Epilepsy Center and Stanford University's Human Intracranial Cognitive Program. Ph.D., Massachusetts Institute of Technology (2007) M.S., City College of the City University of New York (2005) A.B., Columbia University (1995) His research focuses on the biological basis of visual perception, including computational models of the visual pathways using fMRI, EEG, ECoG, and psychophysics. Key areas include: Encoding of visual stimuli in neural pathways Perceptual memory's influence on cognition Neural circuit properties underlying imaging signals Individual differences in visual perception Publications highlight interdisciplinary approaches spanning computational neuroscience, neuroimaging, and psychophysics, with recent work on population receptive fields, spatial frequency tuning, and memory-related cortical dynamics. He has mentored numerous students and postdocs, many of whom have advanced to academic and research roles at institutions like Stanford, Columbia, and the University of Amsterdam. Department of Psychology, NYU Center for Neural Science, NYU Neuroscience Institute, NYU Comprehensive Epilepsy Center, NYU Stanford University collaborations

Deepak GanesanView profile

Professor

• Networking and Distributed Systems
• Mobile and Sensor Systems
• Human-Computer Interactions
• +3 more

Deepak Ganesan is a Professor at the Manning College of Information and Computer Sciences (CICS) at the University of Massachusetts Amherst. His research focuses on low-power sensing and communication, networked systems, and machine learning applied to pervasive health monitoring and societal challenges. PhD, Computer Science, University of California, Los Angeles (2004) MS, Computer Science, University of California, Los Angeles (2000) BTech, Computer Science, Indian Institute of Technology, Madras (1998) Ganesan's work bridges wireless sensor networks, smart textiles, and healthcare applications. He designs ultra-low-power wearable devices for tracking health signals like drug use, smoking, and cognitive performance, often integrating machine learning for robust detection. His research emphasizes societal impact, particularly in aging and Alzheimer's care through the Massachusetts AI and Technology Center for Connected Care (MassAITC) and the Center for Personalized Health Monitoring (CPHM). Recent publications highlight innovations in edge-cloud collaboration, fabric-based sensors, and longitudinal health analytics. His NIH-funded MD2K Center for Excellence and affiliations with the Center for Data Science and Computational Social Science Institute further underscore his interdisciplinary approach. ACM Fellow NSF CAREER Award (2006) IBM Faculty Award (2008) UMass Junior Faculty Fellow (2008) UMass Lilly Teaching Fellow (2009) Best Paper at CHI 2013 Best Paper Runner-up at Mobicom 2014 Honorable Mentions at Ubicomp 2013 Ganesan leads the SENSORS: Wireless Sensor Networks Group and contributes to global initiatives like the Internet of Battlefield Things. His work spans academic research, industry partnerships, and policy development in AgeTech and digital health.

Noel T. ClemensView profile

Professor

• Aerothermodynamics
• Fluid Mechanics
• Hypersonics
• +7 more

Noel T. Clemens serves as a Professor and holds the prestigious Clare Cockrell Williams Centennial Chair in Engineering within the Aerospace Engineering and Engineering Mechanics Department at the University of Texas at Austin's Cockrell School of Engineering. He has been a faculty member since 1993 and served as department chair from 2012 to 2020. His research laboratory is part of the Center for Aeromechanics Research (CAR) where he directs the Flowfield Imaging Laboratory. Dr. Clemens' research focuses on experimental investigations of hypersonic flows, turbulent combustion, and advanced optical diagnostic techniques. His current work emphasizes 3D shock wave/boundary layer interactions, inlet unstart control, flashback in high-pressure combustors, turbulent combustion with non-equilibrium effects, and high-temperature ablation phenomena. He has pioneered laser-based measurement techniques for extreme environments, particularly for hypersonic flight applications where conventional measurement approaches fail. His recent publication record through 2025 demonstrates continued leadership in experimental fluid dynamics, with particular emphasis on plasma diagnostics for ablation studies, shock/boundary layer interaction physics, and advanced optical measurement techniques for extreme environments. The research spans fundamental fluid mechanics investigations to applied aerospace engineering problems relevant to hypersonic vehicle development. Elected to National Academy of Engineering (2024) AIAA Aerodynamic Measurement Technology Award (2022) Elected AIAA Fellow (2019) National Science Foundation Presidential Faculty Fellow (1996) Editor-in-Chief of Experiments in Fluids (2009-2013) Fellow of the American Physical Society Dr. Clemens has secured substantial research funding for his experimental investigations in hypersonics and combustion, leading multiple major research projects with government and industry partners. His laboratory facilities include advanced wind tunnels and state-of-the-art optical diagnostic systems for high-speed flow visualization. The Flowfield Imaging Laboratory at UT Austin serves as a national resource for advanced flow measurement techniques development. As an educator, he teaches core courses in compressible flow, viscous flow, combustion, experimental methods, and laser diagnostic techniques, training the next generation of aerospace engineers in both fundamental principles and cutting-edge measurement technologies.

Raphaël PhanView profile

Professor

• Security
• Cryptography
• Malicious AI
• +5 more

Prof Raphaël Phan is a Professor and Deputy Head of the School of IT at Monash University Malaysia. His expertise spans security, cryptography, malicious AI, emotion recognition, motion analysis, and generative AI. He has published over 220 papers and led significant projects including privacy-preserving data mining funded by UK MoD and Malaysian government grants exceeding RM4 million. He co-designed the BLAKE hash function (SHA-3 finalist) and has an h-index of 50. Education: PhD in Cryptography (Multimedia University, 2005), MEngSci (2001), BEng (Hons) Computer Engineering (1999). Research focuses on adversarial AI, brain networks, and secure systems. Current projects include Æmbience: emotion-aware virtual assistants using motion magnification. Supervised 15 PhD graduates and 19 current students. Professional affiliations: Chartered Engineer (IET, UK), HEA Fellow, Board of Engineers Malaysia. Recent work emphasizes causal bias detection in micro-expressions, brain tumor detection via advanced YOLOv8, and generative adversarial networks for medical imaging. His work bridges cybersecurity with neuroscience applications.

Mohamed HefeedaView profile

Professor

• Multimedia Networking
• Peer-to-Peer Systems
• Internet Protocols
• +6 more

Mohamed Hefeeda is a Professor in the School of Computing Science at Simon Fraser University (SFU), Canada. He leads the Network and Multimedia Systems Lab (NMSL) and previously served as Director of the School from 2018 to 2023. His research focuses on multimedia networking, mobile computing, cloud systems, and hyperspectral imaging. He holds an ACM Distinguished Member designation and has received prestigious awards including the NSERC Discovery Accelerator Supplements (2011) and multiple best paper awards at top conferences like ACM MM and IEEE Infocom. Education: Ph.D., Purdue University, 2004 M.Sc., University of Connecticut, 2001 B.Sc., Mansoura University, Egypt, 1994 Research Interests: Design of efficient multimedia systems and protocols for wired/wireless networks Cloud gaming optimization and video encoding techniques Hyperspectral imaging for healthcare and mobile applications AI-driven multimedia systems and mobile computing innovations Grants & Industry Collaborations: Funded by NSERC, CFI, and companies like AMD, Huawei, and CBC Co-founded Video Semantics (acquired by tech firm) Partnered with CBC on peer-assisted content distribution systems Awards Highlights: 2025: ACM Distinguished Member 2019: Best Student Paper Award at ACM MMSys 2015: NSERC Discovery Accelerator Supplements Labs & Leadership: Network and Multimedia Systems Lab (NMSL) at SFU Contributed to creation of Qatar Computing Research Institute (QCRI)

• Optical Imaging
• Biomedical Device and Instrumentation
• Medical Image Analysis
• +2 more

Jungeun (Jenny) Won is an Assistant Professor of Research in the Department of Biomedical Engineering at the School of Engineering and Applied Sciences, University at Buffalo. Her research focuses on optical imaging , biomedical device development , medical image analysis , and artificial intelligence in OCT . She leads the Translational Biophotonics Laboratory , where she develops advanced OCT techniques for medical applications such as diabetic retinopathy , otitis media , and biofilm analysis . Contact: 215J Bonner Hall, Buffalo NY 14260, jungeunw@buffalo.edu Related Links: CV PDF , Google Scholar , Lab Website Her recent work involves high-resolution OCT for longitudinal studies on retinal degeneration, VISTA OCTA for blood flow analysis, and 3D motion correction algorithms to enhance image quality. She also explores multimodal imaging combining OCT with Raman spectroscopy for bacterial differentiation and microplasma-based therapies for ear infections.

Heidi BaselerView profile

Senior Lecturer

• Visual Neuroscience
• Neuroimaging
• Sensory Processing
• +4 more

Dr. Heidi Baseler is a Senior Lecturer in Imaging Sciences at the Hull York Medical School and the Department of Psychology , University of York . She serves as INSPIRE Programme Lead for undergraduate research and contributes to research governance and public/patient involvement in research through committees like the York Neuroimaging Centre Research Governance Committee and Involvement@York . Education : AB in Biology/Psychology from Dartmouth College (1986), PhD in Vision Science from University of California, Berkeley (1995) Career : Research Fellow at Stanford, Smith-Kettlewell Eye Research Institute, and University of York; Lecturer in Imaging Sciences at Hull York Medical School (2012-2021) Her research focuses on neural mechanisms for central/peripheral vision processing, cortical responses to sensory loss (e.g., AMD, deafness), and neuroprotective strategies like photobiomodulation. Techniques include structural and functional MRI , magnetic resonance spectroscopy , multifocal EEG , and electroretinography . Key findings include cortical reorganization in macular degeneration and superior visual performance in deaf adults. Recent article trends highlight: Neuroimaging biomarkers for AMD progression Cross-modal plasticity in deaf individuals Long-term effects of sensory deprivation on brain structure Photobiomodulation for neurodegeneration Functional connectivity in face-selective regions Contrast perception dynamics across aging Scientific awards include: Exceptional Contribution to Student Experience Finalist , Hull York Medical School (2024) Pursuing Excellence Award , Hull York Medical School (2023) Vice-Chancellor's Teaching Award , University of York (2020) Multiple Teacher of Excellence Finalist recognitions (2016-2018) She teaches undergraduate medical students in Foundations of Medicine and Neurological Diseases , and supervises MSc Cognitive Neuroscience projects. Collaborations span institutions like University of Hull , University of Lille , and University of Regensburg . Current students include Sharyfah Alasiri (PhD, Biomedical Sciences) and Erin English (PhD, Psychology) at the University of York.

• Visual Perception
• Neural Science
• Cognitive Science
• +4 more

Jonathan A Winawer is a Professor of Psychology and Neural Science at New York University, affiliated with the College of Arts & Science. He holds a PhD from MIT (2007), M.S. from City College of CUNY (2005), and A.B. from Columbia University (1995). His research focuses on the neural basis of visual perception, integrating computational models with neuroimaging (MRI, EEG, ECoG) and psychophysics to understand how visual stimuli are encoded and processed. His work explores cortical mechanisms enabling perception, perceptual memory effects on cognition, and the impact of neural pathways on vision. Winawer's lab collaborates with NYU Neuroscience Institute and Stanford University, emphasizing interdisciplinary approaches to visual neuroscience. Recent research trends highlight studies on visual cortex memory, cortical crowding dynamics, spatial frequency tuning, and neural oscillations. Collaborations span EEG-MEG modeling, neuroimaging validation, and developmental neuroscience. Advising encompasses PhD students in cognitive science and neuroscience, with grants supporting neuroimaging and computational projects. The Winawer Lab is a hub for visual perception studies, affiliated with multiple NYU centers including the Center for Neural Science and the Neuroscience Institute.

Gerd BruderView profile

Associate Professor

• Extended Reality (XR)
• Virtual Reality (VR)
• Augmented Reality (AR)
• +12 more

Gerd Bruder is an Associate Professor in the Department of Computer Science at the University of Central Florida and a Research Associate Professor at the Institute for Simulation and Training. His work bridges computer science, human factors, and immersive technologies, with a focus on Extended Reality (XR) systems. Education: Habilitation, Computer Science, University of Hamburg, Germany (2017) Ph.D., Computer Science, University of Münster, Germany (2011) M.Sc., Computer Science with minor in Mathematics, University of Münster, Germany (2009) Dr. Bruder’s research centers on human-computer interaction in virtual and augmented environments. His interests include perception, 3D user interfaces, display technologies, and digital twins, with applications in healthcare, military training, architecture, and smart environments. He investigates how users perceive and interact with immersive systems, leveraging illusions and redirection techniques to enhance experience and usability. His recent publications reveal a strong trend in trust, cognitive load, and social interaction in XR. Themes include user transitions between realities, robot reliability perception, multisensory feedback, and AI integration. His work often explores how visual and spatial cues affect user behavior and decision-making in complex environments. Scientific Awards: Best Paper Award, ACM VRST 2023 2021 Innovation Award, TechConnect World Multiple Best Paper, Demo, and Poster Awards from ACM and IEEE conferences (2008–2021) Dr. Bruder leads an active research group, mentoring students and collaborating on grants and patents related to AR/VR systems. His work is supported by interdisciplinary teams and institutions, including UCF’s Institute for Simulation and Training. He has co-authored numerous patents in AR magnification, audiovisual detection, and virtual human simulation. His lab focuses on immersive environments, digital twins, and human factors in XR. Projects involve collaborative mixed reality, perceptual illusions, and real-world applications in training and healthcare.

Alex BaldwinView profile

Assistant Professor

• Computational Neuroscience
• Visual Psychophysics
• Binocular Vision
• +6 more

Alex Baldwin is an Assistant Professor at McGill University within the Department of Ophthalmology & Visual Sciences. He serves as a Junior Scientist in the Brain Repair and Integrative Neuroscience (BRaIN) program at the Research Institute of the McGill University Health Centre. Supervisor in McGill's Integrated Program in Neuroscience (IPN) Supervisor in Quantitative Life Sciences program Laboratory located at Montreal General Hospital Research focuses span computational neuroscience, visual psychophysics, and binocular vision mechanisms , particularly examining: Amblyopia and spatial scrambling Aging-related changes in stereopsis Visual noise adaptation Contrast summation models Contour integration processes Digital therapeutic development His lab employs Matlab/Octave (Psychtoolbox), Python (PsychoPy), and Unity/C# for experimental design, with Python (Jupyter) and Matlab (Palamedes Toolbox) for data analysis. Collaborations include Wenzhou Medical University. Scientific recognition includes: NSERC Discovery Grant (2022-2027) HBHL Ignite Funding FRQ-S Vision Health Research Network Pilot Training opportunities available for undergraduate (PSYC-396/COGS-444/COGS-401) and graduate students , with current advisees working on topics including: Visual snow syndrome neural mechanisms Binocular imbalance in aging Contour integration modeling Adaptive strategies in amblyopia Dichoptic ebook therapy development

• Machine Learning
• Computer Vision
• Structural Health Monitoring
• +1 more

Senjian An is a Senior Lecturer in the School of Electrical Engineering, Computing and Mathematical Sciences at Curtin University, Faculty of Science and Engineering. His research focuses on machine learning, computer vision, and structural health monitoring, with applications in 3D displacement measurement and anomaly detection. Key interests include physics-guided neural networks, unsupervised learning for time-series data, and vision-based structural analysis. His recent publications emphasize robustness in damage detection, synthetic data generation, and transformer-based models for industrial monitoring. An's work integrates deep learning with engineering challenges, advancing non-contact measurement techniques for civil infrastructure. No students or awards are noted. Collaborative projects involve vibration analysis and maritime surveillance, reflecting a strong applied focus in AI and computer vision.

Haibo LiView profile

Professor

• Media Technology
• Digital Signal Processing
• Image and Video Compression
• +5 more

Haibo Li is a Full Professor of Media Technology at KTH Royal Institute of Technology, affiliated with the School of Electrical Engineering and Computer Science and Digital Futures Faculty. His roles include leading the Media Lab in MID, directing Master’s programs in Media Technology, and teaching courses like Generative AI for Media Technology and Video Technology. He holds a Technical Doctorate from Linköping University (1993) and received the Nordic Best PhD Thesis Award (1994) and Docent title in Image Coding (1997). Research focuses on digital media technologies, including image/video compression, human-computer interaction, and AI-driven media systems. He pioneered the Digital Media Lab at Umeå University and co-founded UCIT. His work spans blind image deblurring, thermal comfort sensing, and multimodal emotion recognition. Over 250 publications and six patents highlight contributions to multimedia, AI, and signal processing. Key projects include developing contactless thermal measurement systems for smart buildings, real-time gesture recognition for wearable devices, and advanced neural networks for image restoration. Awards include the Nordic Best Thesis and leadership in EU projects. He chairs conferences and actively participates in MPEG standardization efforts.

• Inverse Problems
• Image Processing
• Optimization
• +5 more

Markus Grasmair is a Professor at the Department of Mathematical Sciences at the Norwegian University of Science and Technology (NTNU). His research focuses on inverse problems, mathematical methods in image processing, and optimization. He has contributed to nonsmooth variational methods and Lavrentiev regularization for ill-posed problems. Education: Habilitation in Mathematics (University of Vienna, 2011), PhD in Mathematics (University of Innsbruck, 2006), MSc in Mathematics (University of Innsbruck, 2003). Markus's research spans mathematical imaging, biomedical applications, and PDE-based modeling. He has developed regularization techniques for inverse problems, including Lavrentiev and L1 methods, and applied these to medical imaging and cervical cancer risk stratification. His work integrates sparse optimization, shape analysis, and data-driven approaches. Recent publications highlight interdisciplinary trends, combining inverse problems with medical imaging (X-ray calibration, cervical cancer prediction) and extending variational methods to PDEs, multiscale modeling, and graph-based systems. Key subfields include monotone operators, matrix factorization, and elastic shape analysis. He teaches courses in optimization and has held academic positions at the University of Vienna, Catholic University of Eichstätt-Ingolstadt, and University of Innsbruck. Contact: markus.grasmair@ntnu.no. Current Role: Professor (NTNU) Past Roles: Substitute Professor (Catholic University of Eichstätt-Ingolstadt, 2012-2013), Assistant Professor (University of Vienna, 2009-2012)

Yannick BlandinView profile

Professor

• Motor Learning
• Sensorimotor Integration
• Observational Learning
• +3 more

Professor Yannick Blandin is affiliated with the University of Poitiers (Faculty of Sports Sciences) and the Center for Research on Cognition and Learning (CeRCA) . His work focuses on motor learning mechanisms, observational learning, mental imagery, and feedback systems in sensorimotor integration. Ph.D. in Physical Activity Sciences (University of Montreal, 1994, directed by Dr. Luc Proteau) Current research themes: specificity of practice, eye movement analysis, point-light display applications His publications reveal trends in sensorimotor coding , motor sequence acquisition , and visual feedback optimization , often intersecting neuroscience , psychology , and sports rehabilitation . He has developed the PLAViMoP platform for visualizing and modifying motor sequences. International collaborations include Dr. Stefan Panzer (Saarland University) and Dr. Charles Shea (Texas A&M). His research spans applications in stroke rehabilitation , athletic training , and cognitive-motor interfaces .

• Structural Dynamics
• Railway Structural Dynamics
• Structural Health Monitoring
• +7 more

Anders Rønnquist is a Professor and Head of the Department of Structural Engineering at NTNU’s Faculty of Engineering Science. His research focuses on structural dynamics, railway systems, and bridge engineering. He leads projects on structural health monitoring, wind engineering, and architectural collaboration in structural design. Key collaborations include work with KTH Stockholm, Vilnius University, and the University of Porto. He teaches courses such as Structural Dynamics, Steel Structures II, and Railway Catenary Systems. His work integrates advanced sensor technologies, machine learning, and probabilistic methods to address challenges in infrastructure longevity and safety. Research interests span structural monitoring, overhead contact line dynamics, and reliability assessments. Notable contributions include the development of Kalman filter-based systems for crosswind load identification and shape grammar approaches for architectural-structural design integration. His team has pioneered non-contact measurement techniques using digital image correlation and advanced neural networks for bridge rivet inspection. Publications highlight innovations in railway catenary optimization, timber structure dynamics, and probabilistic fatigue analysis. His work emphasizes interdisciplinary approaches, bridging engineering and architectural disciplines to enhance sustainable infrastructure solutions.