جست‌وجوی استاد و پژوهشگر

Fan Wangمشاهده پروفایل

استاد مدعو

• Neuroscience
• Neural Circuits
• Pain Research
• +۴ مورد دیگر

Fan Wang is an Adjunct Professor in the Department of Neurobiology at Duke University since 2021. She is also a Faculty Network Member of the Duke Institute for Brain Sciences (2008–Present) and an Affiliate of the Duke Regeneration Center (2021–Present). Her research focuses on the neural circuit basis of sensory perception, including active touch sensation , pain processing , and anesthesia-induced unconsciousness . Using genetic, viral, electrophysiological, and in vivo imaging techniques, her lab investigates tactile motor control, pain suppression mechanisms, and consciousness modulation. Ph.D., Columbia University (1998) Research trends in recent publications span neural circuit mapping , AI-driven drug design , and medical imaging innovations . Key areas include anesthesia mechanisms , pain suppression pathways , 3D dental modeling , and GABAergic neuron function in the brain stem. Collaborative work extends to computational toxicology , graph neural networks , and green pesticide design using machine learning. Scientific recognition includes the AAAS Fellowship (2014) and the Sloan Research Fellowship in Neuroscience (2004). Media coverage highlights breakthroughs such as the discovery of a potent pain-suppression center in the brain (2020) and advancements in cortical parcellation (2022). Her grants include multiple National Institutes of Health awards (1997–2022) and support from the W.M. Keck Foundation (2016–2018). Labs and teams at Duke, including the Duke Institute for Brain Sciences , collaborate on projects spanning neuroanatomy , computational biology , and environmental toxicology . Current work integrates AI tools for cortical parcellation, protein-ligand affinity prediction , and multi-agent reinforcement learning for biomedical applications.

• Geology
• Geophysics
• Physical Geography and Environmental Geoscience
• +۵ مورد دیگر

Dr. Jeffrey Moore is a Professor in the Department of Geology & Geophysics at the University of Utah, where he leads the Geohazards research group. His work focuses on the mechanics of natural hazards, particularly rock slope failure, structural health monitoring of freestanding rock landforms, and landslide hazard assessment. With a PhD in Civil Engineering from UC Berkeley (2007), Moore has held academic positions at the University of Utah since 2013, advancing to Professor in 2024. He previously conducted research at ETH Zurich on rock slope monitoring. University of Utah, College of Engineering (2013–present) PhD in Civil Engineering, UC Berkeley (2007) Moore’s research integrates field observations, ambient vibration monitoring, and numerical modeling to study rock mechanics, slope stability, and alpine geomorphology. His group specializes in structural health monitoring of rock arches and towers, using seismic resonance to detect damage progression. Current projects examine climate-driven rock slope instability, anthropogenic vibration impacts on geological structures, and hydromechanical effects of glacial cycles. Rock Slope Failure Mechanisms Seismic Resonance Monitoring Climate Change Geohazard Assessment Topographic Amplification Studies His recent publications analyze fracture-controlled resonance modes, insolation-driven frequency drifts, and multi-stage landslide dynamics. Grants include NSF funding for structural health monitoring of national park arches and DOST grants for seismic characterization of rock instabilities. Moore received the L. Jackson Newell Liberal Arts and Sciences Fellowship in 2020. Teaches graduate thesis research courses Offers field geology and dynamic earth instruction Develops geologic engineering curricula

Douglas L. Altshulerمشاهده پروفایل

استاد

• Avian Flight Biomechanics
• Visuomotor Control Systems
• Neurophysiology of Optic Flow
• +۳ مورد دیگر

Douglas L. Altshuler is a Professor in the Department of Zoology at the University of British Columbia , where he leads research in Faculty of Science . His work bridges neurophysiology , biomechanics , and visual ecology to understand avian flight control. Education : BA in History (University of California, Santa Cruz), MSc in Biological Sciences (Purdue University), PhD in Zoology (University of Texas at Austin), Postdoctoral Fellow in Bioengineering (Caltech) Research Focus : Investigates how birds use optic flow for flight stabilization and maneuverability, with specialized work on hummingbird visual systems and zebra finch neuroanatomy . Current projects examine visuomotor control and dynamic wing morphing . Scientific Contributions : 15 most recent articles reveal trends in avian flight biomechanics and visual-neural integration , exploring topics like aeroelastic wing effects , visual motion compensation , and evolutionary metabolic adaptations . Awards : Excellence in Service Award (2024) Stockard Seminar (2020) Lawrence R. Blinks Lecture (2018) Killam Memorial Fund (2017) Peter Wall Scholar (2016) HFSP Awardee (2013) George A. Bartholomew Award (2007) Labs & Collaborations : Leads the Altshuler Lab , collaborating with institutions like Caltech, University of Alberta, and Carleton University. Research integrates neuroanatomy , biomechanics , and comparative physiology to decode flight control circuits.

Nathan B. Gawمشاهده پروفایل

استادیار

• Machine Learning
• Multimodal Data Fusion
• Healthcare Telemonitoring
• +۷ مورد دیگر

Dr. Nathan B. Gaw is an Assistant Professor of Data Science at the Air Force Institute of Technology (AFIT), where he develops advanced statistical machine learning algorithms for multimodal data fusion in defense, healthcare, and remote sensing applications. He holds a Ph.D. in Industrial Engineering from Arizona State University (2019) and completed postdoctoral research at both the ASU-Mayo Clinic Center for Innovative Imaging (2019-2020) and Georgia Institute of Technology's School of Industrial and Systems Engineering (2020-2021). Research Interests: His work focuses on three core areas: Feature extraction/selection using tensor decomposition and functional data analysis Spatio-temporal neural networks with attention-based ConvLSTMs Image registration/fusion through convolutional neural networks Key application domains include aviation human factors, weather remote sensing, and cybersecurity. Scientific Awards: Dr. Gaw has received 14 major scientific awards including: AFWERX Datathon Challenge (5 awards) INFORMS Principal Cup (2nd place) Harold Wolff-John Graham Award (American Academy of Neurology) Tau Beta Pi Fellowship Dean's Fellowship, ASU Professional Engagements: He serves as chair of the INFORMS Data Mining Society and council member of IISE Data Analytics Division, while maintaining IEEE membership. His 16 peer-reviewed publications (12 Q1, 4 Q2) include a U.S. patent and book chapter contributions.

• Neural Signal Processing
• Machine Learning for Neuroscience
• Brain Network Modeling
• +۵ مورد دیگر

Dr. Quanying Liu serves as Associate Professor in the Department of Biomedical Engineering at Southern University of Science and Technology (SUSTech), where she leads the Neural Computing and Control Laboratory (NCC lab) as Principal Investigator and Doctoral Supervisor. Her academic journey includes a PhD from ETH Zurich in Biomedical Engineering, postdoctoral training at Caltech, and research positions at Huntington Medical Research Institute, KU Leuven, and Oxford University. PhD in Biomedical Engineering, ETH Zurich (2013-2017) Master in Computer Science, Lanzhou University (2010-2013) Bachelor in Electrical Engineering, Lanzhou University (2006-2010) Dr. Liu's research bridges neuroscience, machine learning, and control theory with focus on multi-modal neural signal processing (EEG, sEEG, fMRI, DTI), explainable AI for brain interpretation, and optimization frameworks for neuromodulation (tES, TMS). Her work develops high-density EEG source imaging algorithms, data-driven brain network modeling, and control-theoretic approaches for neural stimulation. The NCC lab specializes in machine learning algorithms, neural computation, multimodal data fusion, network control theory, and bidirectional brain-computer interfaces. Analysis of her recent publications reveals strong trends in EEG-based visual decoding, multimodal neural embeddings, and AI-driven brain network modeling. Her work increasingly integrates generative models for neural data synthesis, control theory for precise neuromodulation, and cross-modal approaches connecting neural signals with cognitive functions. The New Brain 30 (2023) AAIC travel award (2019) Estes Stars Award (2018) Shenzhen Peacock Talent Plan C Dr. Liu actively mentors students through SUSTech's doctoral program and leads multiple significant research initiatives including a National Natural Science Foundation Youth Project, a National Key R&D Program in Bio-Information Fusion, and several Shenzhen municipal projects. Her lab receives funding from Guangdong Provincial Basic Research Fund, Shenzhen Science and Technology Innovation Commission, and international fellowships including Boswell Postdoctoral Fellowship and Swiss National Science Foundation grants. The NCC lab maintains strong international collaborations with Caltech, ETH Zurich, and Oxford University while developing novel platforms like WheelCon for sensorimotor control studies. The Neural Computing and Control Laboratory operates as an interdisciplinary hub integrating computational neuroscience, machine learning, and control engineering. The lab develops specialized hardware-software systems for closed-loop neurostimulation, maintains the EEGdenoiseNET benchmark dataset, and pioneers methods like MOVEA for transcranial electrical stimulation optimization. Current research directions include generative models for neural decoding, network control theory applications, and AI-human cognitive interaction frameworks.

Martin Mayfield-Tulipمشاهده پروفایل

استاد

• Sustainable Engineering
• Systems Engineering
• Climate Change Mitigation
• +۳ مورد دیگر

Professor Martin Mayfield-Tulip is the Head of the School of Mechanical, Aerospace and Civil Engineering at the University of Sheffield. As an academic leader with 24 years of industrial experience, he focuses on sustainable infrastructure systems, systems engineering, and climate resilience. His work spans urban metabolism, energy systems, and resource accounting frameworks. Lead researcher in sustainable infrastructure and urban systems Director of EPSRC-funded Sheffield Urban Flows Observatory Co-founder of the RISE research group (14 members) His research integrates complexity science with engineering design, emphasizing the interaction between human and natural systems. Key areas include: Climate resilience of infrastructure networks Smart grid integration with buildings Computer vision applications for urban material stocks Low-cost sensor networks for air quality monitoring Multi-modal energy consumption prediction Grid constraint management with battery storage Recent publications demonstrate expertise in applying computational methods to urban sustainability challenges. His work bridges theoretical advancements in Gaussian processes and practical implementations in city-scale energy systems. EPSRC ENCORE Network+ Principal Investigator Co-Investigator for UKCRIC initiatives Director of £2.4m Sheffield Urban Flows Observatory Co-Investigator for CORONA £8m UKCRIC Urban Observatories grant Managed i-CAIR £8m Integrated Infrastructure project Mayfield-Tulip leads the Sheffield component of the UKCRIC initiative and serves on multiple infrastructure boards including the Grantham Centre for Sustainable Futures and the Sheffield City Region Infrastructure Board. His RISE research group focuses on the intersection of technology and infrastructure to create sustainable built environments.

• Wood Mechanics
• Non-Destructive Testing
• Materials Engineering
• +۳ مورد دیگر

Stéphane Girardon is an Associate Professor at Arts et Métiers Institute of Technology, affiliated with the College of Engineering. His research focuses on advanced wood characterization techniques, mechanical behavior of lignocellulosic materials, and sustainable structural applications. Develops non-destructive testing methods using terahertz imaging and X-ray analysis Applies deep learning for automated defect detection in wood veneers Investigates fiber orientation influence on mechanical properties Optimizes laminated wood structures for civil and automotive engineering His recent work bridges computational modeling with industrial applications, particularly in the BOOST and WOOPS projects. Publications highlight expertise in: Terahertz spectroscopy for wood density measurement Machine learning-based defect recognition Anisotropic material behavior in timber Optical characterization using tracheid effect Mechanical performance of glued wood-concrete connections Microstructure-scale modeling with Discrete Element Method As part of the LaBoMaP research team, he contributes to eco-materials development for sustainable mobility and construction sectors.

• Transcranial Brain Stimulation
• Non-invasive Neuromodulation
• Computational Electromagnetics
• +۵ مورد دیگر

Angel V Peterchev is a Professor in Psychiatry and Behavioral Sciences, Neurosurgery, Biomedical Engineering, and Electrical and Computer Engineering at Duke University. He directs the Brain Stimulation Engineering Lab (BSEL) and holds affiliations with the Duke Institute for Brain Sciences and MEDx. Harvard University: B.A. (1999) University of California, Berkeley: M.S. (2002), Ph.D. (2005) His research focuses on transcranial brain stimulation (TMS, tACS) device development, computational modeling of neural activation, and integration with robotics, imaging, and machine learning. He has pioneered technologies like ElevateTMS, SAMT software, and noise-reduction TMS coils. Recent publications emphasize multi-scale modeling , motor threshold algorithms , magneto-genetic interfaces , and neuroimaging-guided stimulation . His work bridges power electronics and clinical neuroscience , aiming to enhance TMS precision and therapeutic applications. Scientific accolades include the 2024 Brainbox Initiative John Rothwell Award . He has secured continuous NIH funding since 2008 and collaborated with institutions globally to translate lab developments into clinical practice. His lab, BSEL, develops quiet TMS devices , individualized dose tools , and multi-modal stimulation systems , while maintaining open-source platforms like SimNIBS.

Lawrence Virginمشاهده پروفایل

استاد

• Nonlinear Dynamics
• Structural Mechanics
• Buckling and Snap-Through Behavior
• +۴ مورد دیگر

Lawrence Virgin is a Professor at Duke University's Nonlinear Dynamics Lab in the Thomas Lord Department of Mechanical Engineering and Materials Science, with a secondary appointment in the Department of Civil and Environmental Engineering. Holding a Ph.D. from the University of London (1986), he has published extensively on nonlinear structural behavior, chaos theory, and stability transitions. Education : B.S. (1981) and M.S. (1982) from UK institutions. Research : Focuses on postbuckling dynamics, snap-through phenomena, and applications of nonlinear mechanics in aerospace, civil, and biomedical systems. Awards : Fellow of ASME (2023), Frocht Award (2016), J.P. Davis Award (2012). Teaching : Courses like Advanced Mechanical Vibrations and Aerospace Structures emphasize hands-on learning via 3D-printed models. His article trends revolve around nonlinear structural responses under thermal/mechanical loads, with recent work on 3D-printed demonstration devices and dynamical systems theory. Key subfields include buckling of panels, rotordynamics, chaotic transitions, and educational applications of additive manufacturing. Scientific Recognition : ASME Fellow Frocht Award J.P. Davis Award

Yi Zhangمشاهده پروفایل

استادیار

• Computational Biology
• Bioinformatics
• Machine Learning in Genomics
• +۴ مورد دیگر

Yi Zhang is an Assistant Professor at Duke University with primary appointments in the Department of Neurosurgery and secondary affiliations in Biostatistics & Bioinformatics. As a core member of the Duke Brain Tumor Omics Program and the Duke Cancer Institute, Zhang's research integrates machine learning, genomics, and computational biology to address challenges in tumor microenvironment analysis, human genetics, and immunotherapy. The lab develops methods for single-cell and spatial transcriptomics, focusing on interpretable AI models to dissect multi-cellular disease systems like brain tumors. PhD in Bioengineering from University of Illinois at Urbana-Champaign (2019) Postdoctoral training at Dana-Farber Cancer Institute and Harvard T.H. Chan School of Public Health Research Interests: Machine Learning for Omics: Developing interpretable AI models to analyze single-cell, spatial transcriptomics, and multi-omics data Tumor Microenvironment: Investigating cancer-intrinsic/extrinsic interactions and targetable immunity modulators Human Genetics: Mapping genetic variants to functional genomics mechanisms via integrative methods Scientific Leadership: Zhang's 15 most recent publications (2025-2018) span computational methods (STHD, MetaTiME), tumor-immune dynamics, functional genomics (GWAS integration), and immunotherapy modeling. Key themes include spatial transcriptomics, regulatory variant interpretation, and machine learning-driven drug discovery. Awards: EECS Rising Star, University of Texas Austin (2022) Professional Engagement: Zhang organizes Duke Single Cell Initiative symposia, serves on Duke Cancer Institute review committees, and contributes to editorial/review roles for journals like Bioinformatics and Genetics.

• Neuroscience
• Biomedical Engineering
• Neurotechnology
• +۵ مورد دیگر

Risto Ilmoniemi is a Senior Advisor at the Department of Neuroscience and Biomedical Engineering, Aalto University. He has pioneered innovations in magnetoencephalography (MEG) and transcranial magnetic stimulation (TMS), including the minimum-norm estimate, signal-space projection, and navigated TMS (nTMS). He founded Nexstim Plc, commercializing TMS-EEG and nTMS, and currently leads development of multi-locus TMS (mTMS) and hybrid MEG-MRI systems. His work bridges physics, engineering, and clinical neuroscience. Affiliation : Aalto University, Department of Neuroscience and Biomedical Engineering Expertise : Biodesign, Human brain imaging, Electromagnetism, Neurotechnology, Medical Technology His research focuses on bioelectromagnetism , brain connectivity , and mathematical methods for solving inverse problems in brain signal analysis. He develops closed-loop TMS systems and hybrid imaging modalities like MEG-MRI, with applications in neuroscience and clinical diagnostics. His work emphasizes real-time tractography , electromagnetic modeling , and personalized neuromodulation . The 15 most recent articles highlight his leadership in advancing multi-locus TMS , EEG forecasting , and neuroimaging-guided stimulation . Key trends include state-dependent stimulation protocols , hidden Markov modeling of brain dynamics , and open-source tools for closed-loop systems . Scientific Awards : World Technology Award Finalist in Health & Medicine (2013) Fellow of EAMBES (2015) Finnish Academy of Science and Letters (2008) Innovation of the Year Award (2017) Innosuomi 2004 Prize First prize in Medical Technology competition (1997) His career spans founding a neurotech company, inventing brain imaging techniques, and co-developing MEG , TMS , and hybrid systems . He collaborates with the BioMag Laboratory and Aalto Brain Centre , mentoring researchers in neurostimulation and brain modeling .

Ville Pulkkiمشاهده پروفایل

استاد

• Acoustics
• Signal processing
• Audio
• +۱ مورد دیگر

Ville Pulkki serves as a Professor in the Department of Information and Communications Engineering at Aalto University, Finland, maintaining active research output evidenced by publications extending into 2025. His professional contact details include email (ville.pulkki@aalto.fi) and phone (+358505208392), confirming current institutional affiliation. His research expertise spans: Acoustics (particularly underwater and room acoustics) Signal processing for spatial audio systems Audio codec development and compression Spatial sound perception and localization Analysis of his 15 most recent publications reveals dominant research trajectories: underwater bioacoustics applications using spatial audio and 360° video for marine ecosystem monitoring; advanced spatial post-filtering techniques addressing noise reduction and source separation in complex acoustic environments; perceptually-optimized codecs for higher-order ambisonics compression; and fundamental investigations into sound localization challenges including median plane perception and standing wave interference. His work consistently bridges theoretical signal processing with practical applications in virtual reality, marine biology, and auditory perception. No scientific awards, fellowships, or major prizes are documented in the provided materials. While the source text confirms Professor Pulkki's active research status through ongoing publications, it lacks specific details regarding graduate student supervision, research grants, or laboratory leadership. His extensive publication record across diverse spatial audio domains suggests significant collaborative research activity and potential involvement in funded projects, though concrete evidence of advising relationships or grant management is absent from the available information. Similarly, no dedicated research laboratories, departmental teams, or institutional research groups under his direct leadership are mentioned in the source material, despite the technical depth of his work requiring substantial experimental infrastructure.

Utkarsh Mallمشاهده پروفایل

استادیار

• Computer Vision
• Artificial Intelligence
• Self-Supervised Learning
• +۴ مورد دیگر

Utkarsh Mall is an Assistant Professor at the Mohamed bin Zayed University of Artificial Intelligence (MBZUAI) in Abu Dhabi, UAE, starting Fall 2025. His research focuses on computer vision systems for scientific discovery and domain expert collaboration. Previous affiliations: Columbia University (postdoc), Cornell University (PhD 2023), IIT Bombay (BS 2017), Facebook AI Research (FAIR) (internship 2020) Research directions: Supervision-efficient vision systems (self/semi-supervised learning) Trustworthy AI properties (interpretability, uncertainty estimation) Scientific discovery tools (climate monitoring, fashion analysis, urban mapping) Recent article trends: 60% focus on satellite image analysis (change detection, cloud removal, disaster monitoring) and 40% on fundamental vision research (neurosymbolic models, LLM integration, facial expression analysis). Scientific awards: NSF ACED Interdisciplinary Research Grant (2025) NSF Research Grant (2024) Outstanding Reviewer at CVPR 2021 Outstanding Teaching Award (Cornell 2018)

Farid Breidiمشاهده پروفایل

استادیار

• Extended Reality Applications in Engineering Education
• Fluid Power Modeling and Simulation
• Technology Integration for Workforce Development
• +۳ مورد دیگر

Dr. Farid Breidi serves as an Assistant Professor in Mechanical Engineering Technology at Purdue University's Polytechnic Institute, specializing in Extended Reality applications, Fluid Power Modeling, and Engineering Education innovation. His interdisciplinary work bridges digital technologies with traditional engineering practices to enhance both educational experiences and industrial applications. Education: Ph.D. in Agricultural and Biological Engineering, Purdue University (2016) M.S. in Mechanical Engineering, University of Wisconsin-Madison (2012) B.E. in Mechanical Engineering, American University of Beirut (2010) Dr. Breidi's research focuses on Extended Reality applications in engineering education, technology integration for workforce development, and digital fluid power systems. His work develops immersive learning modules that transform how students understand complex engineering concepts, particularly in fluid power systems where virtual and augmented reality create safe, interactive learning environments that would be impractical in physical labs. His publication portfolio demonstrates consistent advancement in mixed reality educational tools and digital hydraulic systems, with recent work emphasizing safety training, personalized learning pathways, and electrification challenges in heavy equipment. This research trajectory shows increasing integration of sustainability considerations and industrial applicability. As Principal Investigator, Dr. Breidi has secured significant funding from the National Science Foundation (NSF) and National Fluid Power Association (NFPA) for projects advancing educational technology and fluid power innovation. His work includes developing transparent hydraulic demonstrators, miniature racing car design projects for freshmen, and digital monitoring systems for hydraulic technologies.

Frederique Vanheusdenمشاهده پروفایل

مدرس ارشد

• Biomedical Signal and Image Processing
• Cardiac Electrophysiology
• Auditory Function Analysis
• +۳ مورد دیگر

Dr. Frederique Vanheusden is a Senior Lecturer and Course Leader for the MSc Medical Engineering program at Nottingham Trent University , affiliated with the School of Science & Technology and Department of Engineering . His research focuses on biomedical signal and image processing, particularly in cardiac and auditory domains. Education: BSc in Biomedical Sciences, MSc in Bio-electronics and Nanotechnology (University of Hasselt), MSc in Molecular Medicine (Cranfield University), PhD in Engineering (University of Leicester) Research Collaborations: Kumoh National Institute of Technology (South Korea), TU Delft (Netherlands), University of Southampton, Imperial College London, Interacoustics (Denmark), and others Research Areas include: Cardiac Electrophysiology: Non-invasive AF source estimation via BSPM, cardiac scar tissue quantification from MRI, drug-induced cardiac toxicity modeling Auditory Function: Objective hearing evaluation through eFFRs and cortical entrainment, electrophysiological mechanisms of hearing/cognitive impairment Stress Monitoring: Multi-modal ECG/EEG/EMG analysis for discomfort assessment in vibration exposure and eSports stress His work has produced significant publications in journals like Frontiers in Physiology , PLoS One , and Ear and Hearing , covering diverse applications from cardiac ablation to fetal movement monitoring. Current projects involve cardiac signal processing, auditory neuroscience, and stress perception modeling. Contact: frederique.vanheusden@ntu.ac.uk | +44 (0)115 848 8391