جست‌وجوی استاد و پژوهشگر

David Patersonمشاهده پروفایل

استاد

• Cardiorespiratory Control
• Autonomic Neuroscience
• Cardiac Neurobiology
• +۱ مورد دیگر

David Paterson is Professor of Physiology and Head of the Department of Physiology, Anatomy & Genetics at the University of Oxford, a role he has held since 2016. He is also a Fellow of Merton College, Oxford, and has served in key administrative positions including Deputy Head (Vice Dean) of the Division of Medical Sciences (2008–2016). His leadership spans strategic planning and education policy, contributing to Oxford’s global ranking in Anatomy & Physiology. Paterson’s research focuses on cardiorespiratory control , autonomic neuroscience , and cardiac neurobiology . His Cardiac Neurobiology Research Group investigates neural regulation of the heart in health and disease, with emphasis on hypertension, arrhythmias, and neurocardiac signaling. Key themes include sympathetic neurotransmission, cyclic nucleotide pathways, and bioelectronic interventions for cardiovascular disorders. His recent publications (2020–2025) emphasize translational neurocardiology, exploring molecular mechanisms of sympathetic hyperactivity, stem cell-based disease models, and bioelectronic therapies. Articles consistently address autonomic dysregulation in hypertension, arrhythmia pathophysiology, and innovative diagnostic tools, reflecting interdisciplinary collaboration across physiology, neuroscience, and engineering. Major Awards & Honors: Honorary Doctorates (Otago, UWA), Fellowships (FRSB, FAPS, FPhysiol) Presidency of The Physiological Society (2020–2022) Carl Ludwig Distinguished Award, Brookhart Award Lecture Editorships: Journal of Physiology (2011–2016), Experimental Physiology (2006–2011) Paterson has supervised 27 doctoral students and secured ~£17M in funding, including a British Heart Foundation Centre of Excellence (£8.4M co-PI) and infrastructural grants for the Burdon Sanderson Cardiac Centre. His group leverages molecular, cellular, and whole-organ approaches to advance neurocardiac therapeutics.

Aysim Tokerمشاهده پروفایل

پژوهشگر

• Computer Vision
• Machine Learning
• Deep Learning
• +۳ مورد دیگر

Aysim Toker is a Ph.D. candidate at the Chair for Computer Vision and Artificial Intelligence , affiliated with the Technical University of Munich . She works under the supervision of Prof. Dr. Laura Leal-Taixe and Prof. Dr. Xiaoxiang Zhu on interdisciplinary projects. Research Focus: Deep learning, sequence analysis, and remote sensing. Key Contributions: Advancing video object segmentation, Earth observation models, and anonymization techniques. Collaborations: Partnered with international researchers across multiple institutions. Publications span top venues like eLife , ICCV , NeurIPS , and CVPR , with a focus on: Deep learning architectures for multi-modal tasks Image and video analysis in remote sensing and anonymization Tracking and segmentation algorithms Her work bridges foundational computer vision research with applications in Earth science and privacy-preserving technologies.

Emrah Celikمشاهده پروفایل

دانشیار

• Additive Manufacturing
• Composite Materials
• 3D Printing
• +۵ مورد دیگر

Emrah Celik is an Associate Professor in the Department of Mechanical & Aerospace Engineering at the College of Engineering, University of Miami. His research focuses on advanced manufacturing techniques, particularly in the area of additive manufacturing of composite materials and their multifunctional properties. Dr. Celik's research interests span multiple cutting-edge areas of materials science and engineering: Additive manufacturing of polymer and fiber-reinforced composites Electrical and mechanical properties of 3D printed composites Carbon fiber reinforced polymer (CFRP) composites Thermoelectric materials and energy harvesting Multi-functional composite structures Advanced characterization techniques for composite materials Analysis of Dr. Celik's recent publications reveals a strong focus on pushing the boundaries of additive manufacturing for composite materials. His work demonstrates significant advancements in controlling fiber alignment in 3D printed thermoset composites, developing novel methodologies for electrical network activation, and enhancing mechanical performance through innovative printing techniques. A notable trend is his exploration of in-situ activation of electrical properties in printed composites, which opens new possibilities for structural health monitoring and self-sensing capabilities. His research also extends to thermoelectric materials, where he has achieved record-breaking performance metrics for 3D printed copper sulfide materials. Dr. Celik's work bridges fundamental materials science with practical aerospace applications where lightweight, high-performance materials are critical. Dr. Celik has established himself as a leading researcher in advanced composite manufacturing with numerous publications in high-impact venues. His innovations include the development of nozzle oscillation infill patterns that improve electrical conductivity by 27% while enhancing dimensional accuracy, and bi-modal fiber alignment approaches that increase mechanical performance by 16% with improved fracture resistance. His laboratory at the University of Miami focuses on Direct Ink Writing processes for thermoset composites, investigating how process parameters affect microstructure formation and resulting material properties. Current research explores new frontiers in multifunctional composite systems with integrated sensing capabilities and spatially controlled electrical properties.

Samuel M Mugoمشاهده پروفایل

استاد

• Analytical Chemistry
• Electroanalytical Chemistry
• Nanochemistry
• +۵ مورد دیگر

Dr. Samuel M Mugo is a Professor and Associate Dean of Development in the Faculty of Arts and Science at MacEwan University (Edmonton, Alberta), affiliated with the Department of Physical Sciences. He holds a PhD in Analytical Chemistry from Memorial University of Newfoundland (2006) and completed an NSERC postdoctoral fellowship at Queen's University (2007-2008). Since joining MacEwan in 2008, he teaches analytical chemistry, industrial chemistry, and mentors undergraduate researchers. Research Focus: Dr. Mugo develops smart polymer nanomaterials for mobile point-of-need spectro-electrochemical sensors. His work spans: Wearable diagnostics for mental health monitoring Precision agriculture and environmental quality sensors Frugal electrochemical platforms integrating data analytics Technology translation from lab to industry/community Key expertise includes nanotechnology, molecular imprinting, nanozymes, and citizen science applications. Publication Trends: Recent articles (2022-2025) demonstrate strong focus on: Wearable/implantable electrochemical sensors Microneedle-based metabolite detection Multiplexed biomarker analysis in biological fluids Smart hydrogels for neural interfaces Sustainable sensor materials from biowaste Awards & Honors: Alberta Newcomers Recognition Award (2022) MacEwan Distinguished Research Award (2021) MacEwan Distinguished Teaching Award (2020) Research Leadership: Dr. Mugo leads an interdisciplinary research group ( mugoresearchlab.com ) focused on sensor development. He has secured multiple grants including NSERC Discovery grants and Alberta Innovates funding. As Vice Chair of the Canadian Society of Chemistry Analytical Division, he promotes inclusive research communities.

Dewar Finlayمشاهده پروفایل

استاد

• Healthcare Technology
• Artificial Intelligence
• Digital Signal Processing
• +۵ مورد دیگر

Dewar Finlay is a Professor of Electronic Systems and Head of the School of Engineering at Ulster University . He previously served as Research Director for the School of Engineering and Interim Associate Dean for Research & Impact within the Faculty of Computing, Engineering and the Built Environment. His work bridges healthcare technology and computational engineering. Education: BEng in Electronic Systems, Ulster University PhD in Computing, Ulster University Research Interests: His research focuses on healthcare technology with emphasis on computerised ECG analysis and deep learning applications in cardiology . He explores AI-driven diagnostics , signal processing , and medical device validation through projects like DTNet+ Digital Twin Network and IoT-Driven Cybersecurity Framework for Intrusion Detection in Drones . Scientific Awards: Best Poster (2024) - Calibrated Uncertainty AI in ECG Analysis Early Career Investigators Award (2022) - British Society for Heart Failure Grants & Collaborations: He has secured funding from EU Horizon 2020 , RCUK , DEL , and InvestNI . Current projects include AI-assisted echocardiography for congenital heart defects in Sub-Saharan Africa and federated learning frameworks for cardiac healthcare.

Ben Maozمشاهده پروفایل

استاد

• Biomedical Engineering
• Nanotechnology
• Neuroscience
• +۴ مورد دیگر

Prof. Ben Maoz is a Professor at the Department of Bio-Medical Engineering , The Iby and Aladar Fleischman Faculty of Engineering , Tel Aviv University . He directs the MaozLab, which pioneers interdisciplinary research in neuroengineering, microphysiological systems, and nanoscale therapeutic delivery. His lab integrates engineering principles with neuroscience to model human diseases and develop translational technologies. Research Focus Prof. Maoz's research spans: Organ-on-Chip Platforms : Developing modular microfluidic systems (e.g., neurovascular units, PNS-CNS models) for disease modeling and drug screening. Nanoneuroengineering : Designing brain-targeted nanocarriers (liposomes, dendriplexes) for siRNA and antibody delivery in neurodegenerative disorders like Parkinson's. Medical Devices : Creating implantable sensors, nanogenerators for sensory restoration, and tools for traumatic brain injury analysis. Cellular Mechanobiology : Investigating biomechanical forces in tissues using magnetoresponsive hydrogels and 3D cultures. Publication Trends His recent work (2023-2025) emphasizes: Advanced drug delivery systems for neurological applications (e.g., siRNA to neurons, alpha-synuclein-targeting antibodies). Innovative organ-on-chip platforms for studying cancer metastasis, viral entry, and neuro-immune interactions. Biomaterials and nanotechnologies addressing sensory restoration, cellular contractility, and super-resolution imaging. Laboratory & Collaborations The MaozLab employs microfabrication, molecular biology, and in vitro modeling to tackle challenges in brain health, with collaborations spanning oncology, virology, and gastroenterology.

• Human Factors
• Cognitive Science
• Cyberpsychology
• +۷ مورد دیگر

Professor Phillip Morgan is a leading academic in Human Factors and Cognitive Science at Cardiff University's School of Psychology, holding a Personal Chair since 2020. He directs the Human Factors Excellence (HuFEx) Research Group and serves as Director of Research for the Centre for Artificial Intelligence, Robotics & Human-Machine Systems (IROHMS) . Since March 2019, he has been seconded part-time to Airbus as Director of their Centre of Excellence in Human-Centric Cyber Security . BSc (Hons) Psychology, Cardiff University (2001) PGDip Research Methods, Cardiff University (2002, Distinction) PhD in Cognitive Psychology, Cardiff University (2005) PGCHE, University of Wales (2012, Distinction) His research merges Human Factors with Cognitive Science to address real-world challenges in: Human-machine interaction in autonomous systems Cyberpsychology and security behavior Transport human factors (connected/autonomous vehicles) Interruption/distraction effects on cognition Trust and blame dynamics in AI systems Industry 5.0 human-centric manufacturing Recent publications show AI and cybersecurity as dominant themes, with specific focus on autonomous vehicle interfaces, human fatigue analysis, and trust calibration in human-machine systems. His work integrates behavioral experiments, driving simulators, and human-state monitoring. Scientific Recognition: Associate Fellow of the British Psychological Society Best Paper Award at AHFE 2021 Member of Experimental Psychology Society Keynote speaker at multiple international conferences As supervisor, he leads projects on cybersecurity frameworks, fatigue detection, and human-AI interaction. His grants portfolio exceeds £37m from sources including EPSRC, ESRC, Airbus, and Wellcome Trust. Current supervisees include Victoria Marcinkiewicz, George Raywood-Burke, and Nicola Turner.

Greg D. Fieldمشاهده پروفایل

دانشیار مدعو

• Neurobiology
• Retinal Processing
• Neural Adaptation
• +۷ مورد دیگر

Greg D. Field is an Adjunct Associate Professor of Neurobiology at Duke University and a Faculty Network Member of the Duke Institute for Brain Sciences. His laboratory investigates retinal processing of visual scenes, focusing on functional connectivity, light adaptation, circadian rhythms, and retinal degenerative conditions. Using multi-electrode arrays, transgenic mouse models, and chemogenetics, he examines how retinal circuits encode visual information and how degeneration impacts signaling. Recent work addresses neural adaptation mechanisms, retinal mosaics, and potential therapies for retinal diseases. Research Themes : Retinal circuit organization, neural adaptation, visual signal processing, retinal degeneration, and optogenetics Technologies : Multi-electrode recordings, light-sheet microscopy, computational modeling, and transgenic approaches The 15 most recent publications (2010-2025) demonstrate his work on retinal ganglion cell function, visual hierarchy encoding, and therapies for photoreceptor degeneration. Grants from the National Institutes of Health (2015-2025) support studies on neural population mapping, comparative biology, and retinal circuit restoration. His work bridges theoretical neuroscience with clinical applications, particularly in developing interventions for blindness.

Ruwen Qinمشاهده پروفایل

دانشیار

• Intelligent transportation systems
• Smart civil infrastructure systems
• Human sensing & analytics
• +۸ مورد دیگر

Ruwen Qin is an Associate Professor in the Department of Civil Engineering at Stony Brook University. Her research focuses on integrating data analytics, machine learning, and systems engineering into civil infrastructure systems to develop cyber-physical systems and intelligent automation. She applies these technologies to enhance human-AI collaboration, improve transportation safety, and advance smart infrastructure monitoring. Developing AI models for structural health monitoring Applications in worker safety and transportation systems Specializes in computer vision and sensor fusion Her recent work includes deep learning frameworks for drone-assisted inspections, structural component segmentation using weak annotations, and attention-based networks for traffic risk prediction. She also explores explainable AI for crash anticipation and interactive systems for bridge inspectors. Ruwen Qin's research spans interdisciplinary domains, combining civil engineering with AI-driven analytics to address challenges in infrastructure resilience, transportation safety, and human-centric automation systems.

• Data Visualization
• Visual Analytics
• Big Data Analysis
• +۱۲ مورد دیگر

Professor Jang Yoon is a faculty member in the Department of Computer Engineering at Sejong University, South Korea. He currently holds the position of Daeyang Distinguished Professor and leads the Data Visualization Lab. His academic journey includes postdoctoral research at the Swiss National Supercomputing Center (2007-2009), ETH Zurich (2009-2011), and Purdue University (2011-2012). His educational background includes a Bachelor's degree from Seoul National University in Electrical Engineering (2000), and Master's and Doctoral degrees from Purdue University in Electrical and Computer Engineering (2002 and 2007). His academic progression at Sejong University shows his appointment as Assistant Professor (2012-2016), Associate Professor (2016-2022), and Professor (2022-present). Professor Jang's research spans multiple domains within data science and visualization, with primary focus on data visualization, visual analytics, and their applications in various domains. His work bridges theoretical computer science with practical applications in traffic analysis, healthcare, and smart city infrastructure. He has developed innovative techniques for spatiotemporal data visualization, volume rendering, and causal analysis in complex datasets. His recent publications (2023-2025) demonstrate a strong focus on integrating deep learning with visualization techniques, particularly in traffic analysis, volume rendering, and large language model interpretability. His work shows a clear trajectory toward combining causal inference with visual analytics, applying these methods to urban traffic systems, structural health monitoring, and public relations analysis. Professor Jang has served in numerous leadership roles in major visualization conferences including IEEE VIS, IEEE PacificVis (as General Chair in 2023), EuroVis, and HCI Korea conferences. His service contributions include program committee memberships and chair positions across multiple prestigious conferences in the visualization field. His laboratory work focuses on practical applications of visualization techniques with numerous patents registered in Korea. His research has resulted in multiple practical systems for traffic analysis, VR sickness detection, data quality improvement, and eye-tracking applications. The lab maintains strong industry connections through applied research projects addressing real-world problems.

Thomas Dayمشاهده پروفایل

پژوهشگر ارشد

• Artificial Intelligence
• Fetal Echocardiography
• Congenital Heart Disease
• +۵ مورد دیگر

Thomas Day is a Clinical Research Fellow at King's College London's School of Biomedical Engineering & Imaging Sciences, Department of Cardiovascular Imaging. He works within the Intelligent Fetal Imaging and Diagnosis (iFIND) project and practices clinically at The Evelina London Children's Hospital, part of Guy's and St Thomas' NHS Foundation Trust. Education: MBChB in Medicine, University of Manchester (2002-2008) MRes (intercalated) in Medicine, University of Manchester (2006-2008) His research focuses on leveraging artificial intelligence to enhance congenital heart disease screening through fetal echocardiography and ultrasound imaging. Key contributions include developing AI-driven tools for fetal biometric estimation, lymphatic perfusion segmentation, echocardiogram synthesis, and outlier detection in medical imaging. Scientific Awards: KHP Clinical Research Excellence Fellow Research Projects: Randomised controlled trial of AI-assisted fetal ultrasound (NIHR, 2025-2027) AI in Sub-Saharan Africa echocardiography (NIH, 2023-2025) Antenatal congenital heart disease detection (NIHR, 2021-2024)

Xin Huangمشاهده پروفایل

دانشیار

• Graph Data Management
• Big Graph Mining & Visualization
• Social Network Analysis
• +۴ مورد دیگر

Xin Huang is an Associate Professor in the Department of Computer Science at Hong Kong Baptist University (HKBU), Faculty of Science. He serves as Coordinator of Research Postgraduate Programme (PhD&MPhil) and Coordinator of Programming Contest Teams. His educational background includes: Ph.D. in Systems Engineering and Engineering Management from The Chinese University of Hong Kong (2014) B.Eng. in Computer Science from Xiamen University (2010) Huang's research focuses on innovative technologies for large-scale graph data management and analysis. His work spans graph data management including keyword search and graph indexing, graph mining techniques for summarization and decomposition, community search algorithms, and graph learning approaches including graph neural networks. His research integrates theoretical foundations with practical applications in social network analysis and privacy-aware computing. His publication record shows consistent output in top-tier venues with a clear evolution from foundational graph algorithms to more complex applications involving dynamic and uncertain graphs, reflecting the growing importance of graph analytics in real-world systems. Notable awards include: Best Student Paper Award at ACM/IEEE IWLS 2023 Best Faculty Article Award from Chinese Communication Association (2022) HKBU President's Award for Outstanding Performance as Young Researcher (2021) RGC Early Career Award (2020) Best Paper Award at WISE 2019 Huang actively mentors PhD students and postdoctoral fellows, currently supervising five PhD candidates and four postdocs. His research has been supported by competitive grants including the RGC Early Career Award. He serves as Associate Editor for Data Science and Engineering and World Wide Web Journal, and participates extensively in program committees for major conferences including VLDB, ICDE, and WWW. As part of HKBU's Database Research Group, Huang contributes to a vibrant research environment that has secured over $10 million in research funding and published more than 200 papers in top venues.

Daniel Moranمشاهده پروفایل

استاد

• Neuroprosthetics
• Neural Engineering
• Brain-Computer Interfaces
• +۳ مورد دیگر

Daniel Moran is a Professor at Washington University in St. Louis since 2001, specializing in neuroprosthetics and brain-computer interfaces through the Division of Biology & Biomedical Sciences. His research restores motor function in paralyzed patients by decoding neural signals for neuroprosthetic control. Education PhD, Arizona State University, 1994 BS, Milwaukee School of Engineering, 1989 His lab investigates voluntary upper limb motor control mechanisms and alternative neural signal pathways for brain-computer interfaces. This work directly enables technologies like the FDA-approved IpsiHand, which translates ipsilateral brain activity into hand movement for stroke patients. Scientific Awards National Academy of Inventors (2021) for 'highly prolific spirit of innovation' Moran co-developed the IpsiHand neuroprosthetic (FDA approved 2021) and leads an NIH-funded neurotech training program (2022) cultivating engineering solutions for neurological disorders. His prior neurophysiology research at the Neurosciences Institute in San Diego established foundational motor control principles.

Vijaykrishnan Narayananمشاهده پروفایل

استاد

• Power Aware Computing
• Computer Architecture
• Embedded Systems
• +۴ مورد دیگر

Vijaykrishnan Narayanan is a Professor at the College of Engineering , Pennsylvania State University, with affiliations in both Computer Science & Engineering and Electrical Engineering departments. He co-directs the Microsystems Design Lab and leads the Architecture, Benchmarking, and Circuits Thrust at the DARPA/SRC LEAST Center. Education : Bachelors (1993) from University of Madras; Ph.D. (1998) from University of South Florida His research focuses on Power Aware Computing , Computer Architecture , Embedded Systems , and Emerging Device Integration . Recent work explores steep-slope devices for energy efficiency, nonvolatile processors for ambient energy harvesting, and neuromorphic architectures using hybrid VO₂-MOSFET oscillators. Key article trends span post-CMOS technologies (tunnel FETs, VO₂ devices), low-power design , and bio-inspired signal processing . Scientific Awards : IEEE Fellow, ACM Fellow, IEEE Transactions on VLSI Best Paper, IEEE Micro Best Paper Patents : Dynamically-configurable hardware architecture for audience analytics

Marco Prinzمشاهده پروفایل

استاد

• Neuroimmunology
• Microglia Biology
• CNS Inflammation
• +۵ مورد دیگر

Professor Marco Prinz serves as Principal Investigator leading the Innate Immunity research group at the Institute of Neuropathology, University of Freiburg Faculty of Medicine. His laboratory investigates the critical role of brain-specific innate immune cells, particularly microglia, in neurological health and disease. Dr. Prinz's research focuses on understanding how microglia—the brain's resident macrophages—contribute to both protective and pathological processes in the central nervous system. His work examines microglial function in neuroinflammation, neurodegeneration, and autoimmune conditions like multiple sclerosis using advanced mouse models including EAE and cuprizone models. A significant portion of his recent research employs single-cell analysis techniques to characterize the heterogeneity of microglial cells in various disease states, particularly in chronic active lesions and paramagnetic rim lesions in MS patients. The laboratory has made important contributions to understanding microglial development, showing how these cells emerge from specific precursors and establish themselves in defined niches within the CNS. Their work has revealed how microglia act as both guardians and potential contributors to neurological damage, with implications for Alzheimer's disease, Parkinson's disease, and multiple sclerosis. Dr. Prinz's research team includes multiple postdoctoral researchers, PhD students, and technical staff who contribute to ongoing investigations into CNS immunity. His laboratory has pioneered techniques for studying microglia, including novel genetic tools and single-cell analysis approaches that have provided unprecedented insights into the cellular composition of brain lesions and the dynamic behavior of immune cells in neurological disorders.