جست‌وجوی استاد و پژوهشگر

Alfred Heroمشاهده پروفایل

استاد

• Data Science
• Statistical Machine Learning
• Distributed Optimization
• +۱۰ مورد دیگر

Alfred Hero is the John H. Holland Distinguished University Professor of Electrical Engineering and Computer Science and the R. Jamison and Betty Williams Professor of Engineering at the University of Michigan. He is currently on leave from the University of Michigan as a Program Director in the CISE Directorate at the National Science Foundation. His primary appointment is in the Department of Electrical Engineering and Computer Science (EECS) with secondary appointments in the Department of Biomedical Engineering and the Department of Statistics. He is affiliated with multiple research centers including the UM Center for Computational Medicine and Bioinformatics (CCMB), the UM Graduate Program in Applied and Interdisciplinary Mathematics (AIM), the UM Applied Physics Program, and the Michigan Institute for Data Science (MIDAS). Hero's research focuses on data science, developing theory and algorithms for multimodality data collection, fusion, analysis and visualization using statistical machine learning and distributed optimization. His work has applications in wearable technologies for personalized health and predictive medicine, spatio-temporal networks in biology, climate, and social discourse, anomaly detection, and data analysis for international security. His research group has produced numerous PhD students who have gone on to prominent academic and industry positions. His recent publications show a strong focus on high-dimensional statistical methods, machine learning theory, network analysis, and applications in biomedical domains. The research trends indicate increasing emphasis on multimodal data fusion, robust learning algorithms, and applications to complex systems in biology and security domains. His work bridges theoretical foundations with practical implementations across diverse application areas. Fellow of the Institute of Electrical and Electronics Engineers (IEEE) Fellow of the Society for Industrial and Applied Mathematics (SIAM) Fourier Award in Signal Processing from the IEEE Hero has advised numerous PhD, MS, and undergraduate students who have gone on to successful careers in academia and industry. His research has been supported by various grants, though specific grant details are not provided in the source material. His lab collaborates extensively across disciplines with researchers in statistics, biomedical engineering, and computational medicine. The Hero Research Group maintains active collaborations with institutions worldwide and participates in major conferences in machine learning, signal processing, and data science.

Eduardo Maldonadoمشاهده پروفایل

دانشیار

• Mitochondrial Metabolism
• Cancer Bioenergetics
• Voltage-Dependent Anion Channels (VDAC)
• +۵ مورد دیگر

Eduardo Maldonado is an Associate Professor in the Drug Discovery and Biomedical Sciences department at the College of Pharmacy, Medical University of South Carolina (MUSC) . His research focuses on mitochondrial metabolism in cancer cells, T cells, and cancer stem cells, particularly targeting mechanisms regulating Voltage-Dependent Anion Channels (VDAC) to develop therapeutic strategies. Education: DVM from Universidad Nacional del Centro (1986), PhD in Human Pathophysiology from Universidad Nacional del Sur (2001), Postdoctoral training at MUSC (2006, 2010), Predoctoral research at University of the Basque Country (1999). Research Interests: Mitochondrial metabolism regulation in cancer, VDAC-targeted small molecules, T cell immunometabolism, and cancer stem cell biology. His lab (established in 2015) explores how modulating VDAC channels through tubulin interactions or NADH-binding pockets can alter tumor proliferation and survival. Article Trends: Recent publications highlight VDAC's role in cancer bioenergetics, immunometabolic reprogramming (e.g., H2S-Prdx4 axis), and synergistic drug combinations. Earlier works emphasize mitochondrial ROS, lipid metabolism, and Golgi stress in disease contexts. Labs & Teams: Leads a research group at MUSC's College of Pharmacy, affiliated with the Developmental Cancer Therapeutics Program at Hollings Cancer Center. His work bridges mitochondrial physiology, cancer metabolism, and pharmacological intervention.

• Circadian Rhythm
• Dynamics
• Neuroscience
• +۳ مورد دیگر

Casey Diekman is a Professor in the Department of Mathematical Sciences at New Jersey Institute of Technology (NJIT). His research focuses on mathematical and computational modeling of circadian rhythms, neural dynamics, and physiological systems. He has led NSF-funded projects, including studies on circadian clock mechanisms, neuronal data assimilation, and hybrid modeling of Alzheimer’s disease. His work integrates biophysical models with machine learning to study systems like cardiac electrophysiology and respiratory control. Roles: Professor, PI of multiple NSF grants Key Collaborations: Projects with researchers in neuroscience, cardiology, and computational biology Education & Background: While specific educational details are not provided, his academic position implies advanced training in applied mathematics or systems biology. Research Interests: Circadian rhythms, entrainment dynamics, computational modeling of biological systems, and applications in health (e.g., arrhythmias, neurodegenerative diseases). His work bridges mathematical theory and experimental data to address clinical problems like drug timing and respiratory failure. Grant Highlights: NSF GOALI (2022–2026): Integrates deep learning and mechanistic models for circadian clock neurons and Alzheimer’s disease NSF Career (2016–2021): Developed data assimilation tools for circadian rhythm studies NSF (2014–2017): Modeled circadian clock mechanisms from synapse to gene Recent Research Trends: Publications since 2022 focus on circadian impacts on drug safety, respiratory control during SARS-CoV-2 infection, and Alzheimer’s disease modeling using deep learning. His work often emphasizes interdisciplinary approaches to understand biological timing and its disruptions. Awards & Recognition: While specific prizes are not listed, his extensive grant portfolio and citation count (792) reflect scholarly impact. Advising & Grants: Oversees research teams in circadian biology and computational neuroscience. Media coverage highlights breakthroughs like explaining ‘happy hypoxia’ in COVID-19 patients and antiarrhythmic drug timing risks. Labs/Teams: Engaged in collaborative projects with institutions like NIH and other universities, focusing on systems-level biological modeling.

• Microchannel Engineering
• Proton Exchange Membrane Fuel Cell
• Two-phase Flow
• +۷ مورد دیگر

Eon Soo Lee is an Associate Professor in the Department of Mechanical and Industrial Engineering at the New Jersey Institute of Technology (NJIT). His primary research focuses on advanced materials engineering, biomedical microfluidics, and assistive technologies for individuals with disabilities. He has led federally funded projects including 'I-Corps: Multiplex Diagnostic Assay Using Interdigitated Nano-Sensing Technology' (NSF, 2023-2025) and 'Innovative Nano Catalysts for Automobile and Fuel Cell Applications' (NSF, 2018). Research Interests: Lee's work spans interdisciplinary areas including: Development of N-doped graphene/MOF composites for energy applications Microfluidic systems for blood plasma separation and antigen detection Design of accessible technologies for visually impaired users, including VR audio descriptions and remote sighted assistance systems Grants and Projects (select): National Science Foundation (2023): $500K for multiplex diagnostic assays National Science Foundation (2018): $300K for nano-catalysts in fuel cells Multiyear collaborations with industry partners on biosensor integration Innovation Highlights: Developed AIGuide: AR hand-guidance system for visual impairments Pioneered omnidirectional audio descriptions for VR music performances Published extensively in Carbon , Biomicrofluidics , and ACM/IEEE accessibility venues

• Neuroengineering
• Rehabilitation Engineering
• Biomedical Engineering
• +۳ مورد دیگر

Baldassarre D'Elia is a Researcher affiliated with the Department of Bioengineering at University of Roma Tre, associated with BioLab³. He holds a MSc in Electrical Engineering (1992) and PhD from Sapienza University of Rome (1996), followed by postdoctoral research there (2000). Since 2010, he has been involved in the Bioengineering Doctoral School at Roma Tre. His research focuses on neuroengineering applications in rehabilitation, particularly using haptic systems to aid post-stroke and Parkinson's patients. He explores movement regularity metrics in elderly populations through haptic feedback analysis. Education: MSc (Electrical Engineering, Sapienza 1992), PhD (Sapienza 1996), Postdoc (Sapienza 2000), current involvement in Roma Tre's Bioengineering Doctoral School. Research emphasizes haptic platforms for motor learning, quantifying movement parameters using kinematic data. His work bridges clinical needs with engineering solutions, addressing both neurological disorders and geriatric rehabilitation challenges. Publications (2012–2016) highlight studies on haptic feedback efficacy, comparison of visual/haptic modalities, and development of analytical frameworks for rehabilitation metrics. No awards explicitly mentioned but active in international conferences (ECCE, ICNR, Mediterranean Conferences). Associated with BioLab³, focusing on interdisciplinary projects combining neuroengineering and clinical applications. No formal advising role documented in provided texts.

Vassilis P. Plagianakosمشاهده پروفایل

دانشیار

• Machine Learning
• Neural Networks
• Bioinformatics
• +۵ مورد دیگر

Vassilis P. Plagianakos is an Associate Professor at the Department of Computer Science and Biomedical Informatics, University of Thessaly, Greece. He has held visiting academic roles at the University of the Aegean, University of Patras, and University of Central Greece. He currently serves as the Department Head and Director of the postgraduate program Informatics and Computational Biomedicine in the School of Sciences. His research focuses on machine learning, neural networks, bioinformatics, and parallel computing with applications in healthcare and education. Education : Bachelor’s in Mathematics (1996), University of Patras Ph.D. in Mathematics (2003), University of Patras Research Interests : Plagianakos explores neural networks, evolutionary algorithms, and machine learning applications in bioinformatics, medical diagnosis, and educational technology. His work bridges computational methods with real-world challenges in healthcare (e.g., precision medicine) and STEM education (e.g., flipped classrooms, AI integration). Recent Trends in Publications : Recent work emphasizes predictive precision medicine using big data, blockchain scalability solutions, and AI ethics in automated content detection. He has pioneered methods like the HCER hierarchical clustering-ensemble regressor and developed tools for analyzing single-cell RNA sequencing data. Professional Activities : Member of IEEE Neural Networks Society, IEEE BBTC, and former Board Member of the Hellenic AI Society. Active in collaborative projects like CrowdHEALTH for policy-driven health data analytics.

• Medical Image Analysis
• Machine Learning
• Computer Vision
• +۳ مورد دیگر

Dr Himashi Peiris is a Research Fellow in the Department of Data Science & AI at Monash University's Faculty of Information Technology in Australia. She holds a PhD in Biomedical Engineering from Monash University (2024) and a Bachelor's in Information Technology from the University of Moratuwa, Sri Lanka. Her work focuses on semi-supervised learning, medical image analysis, and AI-driven healthcare solutions. She has over three years of industry experience in software engineering. Research interests include developing machine learning algorithms for medical imaging challenges, particularly in scenarios with limited labeled data. Her innovations span neural networks, transformer architectures, and uncertainty-guided segmentation techniques applied to MRI, CT scans, and biomedical datasets. Her publications in Nature Machine Intelligence and MICCAI conference highlight contributions to semi-supervised segmentation and AI-driven diagnostic tools. Notable collaborations include the development of PINGU for perivascular space identification and adversarial networks for construction waste recognition. Awards include the 2023 Victorian Biomedical Imaging Capability Early Career Award and 2023 IEEE ACS Student Writing Award. Her work has been featured in media outlets and Mendeley platforms, emphasizing AI's role in medical decision-making.

Clemens V. Verhooselمشاهده پروفایل

دانشیار

• Computational Mechanics
• Isogeometric Analysis
• Fluid Dynamics
• +۵ مورد دیگر

Clemens V. Verhoosel is an Associate Professor in Computational Methods for Model- and Data-Driven Engineering at Eindhoven University of Technology (TU/e). He holds positions in the Department of Mechanical Engineering under the Energy Technology and Fluid Dynamics section, and is affiliated with the EAISI Foundational initiative. His research focuses on scan-based immersed isogeometric analysis, uncertainty quantification, and Bayesian inference for complex engineering problems. He leads the Group Verhoosel and manages the Engineering Mechanics Graduate School since 2018. Education: MSc (Aerospace Engineering, TU Delft, 2005, cum laude PhD, TU Delft, 2009). Postdoctoral research at University of Texas at Austin (2009-2010). Awarded NWO VENI Grant (2011). Research interests include numerical methods for solid mechanics, fluid dynamics, coupled problems, and applications in biomedical engineering (e.g., cardiac mechanics). He develops open-source tools like the Nutils toolkit and collaborates with industry partners such as Evalf Computing. Key contributions include isogeometric analysis for fracture mechanics, phase-field models, and mesh-free simulation workflows. Honors: NWO Veni Award (2011). Teaching includes Advanced Discretization Techniques and Scientific Computing courses. Active in professional activities, including invited talks on cardiac mechanics and computational methods.

• 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 .

Kim Cluffمشاهده پروفایل

استاد

• Wearable Sensing Systems
• Biomedical Engineering
• Aerospace Applications
• +۳ مورد دیگر

Kim Cluff is a Professor and IACUC Chair at Wichita State University. Her research focuses on wearable sensing systems, biomedical engineering, and aerospace applications, with a particular emphasis on non-invasive monitoring of biofluid dynamics and medical diagnostics. She has developed novel sensors for applications ranging from aerospace health monitoring to patient-specific medical systems. Her work integrates advanced materials like PVDF and dielectric elastomers with electromagnetic and RF technologies to create innovative diagnostic tools. Key projects include skin patch resonators for fluid volume measurement and systems for real-time organ motion management in medical therapies. Publications highlight contributions to biomedical sensor design, including CO₂ gas detection and shoulder joint clearance monitoring in space suits. Though no grants or awards are explicitly listed, her research has been applied in clinical contexts such as peripheral artery disease diagnostics and cancer treatment systems. A lab website exists for her main campus research activities, though specific lab details are not provided in the text.

Ahsan Adeelمشاهده پروفایل

دانشیار

• Artificial Intelligence
• Computational Neuroscience
• Multisensory Integration
• +۵ مورد دیگر

Dr. Ahsan Adeel is an Associate Professor of Cellular AI and Theoretical Neuroscience at the University of Stirling. He holds affiliations with multiple institutions including MIT, Oxford, and the Howard Brain Sciences Foundation. His research focuses on bridging cellular neurobiology with AI, particularly through the study of pyramidal Two-Point Neurons (TPNs) and their role in conscious processing. His work emphasizes developing biologically plausible AI models for healthcare, robotics, and neuromorphic computing. Education: B.Eng. in Electrical Engineering, MSc in Electronics, PhD in Cognitive Computing. Research interests include: Conscious Multisensory Integration (CMI), neuromorphic chip design, explainable AI (XAI), and applications in hearing aids, disaster management, and neurological disorders. His lab, the CMI Lab, explores how TPN mechanisms can overcome computational limitations of current AI. Key projects include a £4M EPSRC-funded hearing aid initiative, 5G-enabled environment planners for dementia patients, and collaborations with NASA/ESA on AI for space exploration. His work is featured in flagship journals like Frontiers in Computational Neuroscience and the €1.2B Human Brain Project. Awards include Fellowships from Howard Foundation, MIT, and Oxford, alongside recognition for contributions to neuromorphic computing and TPN research. He has over 30 publications and leads interdisciplinary teams across 10+ global institutions.

• Neuroscience
• Neuroimaging
• Biomedical Engineering
• +۳ مورد دیگر

Malika Datta is a Research Fellow in Neuroscience at Yale School of Medicine, Yale University. Her work focuses on advanced neuroimaging techniques and molecular mechanisms in neuroscience. She holds appointments in the Neuroscience department and contributes to interdisciplinary research in biomedical engineering and pharmacology. Her research interests include light-sheet microscopy innovation for large-scale biological imaging, dopaminergic system analysis under drug exposure, and genome editing via focused ultrasound. She has published extensively on topics such as Norrin-mediated astroglia-neuron interactions and optogenetic systems development. Recent publications highlight her contributions to scalable microscopy technologies and brain mapping methodologies. Her work bridges engineering and basic neuroscience, with applications in drug impact studies and neurotechnology. No scientific awards are explicitly mentioned in the provided information.

• Cryo-electron microscopy/tomography
• Cell motility
• Cellular energy metabolism
• +۳ مورد دیگر

Jack Zhang is an Assistant Professor in the Department of Molecular Biophysics and Biochemistry at Yale School of Medicine. His research focuses on developing advanced cryo-electron microscopy/tomography (cryo-EM/ET) methods to investigate dynamic molecular machines in cellular contexts, particularly mechanisms of cell motility and energy metabolism. PhD in Biophysics from Institute of Biophysics (CAS) Postdoctoral work at MRC Laboratory of Molecular Biology Joined Yale faculty in 2019 Research interests include: Mechanistic analysis of dynein motor proteins Structural studies of mitochondrial respiratory supercomplexes Cytoskeletal repair mechanisms via Abl2-tubulin interactions Environmental signal response in mastigoneme assembly Allostery in microtubule transport activation Recent publications demonstrate expertise in: High-resolution in situ structural biology Tomographic analysis of cellular machines Mechanochemical cycle mapping Male infertility structural pathology Contact: jack.zhang@yale.edu

• Healthcare Design
• Universal Design
• Service Design
• +۷ مورد دیگر

Hatice Kübra Yıldız is a Researcher at the Department of Industrial Design, Faculty of Architecture, Istanbul Technical University. Her work bridges design theory with interdisciplinary applications in healthcare, sustainability, and plant biology. Education : PhD in Industrial Design (ITU, 2016–2024), MSc in Industrial Product Design (Mimar Sinan Fine Arts University, 2014–2016), BSc in Industrial Design (Anadolu University, 2008–2013) Her research focuses on Healthcare Design , Universal Design , and Inclusive Design , exemplified by work on cesarean section patient journeys. She explores sustainable practices through Service Design and Photo-Based Research Methods , including analyses of the Braun Prize competitions. Recent studies include Wind Power Site Selection and the biological impact of Hypericum perforatum tea. The scientific trends in her publications span healthcare service innovation, sustainable design frameworks, computational decision-making in energy planning, and microbiota-related health research. Her work emphasizes interdisciplinary collaboration, user-centered methodologies, and ecological responsibility.

• Developmental neurobiology
• axon guidance
• neural plasticity
• +۳ مورد دیگر

Associate Professor Catherine Leamey is a Senior Lecturer in Physiology within the School of Medical Sciences at the University of Sydney, affiliated with the Bosch Institute. Her research focuses on developmental neurobiology with particular emphasis on axon guidance and neural plasticity mechanisms in the visual system. Dr. Leamey's research interests center on understanding how neural circuits develop and function, with a specific focus on the role of teneurin proteins (particularly Ten-m3) in visual system development. Her work employs animal models , cellular/molecular approaches , and growth & development methodologies to investigate how environmental factors influence neural development. Her research spans behavioral neuroscience , the nervous system , neurosciences , vision , and axon guidance mechanisms. Analysis of her recent publications (2014-2025) reveals a consistent research trajectory focused on teneurin proteins and their role in neural circuit formation, particularly in the visual system. Her work has increasingly incorporated microglial function in neuroplasticity and has expanded into optogenetic approaches for vision restoration. The research demonstrates sophisticated integration of molecular biology, developmental neuroscience, and behavioral analysis, with significant implications for understanding neural development disorders. Dr. Leamey has successfully supervised multiple PhD students, including Hannan Mansuri who is researching 'Retinal Ganglion Cells in Binocular Vision and the effects of Teneurin proteins.' She has secured substantial research funding from major organizations including the National Health and Medical Research Council (NHMRC), Australian Research Council (ARC), Simons Foundation, and the Michael J. Fox Foundation for Parkinson's Research. Her grants span diverse areas including visual system development, neural circuit mapping, and optogenetic vision restoration. Her laboratory appears to focus on neural development using mouse models, with particular expertise in visual system circuitry, teneurin protein function, and the impact of environmental enrichment on neural development. The research group combines molecular, cellular, and behavioral approaches to investigate fundamental mechanisms of neural circuit formation and plasticity.