جست‌وجوی استاد و پژوهشگر

• Neural Oscillations
• Computational Neuroscience
• EEG/MEG Analysis
• +۳ مورد دیگر

Thomas Donoghue is a researcher in the Department of Cognitive Science at the University of California, San Diego, specializing in neural oscillations and computational neuroscience methods. His work focuses on developing rigorous approaches for analyzing brain signals, particularly EEG and MEG data. Dr. Donoghue's research interests center on understanding the methodological considerations for studying neural oscillations, with particular emphasis on verifying the presence of oscillations, validating oscillation band definitions, and accounting for concurrent non-oscillatory aperiodic activity. His work addresses critical issues in the field such as temporal variability, waveform shape of neural oscillations, and separating spatially overlapping rhythms. His publication record demonstrates expertise in developing computational tools for neural signal processing, including contributions to the NeuroDSP software package. His research bridges theoretical neuroscience with practical methodological considerations for interpreting neural data. Dr. Donoghue has received funding support from the Halıcıoğlu Data Science Institute Fellowship, National Science Foundation (BCS-1736028), and National Institute of General Medical Sciences (R01GM134363-02). His collaborative work extends across multiple research groups at UCSD, including the Neurosciences Graduate Program, Halıcıoğlu Data Science Institute, and Kavli Institute for Brain and Mind.

Guus Smitمشاهده پروفایل

استاد

• Neuroscience
• Proteomics
• Alzheimer's Disease
• +۵ مورد دیگر

Prof. Guus Smit is a Full Professor at the Vrije Universiteit Amsterdam (VU), holding appointments in the Faculty of Science, Center for Neurogenomics and Cognitive Research (CNCR), and Amsterdam Neuroscience (divisions: Cellular & Molecular Mechanisms and Neurodegeneration). He specializes in synaptic biology, neurodegenerative disorders, and proteomics. His research focuses on molecular mechanisms underlying Alzheimer’s disease, schizophrenia, and synaptic dysfunction, with over 370 peer-reviewed publications. He teaches courses including Cell Biology, Neurogenomics, and From Molecule to Mind. Key research areas include synaptic protein complexes, neurodevelopmental processes, and biomarker discovery for neurological diseases. His work contributes to UN Sustainable Development Goals related to health and well-being. Smit collaborates internationally and leads projects analyzing genetic overlaps in neurodegenerative diseases. He has supervised 59 PhD theses and contributed to datasets on Alzheimer’s proteomics and centenarian neuropathology. His recent publications (2025) address neuropeptide secretion mechanisms, SFRP1-driven synaptic dysfunction in Alzheimer’s, glycine receptor proteomics, schizophrenia-immune links, and hippocampal memory engram studies. He actively shares data via platforms like Figshare and engages in open-access publishing.

Greg Zaharchukمشاهده پروفایل

استاد

• Neuroimaging
• Radiology
• Artificial Intelligence in Medical Imaging
• +۴ مورد دیگر

Greg Zaharchuk is a Professor of Radiology specializing in Neuroimaging and Neurointervention at Stanford University's School of Medicine. His academic roles include leadership in clinical and translational imaging research. He holds an MD from Harvard Medical School, a PhD in Applied Physics from Harvard/MIT, and dual undergraduate degrees in Materials Science & Engineering and German Studies from Stanford. Education: MD, Harvard Medical School (2000) PhD, Harvard/MIT (1999) BS & BA, Stanford (1990) Research Focus: Dr. Zaharchuk's work centers on advancing neuroimaging techniques for cerebrovascular diseases, stroke, and neurodegenerative disorders. He pioneers AI-driven innovations in MRI/PET fusion, low-dose imaging, and deep learning models to enhance diagnostic accuracy and clinical decision-making. Key areas include stroke outcome prediction, amyloid PET reconstruction, and cross-modality imaging integration. Research Trends: His recent articles emphasize AI applications in neuroimaging, such as improving low-field MRI quality and PET reconstruction using MRI priors. He also explores stroke lesion segmentation, CBF quantification, and the ethical implications of AI in neuroradiology. Affiliations & Labs: He leads the Center for Advanced Functional Neuroimaging at Stanford, advancing cutting-edge imaging technologies. His research bridges clinical practice and innovation, addressing challenges in ischemic stroke, Alzheimer's imaging, and radiation dose reduction. Grants & Collaborations: His work is supported by NIH grants and industry partnerships, focusing on multimodal imaging systems and AI-driven diagnostics. Collaborations include international neuroradiology societies and interdisciplinary teams in neurology and computer science.

• Rhythm Perception
• Pattern Recognition
• Music and Entrainment
• +۳ مورد دیگر

Nashra Ahmad is a Research Fellow at Durham University, affiliated with the Department of Music and the Institute for Medical Humanities. She is a PhD candidate supported by the Durham Doctoral Studentship and holds a Master's in Cognitive Science from IIT Gandhinagar (2021) and a BA in Psychology (First Class Honours) from Aligarh Muslim University (2018). Her research focuses on rhythm perception, consonance/dissonance dynamics, and music cognition, combining neuroscience and interdisciplinary approaches. She is an active member of the Music and Science Lab and an editorial assistant for DURMS . Additionally, she teaches Psychology at the Durham Centre for Academic Development (DCAD). Key research interests include: rhythmic entrainment in North Indian classical music, sensorimotor synchronization, and neural correlates of musical perception. Her work bridges cognitive science, musicology, and technology, with publications in Data in Brief , Frontiers in Neurorobotics , and Music & Science . Awards include the Sabarmati Bridge Fellowship (2021) for pre-doctoral research and the Durham Doctoral Studentship (2022). Education: Bachelor of Arts in Psychology (First Class Honours), Aligarh Muslim University, 2018 Masters in Cognitive Science, Indian Institute of Technology Gandhinagar, 2021 Her publications analyze EEG responses to music, resonance strategies in AI design, and beat prediction from neural data. She has presented at international conferences such as the International Conference of Students of Systematic Musicology (2023) and the Max-Planck-Institut für empirische Ästhetik (2022). Awards: 2022: Durham Doctoral Studentship 2021: Sabarmati Bridge Fellowship Teaching and Outreach: She teaches Psychology to foundation-year students at DCAD and has prior experience teaching guitar and music theory in India. Her creative interests include landscape painting and sculpting, reflecting her interdisciplinary engagement with art and science.

Nidhi Sofatمشاهده پروفایل

استاد

• Rheumatology
• Osteoarthritis
• Inflammation Mechanisms
• +۵ مورد دیگر

Professor Nidhi Sofat is a Professor of Rheumatology at St George's, University of London, and a Consultant Rheumatologist at St George's University Hospitals NHS Foundation Trust. She leads the NIHR Integrated Academic Programme for Clinical Academic Trainees, overseeing research and training programs such as the PGCert in Research Skills and Methods. She qualified in medicine from University College London (1996) with First Class Honours, completed specialist rheumatology training in 2007, and earned her PhD from the Kennedy Institute of Rheumatology (Imperial College London). Her research focuses on understanding pain and inflammation in musculoskeletal diseases, particularly osteoarthritis and rheumatoid arthritis. Her group pioneered the Osteoarthritis Bone Score (OABS), the first histological scoring system for bone marrow lesions in osteoarthritis. Key research areas include mechanisms of pain sensitization, imaging techniques (MRI), clinical trials (e.g., DUPRO, PAPO), and collaborations with institutions like the University of Nottingham and Royal Veterinary College. She has received awards such as the Michael Mason Prize (2013) and Wellcome Trust Fellowship (2003). Her clinical roles include managing general rheumatology, inflammatory arthritis, and osteoarthritis at the Hotung Centre. She has contributed to national guidelines via the Arthritis and Musculoskeletal Alliance (ARMA) and served on committees like the British Society for Rheumatology's Heberden Committee. Major grants include funding from NIHR, Versus Arthritis, and the Wellcome Trust. Collaborations span academic and industry partners, including Pfizer and Merck. Her translational research facility bridges clinical and experimental work, aiming to improve diagnostic tools and therapies for arthritis.

Moo Chungمشاهده پروفایل

استاد

• Computational Neuroimaging
• Topological Data Analysis
• Brain Networks
• +۵ مورد دیگر

Moo Chung is a Professor of Biostatistics and Medical Informatics at the University of Wisconsin-Madison, affiliated with the School of Medicine and Public Health. He holds additional appointments in the Department of Statistics and the College of Letters and Science. Chung earned his Ph.D. in Mathematics and Statistics from McGill University under Professors Keith J. Worsley and James O. Ramsay. His research focuses on computational neuroimaging, leveraging MRI, fMRI, and DTI to study brain dynamics through topological and geometric methods. Key areas include persistent homology, brain network analysis, and statistical modeling of high-dimensional imaging data. He has pioneered methods like hyper-network construction and exact topological inference for paired brain networks, addressing computational challenges in analyzing large-scale neuroimaging datasets. Chung’s work integrates advanced mathematical techniques such as Hodge Laplacian, spectral graph theory, and Wasserstein distances to analyze brain connectivity. He has secured NIH funding for projects like the Brain Initiative (2017-2020) and current grant MH133614 (2023), focusing on geometric data analysis and topological dynamics. His contributions include three books on brain imaging and network analysis, with ongoing research on topological data analysis applications. Awards: Vilas Associate Award (2013-2014), NIH Brain Initiative Award, Editor's Award (2011) Labs/Teams: Leads brain imaging workshops globally, including Seoul National University (2024) and POSTECH (2024), and organizes conferences like ISBI and MICCAI special sessions. Grants: NIH EB022856 (Brain Initiative), MH133614 (2023), and collaborations with institutions like Vanderbilt University and University of Chicago. Chung actively mentors students and postdocs in biomedical data science, offering fellowships through the CIBM program. His group maintains a Google mailing list for brain image analysis discussions and hosts regular seminars on methodological advancements.

• Biomedical Data Computing
• Medical Image Processing
• Image Registration
• +۴ مورد دیگر

Associate Professor Xiu Wang is affiliated with the School of Computer Science at The University of Sydney, where she serves as Associate Director of the Multimedia Lab and a member of the Biomedical & Multimedia Information Technology (BMIT) Research Group. Her research focuses on panoramic data analysis, biomedical computing, image processing, and medical data fusion. Key projects include tumor treatment outcome prediction using deep learning, collaborative learning of multimodal medical imaging, and deformable image registration techniques. She teaches courses such as COMP5214 (Software Development in Java) and supervises graduate students in AI-driven medical diagnostics and imaging. Notable collaborations involve Dr. Hui Cui and Mr. Chaojie Zheng. Her work bridges computer science and healthcare, emphasizing AI applications in oncology, radiology, and neuroimaging. Recent articles highlight advancements in MRI segmentation, PET/CT radiomics, and graph neural networks for disease diagnosis. She actively contributes to interdisciplinary research, integrating computational methods with clinical data for precision medicine.

Uri Maozمشاهده پروفایل

دانشیار

• Computational Neuroscience
• Neuroethics
• Volition and Decision-Making
• +۶ مورد دیگر

Dr. Uri Maoz is an Associate Professor at Chapman University, affiliated with the Crean College of Health and Behavioral Sciences, Schmid College of Science and Technology, and Fowler School of Engineering. His research bridges computational neuroscience, decision-making, and moral philosophy, focusing on volition and the neural underpinnings of conscious action. He holds visiting roles at UCLA (Department of Anesthesiology) and Caltech (Biology and Bioengineering). Educations: Bachelor of Science in Computer Science and General Humanistic Studies, The Hebrew University of Jerusalem Ph.D. in Neural Computation, The Hebrew University of Jerusalem Research Interests: Dr. Maoz investigates how consciousness influences voluntary actions through empirical methods (EEG, intracranial recordings) and theoretical models. He explores ethical and legal implications of neuroscience, particularly regarding free will and decision-making. His work integrates machine learning for real-time neural data analysis. Key Projects: Leading the COVID-Dynamic longitudinal study on pandemic-related behavioral and emotional changes. Developing computational models of volition and neural correlates of intention. Collaborating across disciplines to address neuroethical questions. Visiting Roles: Visiting Assistant Professor at UCLA’s Department of Anesthesiology Visiting Associate in Biology and Bioengineering at Caltech Labs/Teams: Active in Chapman’s Institute for Interdisciplinary Brain and Behavioral Sciences and collaborates with the Anderson School of Management at UCLA.

Nilay Patelمشاهده پروفایل

دانشیار

• Drug Discovery
• Cell Cycle Regulation
• Signal Transduction
• +۳ مورد دیگر

Dr. Nilay Patel is an Associate Professor in the Department of Biological Science at California State University, Fullerton (CSUF). His research focuses on drug discovery, particularly the anti-proliferative effects of niclosamide and related compounds on cancer cells, with collaborations in chemistry and biochemistry. He investigates signal transduction pathways and gene expression regulation in cell cycle processes. Dr. Patel teaches courses in cellular/molecular biology, stem cell biology, and related advanced topics. Education: PhD, The State University of New York, Stony Brook BS, University of Cincinnati Research Interests: Design and testing of anti-cancer compounds targeting β-catenin reduction Impact of signal transduction pathways on cancer proliferation Collaborative drug development with CSUF Chemistry & Biochemistry Department Publications Trends: His work bridges pharmacology and cell biology, emphasizing stem cell pluripotency, neurodegenerative disease mechanisms, and aging-related biomarkers. Key themes include caloric restriction effects on amyloid accumulation and glial cell functions. Awards/Grants: Bridges to Stem Cell Research (BSCR) Program Advising & Mentorship: Supervised multiple student co-authors in stem cell and cancer biology research projects. Active in training through internships (BIOL 495C) and advanced seminars.

Eunsik Kimمشاهده پروفایل

استاد

• Ergonomics
• Biomechanics
• Human Factors Engineering
• +۵ مورد دیگر

Eunsik Kim is a Professor at the University of Windsor , holding a position in the Department of Mechanical, Automotive, and Materials Engineering within the Faculty of Engineering . His research focuses on ergonomics, occupational safety, and biomechanics, with applications in automotive design, workplace safety, and human-machine interaction. He leads the Occupational Safety and Ergonomics research lab , where students explore real-world solutions for challenges such as driver fatigue, musculoskeletal risks in manual labor, and automation in agriculture. Key research interests include: Ergonomics : Optimizing workstation designs, automotive seating, and anti-vibration tools Biomechanics : Analyzing human posture, musculoskeletal loading, and workplace ergonomics Machine Learning : Developing AI-driven systems for posture recognition, workload prediction, and task automation Autonomous Vehicles : Investigating human factors in driving automation and takeover scenarios Education Innovation : Gamification in engineering labs to enhance student motivation and learning Collaborations include projects with Ewha Womans University (South Korea) on autonomous vehicle comfort and a prototype robotic system for mushroom harvesting. His work often bridges theoretical research with practical applications, addressing both industry and academic challenges. Awards and Recognition: Students Ilfeoma Michael and Elnaz Akhavan Rezaee received accolades at the Association of Canadian Ergonomists conference for their lab research Advising and Grants: Professor Kim mentors students in interdisciplinary projects, focusing on ergonomics, robotics, and AI. His research has led to innovations in workplace safety and automated systems, supported by institutional and collaborative funding. Labs/Teams: The Occupational Safety and Ergonomics Lab and partnerships with South Korean institutions drive cutting-edge studies in automotive safety, robotics, and human factors engineering.

Nitish V. Thakorمشاهده پروفایل

استاد

• Biomedical Engineering
• Neuroengineering
• Neural Prosthetics
• +۵ مورد دیگر

Nitish V. Thakor is a Professor of Biomedical Engineering and Neurology at Johns Hopkins University School of Medicine, with secondary appointments in Electrical and Computer Engineering. He directs the Laboratory for Neuroengineering and oversees the NIH Neuroengineering Training Grant. His research focuses on neural prosthetics, brain-machine interfaces, and clinical neurorehabilitation technologies. Education: B.Tech from IIT Bombay (India), M.S. and Ph.D. in Biomedical Engineering from University of Wisconsin-Madison Joined Johns Hopkins faculty in 1983 Research emphasizes translational neuroengineering: developing prosthetic limbs with sensory feedback, advanced neural interfaces, and diagnostic technologies for brain injury monitoring. The lab integrates microfabrication, stem cell biology, and integrated circuit design with clinical applications. Notable projects include DARPA-funded advanced prosthetic systems and temperature-sensitive prosthetic fingertips. Recent lab milestones include robotic hand research published in Science Advances, and student achievements like NIH fellowships and Siebel Scholar awards. Honors: IEEE Fellow (1997), AIMBE Fellow (1996), NSF Presidential Young Investigator (1985) Advising over 20 students/postdocs, he also serves as editor-in-chief of Medical and Biological Engineering and Computing . Active in global biomedical engineering outreach through conferences and educational programs.

Hina Shaheenمشاهده پروفایل

استادیار

• Bio-statistics
• Neuroscience Data Analysis
• Computational Modelling
• +۹ مورد دیگر

Hina Shaheen is an Assistant Professor in the Department of Statistics , Faculty of Science, University of Manitoba. Her research integrates statistical methods with computational neuroscience and neurodegenerative disease modeling. Email: Hina.Shaheen@umanitoba.ca Lab: NeuroStats Lab Research Interests: Shaheen specializes in neurodegenerative disorders like Alzheimer’s and Parkinson’s disease, with a focus on: Multiscale and network modeling of brain dynamics Bio-statistical and machine learning approaches BAYESIAN inference and STOCHASTIC processes Calcium signaling and PROTEIN dynamics in disease pathology Publication Trends: Recent work combines data-driven stochastic modeling with connectomic insights to study neurodegenerative mechanisms. Key themes include: Integration of machine learning and BAYESIAN frameworks in brain network analysis Applications to Alzheimer’s (amyloid-beta/calcium interactions, exosomal spread) and Parkinson’s (DBS treatment, neural dynamics) Development of multiscale co-simulation techniques for clinical data interpretation Academic Engagement: Shaheen actively mentors graduate students and collaborates across disciplines. She participated in the V AMMCS International Conference (2019) and maintains affiliations with computational neuroscience communities.

Jordan J. Williamsمشاهده پروفایل

استادیار

• Neural Engineering
• Optogenetics
• Biomedical Engineering
• +۵ مورد دیگر

Jordan J. Williams is an Assistant Professor and Director of the Neural Engineering & Modulation Laboratory (NEMo Lab) at the Joint Department of Biomedical Engineering, affiliated with Marquette University and the Medical College of Wisconsin. He holds MD and PhD degrees from Washington University in St. Louis and completed postdoctoral work at the University of Pittsburgh. Education: Postdoctoral Scholar (2013-2019), Systems Neuroscience Institute, University of Pittsburgh MD (2013), Washington University in St. Louis PhD (2013), Biomedical Engineering, Washington University in St. Louis B.S. (2005), Electrical Engineering and Engineering Physics, South Dakota State University His research focuses on neural engineering, optogenetics, and brain-machine interfaces. Key projects include peripheral optogenetic stimulation for motor recovery post-spinal cord injury, neuroprosthetics, and viral gene therapy applications. Recent publications highlight advancements in spatiotemporal nerve stimulation patterns, non-human primate studies, and neural interface biocompatibility. Dr. Williams teaches courses like Neural Engineering , Biomedical Signal Processing , and Control Systems for Biomedical Engineering . His funded grants include projects on functional motor recovery and improved spinal cord injury rehabilitation through optogenetics. Current research emphasizes the intersection of neuroscience and engineering to address paralysis, with a strong focus on translating preclinical findings into clinical applications. His work has been published in journals such as Journal of Neuroscience Methods , Science Robotics , and Frontiers in Neuroscience .

• Biomedical Signal Processing
• Computational Neuroscience
• Brain-Computer Interfaces (BCI)
• +۷ مورد دیگر

David B. Grayden is a Professor at The University of Melbourne, affiliated with the Melbourne School of Engineering and the Department of Electrical and Electronic Engineering . His work spans Biomedical Signal Processing , Computational Neuroscience , and Brain-Computer Interfaces (BCI) , focusing on applications in Epilepsy Research and Cochlear Implants . Melbourne Neural Engineering Laboratory member Collaborator in multidisciplinary biomedical research Key research interests include: Developing Seizure Prediction Algorithms using long-term EEG/iEEG data Neural mass modeling for Epilepsy and Inhibitory Network Behavior Optimizing Cochlear Implants via computational models Advancing Endovascular BCI Systems and Neural Stimulation Recent publications highlight trends in Machine Learning , Path Signatures , and Multi-Frequency Stimulation for SSVEP-based BCIs . His work integrates Computational Modeling with Biomedical Engineering to address clinical challenges in neuroprosthetics and sensory processing. Grayden leads projects on Neural Network Dynamics , Biomedical Signal Analysis , and Neurostimulation , often collaborating with institutions like Monash University and Royal Melbourne Hospital .

Peter Bienstmanمشاهده پروفایل

استاد

• Photonics
• Neuromorphic computing
• Nanophotonics
• +۱۱ مورد دیگر

Peter Bienstman is a full professor at Ghent University, working in the Department of Information Technology (INTEC) where he has been since 1997. He is affiliated with the Photonics Research Group and also collaborates with imec. His research spans nanophotonics, neuromorphic computing, and biosensing applications. Bienstman received his electrical engineering degree from Ghent University in 1997 and completed his Ph.D. at the same institution in 2001. His doctoral work focused on "Rigorous and efficient modelling of wavelength scale photonic components." His research interests primarily revolve around nanophotonics and its applications, with specific focus areas including: Photonic Reservoir Computing for neuromorphic information processing Optical label-free biosensors based on ring resonators TE/TM biosensors for measuring conformational changes SiN biosensors operating in the visible spectrum Optical spiking neurons and neuromorphic architectures Nanophotonic information processing systems Analysis of his recent publications reveals a strong focus on advancing photonic reservoir computing for practical applications, particularly in communications signal processing and biomedical sensing. His work demonstrates how photonic systems can implement neuromorphic computing paradigms with energy efficiency advantages over traditional electronics. Recent trends show increasing integration of phase-change materials and exploration of quantum-inspired photonic computing approaches. Bienstman has received significant recognition for his work, most notably an ERC Starting Grant for the Naresco-project: "Novel paradigms for massively parallel nanophotonic information processing." This prestigious European grant supports his innovative research at the intersection of photonics and computing. As an advisor, Bienstman has supervised numerous doctoral students to completion and currently mentors a large research group with nine active PhD students and two postdoctoral researchers. His research is supported by multiple grants that enable the development of novel photonic computing architectures and biosensing platforms. The group's work bridges fundamental photonics research with practical applications in communications, healthcare, and computing. The Photonics Research Group at Ghent University, where Bienstman works, maintains state-of-the-art facilities for nanophotonic device design, fabrication, and characterization. The group collaborates extensively with imec and other international research institutions, creating a vibrant ecosystem for advancing photonic technologies from fundamental research to potential commercial applications.