جست‌وجوی استاد و پژوهشگر

Manuel Blanco Velascoمشاهده پروفایل

استاد

• Biomedical Engineering
• Signal Processing
• Machine Learning
• +۳ مورد دیگر

Manuel Blanco Velasco is a Professor at the Department of Signal Theory and Communications, Universidad de Alcalá. His research focuses on biomedical signal processing, particularly in electrocardiogram (ECG) analysis, machine learning applications in healthcare, and communication systems. He holds a PhD from Universidad de Alcalá (2004) with a thesis on ECG compression using modulated filter banks. His work bridges signal processing theory and practical biomedical engineering, addressing challenges in ECG noise classification, T-wave alternans detection, and telemedicine systems. Research interests include: Medical signal processing for arrhythmia detection Deep learning models for clinical data interpretation OFDM-based communication systems ECG compression and denoising algorithms His recent publications emphasize interpretable deep learning methods for ECG analysis, noise characterization in long-term monitoring, and ensemble approaches for T-wave alternans detection. Contributions span both biomedical and communication engineering domains, reflecting his interdisciplinary expertise.

• Cardiac Electrophysiology
• Atrial Fibrillation
• Ventricular Tachycardia
• +۴ مورد دیگر

Walid Saliba, MD is a prominent cardiac electrophysiologist serving as Director of the Electrophysiology Lab, Associate Section Head of Pacing and Electrophysiology, Co-Director of the Ventricular Arrhythmia Center, and Medical Director of the Center for Atrial Fibrillation at Cleveland Clinic's Department of Cardiovascular Medicine. Board-certified in cardiac electrophysiology, cardiovascular disease, and internal medicine, Dr. Saliba performs approximately 100 ablations and 75 device procedures annually. Dr. Saliba's research focuses on innovative treatments for atrial fibrillation and pacemaker/defibrillator performance. His clinical expertise spans catheter ablation of complex arrhythmias , implantation of cardiac devices , left atrial occlusion procedures , and laser-assisted lead extraction . His scholarly work has been published in premier journals including Circulation and Journal of the American College of Cardiology , with particular emphasis on advancing ablation techniques and device therapies. Analysis of Dr. Saliba's publication record reveals consistent contributions to atrial fibrillation management , ventricular tachycardia ablation , and cardiac device innovation . His research demonstrates evolution from traditional approaches toward personalized, precision-based techniques incorporating advanced mapping technologies and novel ablation strategies. Recent work increasingly addresses real-world outcomes, cost-effectiveness, and special patient populations including the elderly and those with structural heart disease. Industry consultant for Boston Scientific Corporation (fees exceeding $5,000 annually) Invited lecturer at numerous national cardiology conferences Recipient of consistently high patient satisfaction ratings (4.9/5 stars) Dr. Saliba maintains active clinical practice with robust procedural volume and offers both in-person and virtual follow-up visits through Cleveland Clinic Express Care Online. His patient-centered philosophy emphasizes collaborative decision-making, as reflected in his statement: "The best reward is when the patient comes back to see you in the clinic, feeling great and they say: 'I have a new life.'"

Karthi Umapathyمشاهده پروفایل

استاد

• Biomedical Signal and Image Analysis
• Time-frequency Analysis
• Digital Signal Processing
• +۵ مورد دیگر

Dr. Karthi Umapathy is a Professor at the Department of Electrical and Computer Engineering at Toronto Metropolitan University, serving as Program Director for Biomedical Engineering and Associate Chair for Student Affairs. He holds senior membership in IEEE and is an Affiliate Scientist at St. Michael's Hospital (iBest). He is a registered professional engineer in Ontario, Canada. Education: Bachelor of Engineering (B.E.) in Electronics and Communication Engineering, Bharathiar University, India (1992) Master of Philosophy (MPhil) in Electronics, Communication & Electrical Engineering, University of Hertfordshire, UK (2002) Doctor of Philosophy (Ph.D.) in Electrical and Computer Engineering, University of Western Ontario, Canada (2006) Research focuses on Biomedical Signal and Image Analysis , Cardiac Electrophysiology , and MRI . Recent work explores signal subspace techniques for ventricular fibrillation analysis and MRI data fusion for cardiac arrhythmia studies. His articles emphasize clinical translation of signal processing methods in healthcare. Notable awards include the NSERC CGS/PGS scholarships and the Heart & Stroke Richard Lewar Fellowship. His career includes MRI leadership at Philips Medical Systems India and postdoctoral training at Ryerson University.

• Arrhythmias, Cardiac
• Atrial Fibrillation
• Cardiology
• +۵ مورد دیگر

Joseph Akar, MD, PhD, is a Professor of Medicine in Cardiovascular Medicine and Director of the Cardiac Electrophysiology Program at Yale School of Medicine. He specializes in complex arrhythmias, particularly atrial fibrillation and ventricular tachycardia, with expertise in catheter ablation and fluoroscopy-free techniques using intracardiac echocardiography. His academic roles include co-PI of an NIH-funded study on atrial fibrosis imaging and leadership in national registries (NCDR AFib Ablation Registry). Education: MD from University of Pittsburgh (1995), Internal Medicine residency at Yale New Haven Hospital (1998), Fellowships in Cardiovascular Medicine and Cardiac Electrophysiology at University of Virginia (2002–2004), and PhD in Molecular Physiology and Biological Physics (2004). He previously held faculty positions at Loyola University Medical Center before returning to Yale in 2013. Research focuses on atrial fibrillation mechanisms, including electrical/structural remodeling, non-invasive imaging, and device remote monitoring. He contributed to consensus statements on atrial cardiomyopathy and EP lab standards. His work spans basic science (mouse models), translational studies (ablation techniques), and outcomes research (30,000-patient device registry). Key contributions include reducing radiation exposure in ablation, identifying atrial fibrosis biomarkers, and advancing understanding of arrhythmia triggers. He collaborates with engineers and clinicians globally, holds NIH and FDA grants, and mentors trainees in cardiology and electrophysiology. Labs/Teams: Directs Yale’s Complex Ablation Program and participates in the Electrophysiology & Cardiac Arrhythmia Program. Active in professional societies (HRS, EHRA) and guideline-writing groups.

• Mathematical Finance
• Volatility Estimation
• Option Pricing
• +۳ مورد دیگر

Simona Sanfelici is a Full Professor of Mathematical Methods for Economics, Actuarial Sciences and Finance at the University of Parma's Department of Economics and Business Sciences. She has held this position since January 2020, following roles as Associate Professor (2005-2020) and Permanent Research Associate (2000-2005) at the same institution. Her academic qualifications include a Degree in Mathematics from the University of Parma (1994) and a PhD in Computational Mathematics and Operational Research from the University of Milan (1998). She obtained National Scientific Qualification as Full Professor in 2017. Her research focuses on mathematical finance with emphasis on volatility estimation, option pricing, financial instability modeling, and computational methods. Key areas include: High-frequency data analysis and Fourier-based volatility techniques Stochastic modeling of financial markets and derivatives Numerical methods for partial differential equations in finance Financial risk assessment and early warning systems Her publication record spans computational finance, econometrics, and applied mathematics. Recent work (2020-2024) shows strong focus on Fourier-Malliavin volatility estimation, climate-related financial risks, stochastic volatility models, and numerical methods for option pricing. She maintains an interdisciplinary approach with applications in epidemiology and cardiac electrophysiology from earlier career stages. Teaching responsibilities include courses in Mathematical Finance, Computational Methods for Finance, and Mathematical Methods for Economics across undergraduate and graduate programs at the University of Parma.

Antoni Ivorraمشاهده پروفایل

استاد

• Bioelectrical Phenomena
• Biomedical Engineering
• Electroporation
• +۶ مورد دیگر

Antoni Ivorra is a Professor at the Department of Information and Communication Technologies (DTIC) of Universitat Pompeu Fabra (UPF) , and a Serra Húnter Fellow and ICREA Acadèmia Fellow . He joined UPF in 2010 after completing a postdoctoral fellowship at the University of California, Berkeley (2005-2009), a short-term position at CNRS-Institut Gustave Roussy (2009), and prior work at the Biomedical Applications Group of the Centre Nacional de Microelectrònica (1998-2005). He earned a PhD in Electronics Engineering from the Universitat Politècnica de Catalunya in 2005. His research focuses on bioelectrical phenomena for biomedical applications , including electroporation , electrical bioimpedance , and injectable electronics for neuroprosthetics. His work spans device development, computational modeling, and clinical translation, with emphasis on tissue ablation and wireless implantable systems. His recent publications highlight advancements in pulsed field ablation , volume conduction for powering implants, and multiscale modeling of electroporation effects. These contributions reflect interdisciplinary expertise in biomedical engineering , electrophysiology , and medical device innovation . Scientific Awards : ERC Consolidator Grant (2016) Serra Húnter Fellow ICREA Acadèmia Fellow

Line Jacquesمشاهده پروفایل

استاد

• Neurosurgery
• Neurology
• Spinal Cord Electrophysiology
• +۳ مورد دیگر

Line Jacques, MD, MS, is a Professor in the Department of Neurological Surgery at the University of California, San Francisco (UCSF) School of Medicine. With clinical expertise in pediatric and adult neurosurgery, she specializes in neurofibromatosis (NF1, Schwannomatosis), peripheral nerve surgery, and spinal cord electrophysiology. Education: MD from Universite de Montreal (1990), General Surgery Internship (Cliniques Universitaires Saint-Luc, 1991), Neurosurgery Residency (University of Montreal Hospital Saint-Luc, 1996), and Neurosurgery Fellowship (LSU Health Shreveport, 1997). Certifications: Board-certified in Neurological Surgery by the American Board of Neurological Surgery (2003). Research Focus: Her work bridges clinical neurosurgery with translational research, emphasizing neurofibromatosis tumor biology, spinal cord stimulation for pain management, and peripheral nerve injury mechanisms. Key contributions include studies on epidural spinal electrograms for movement mapping, Schwann cell tumor dedifferentiation, and diagnostic accuracy of MRI for nerve sheath tumors. Scientific Trends: Recent articles highlight advancements in spinal cord herniation pathophysiology, neuralgic amyotrophy diagnostics, and neurogenomic approaches to schwannomatosis. Earlier publications established foundational work in failed back surgery syndrome management via spinal cord stimulation. Clinical Impact: Jacques co-authored high-impact trials like the PROCESS Study (2008) evaluating spinal cord stimulation versus conventional pain management, with over 250 citations. Her work informs surgical protocols for brachial plexus trauma and cervical nerve tumors.

• Cardiac Arrhythmias
• Atrial Fibrillation
• Cardiac Mapping
• +۵ مورد دیگر

Derek J. Dosdall, PhD, is an Associate Professor at the University of Utah, affiliated with the Department of Surgery (Division of Cardiothoracic Surgery) and holds adjunct appointments in the Department of Bioengineering and the Department of Internal Medicine (Division of Cardiovascular Medicine). His research focuses on mapping cardiac arrhythmias, particularly atrial fibrillation, using chronic animal models to investigate conduction disturbances and the role of fibrosis in arrhythmogenesis. Education: PhD in Bioengineering, Arizona State University Postdoctoral Training, University of Alabama at Birmingham His work explores the specialized cardiac conduction system in ventricles and its role in arrhythmia onset, alongside computational modeling for personalized ablation strategies. Recent publications highlight advancements in left bundle branch pacing, gene therapy for heart failure, and machine learning applications in electrogram classification. Key trends in his research include: chronic animal models of arrhythmias, fibrosis quantification, ablation optimization, and integration of artificial intelligence in cardiac signal analysis. He has authored patents on low-energy defibrillation methods and atrial fibrillation treatment systems.

• Cardiology
• Electrophysiology
• Atrial Fibrillation
• +۵ مورد دیگر

Dr. Mathijs van Schie is a researcher in the Department of Cardiology at Erasmus MC, Rotterdam, Netherlands. His work focuses on cardiac electrophysiology, particularly atrial fibrillation, signal processing of electrograms, and surgical ablation techniques. He is actively contributing to both clinical and translational research, collaborating with leading experts such as Prof. N.M.S. de Groot. His research interests lie at the intersection of cardiology and biomedical signal analysis, with a strong emphasis on understanding the mechanisms of atrial fibrillation. Key areas include atrial potential morphology, sex differences in arrhythmia, epicardial mapping, and the development of novel diagnostic tools based on high-resolution ECG and electrophysiological data. The most recent publications demonstrate a trend toward integrating advanced signal processing (e.g., singular value decomposition) with clinical electrophysiology to identify abnormal atrial regions. There is also growing interest in molecular markers of electropathology , such as DNA damage, and personalized ablation strategies in congenital heart disease and leadless pacing systems. Dr. van Schie has contributed to several high-impact review and original research articles in journals including European Heart Journal , JACC: Clinical Electrophysiology , and IEEE Transactions on Biomedical Engineering . He has supervised at least one doctoral thesis, indicating involvement in academic mentoring. While no formal grants are listed, his collaborative output suggests participation in multidisciplinary research projects within Erasmus MC’s electrophysiology group. His work is associated with the cardiac electrophysiology laboratory at Erasmus MC, where advanced mapping and ablation techniques are developed and applied in both acquired and congenital heart disease contexts.

Richard Schillingمشاهده پروفایل

استاد

• Cardiac Arrhythmias
• Electrophysiology
• Clinical Research
• +۳ مورد دیگر

Professor Richard Schilling is a Consultant Cardiologist and lead of the academic department of cardiac electrophysiology at Queen Mary University of London and St Bartholomew's Hospital. He specializes in clinical research addressing complex cardiac arrhythmias and percutaneous treatments, particularly in structural heart disease, congenital heart disease, atrial fibrillation, and heart failure. His team has secured funding from peer-reviewed grants and industry, enabling the acquisition of advanced equipment such as electroanatomical 3D mapping systems and robotic ablation tools. Key collaborators include Professor Ken Suzuki and sponsors like Barts Charity and Medtronic. Research focuses on elucidating arrhythmia mechanisms and improving patient outcomes through innovative therapies. His work emphasizes translational research, with a focus on clinical trials and device development. The department’s infrastructure includes offices housing research fellows, nurses, and administrators, reflecting its growth over five years. Current projects explore non-invasive mapping techniques, AI-driven analysis, and patient-centered quality-of-life measures in atrial fibrillation management. Awards and grants: Supported by major organizations including the British Heart Foundation and Biosense Webster. Collaborations extend to industry leaders in cardiac devices. His contributions to catheter ablation techniques and ambulatory surgical models aim to enhance healthcare efficiency and patient safety.

Xin Liمشاهده پروفایل

مدرس

• Biomedical Engineering
• Cardiac Arrhythmias
• Signal Processing
• +۵ مورد دیگر

Xin Li is a Lecturer in Biomedical Engineering at the University of Leicester, jointly appointed at the School of Engineering and the Department of Cardiovascular Sciences. He holds a BEng in Electrical Information Engineering (University of Science and Technology Beijing, 2011), an MSc in Electrical Electronic Engineering (University of Leeds, 2012), and a PhD in Biomedical Engineering (University of Leicester, 2016). His research focuses on advanced signal processing techniques for cardiac arrhythmias, machine learning applications in biomedical engineering, and wearable medical devices for remote monitoring. Specific interests include P-wave analysis for atrial fibrillation ablation outcomes, sudden cardiac death risk prediction, and non-invasive cardiac imaging techniques. His work integrates computational methods, clinical data, and biomedical engineering to improve diagnostic tools and therapeutic strategies. Notable projects include developing AI-driven Holter monitors for arrhythmia detection and optimizing catheter ablation protocols using electrogram features. He collaborates across disciplines, bridging engineering and clinical cardiology. Research highlights include studies on body surface potential mapping for atrial fibrillation recurrence prediction and the role of wearable devices in healthcare. His lab focuses on translational research, aiming to transition innovations into clinical practice.

Brodie Lawsonمشاهده پروفایل

پژوهشگر ارشد

• Computational Biology
• Cardiac Modeling
• Medical Image Analysis
• +۲ مورد دیگر

Research Fellow at QUT Centre for Data Science and ARC Centre of Excellence, specializing in computational models of cardiac systems. Develops methods to analyze parameter sensitivity and variability in biological systems using statistical approaches. Education: PhD from QUT; BSc (Mathematics/Physics) from QUT. Research: Creates physiologically realistic models of cardiac fibrosis and arrhythmia patterns. Recent work includes digital twin development for cardiac repolarization and Perlin noise applications in tissue modeling. Collaborates with international teams on virtual drug testing platforms. Projects: Funded by ARC Centre for Mathematical and Statistical Frontiers. Publications in Medical Image Analysis and Scientific Reports demonstrate cross-disciplinary approaches to cardiac computational modeling.

• Cardiology
• Electrophysiology
• Cardiac Arrhythmias
• +۳ مورد دیگر

Javad Hashemi serves as an Adjunct Assistant Professor at Queen's University within the School of Computing (Faculty of Arts and Science), with cross-appointments at the Translational Institute of Medicine (TIME). His primary academic affiliation combines computational expertise with clinical cardiology applications. His research focuses on cardiovascular electrophysiology , specializing in atrial fibrillation mechanisms, cardiac arrhythmia detection, and ablation therapy optimization. Key methodologies include intracardiac electrogram analysis, dominant frequency mapping, and machine learning applications for ECG/IEGM signal processing. Current work emphasizes Real-time arrhythmia classification systems Uncertainty-aware diagnostic models Novel ablation guidance techniques using electrogram feature analysis Continual learning frameworks for medical monitoring His publication portfolio demonstrates consistent innovation in translational cardiovascular engineering , with recent work (2022-2025) advancing AI-driven ECG analysis while maintaining continuity with earlier electrophysiology research (2014-2019) on atrial fibrillation mapping and ventricular tachycardia ablation strategies. No scientific awards were documented in the source materials. Dr. Hashemi maintains active research collaborations across Queen's medical and engineering departments, particularly through TIME. His work integrates clinical electrophysiology data with advanced computational modeling to develop next-generation cardiac diagnostic and therapeutic tools. Current projects focus on uncertainty quantification in arrhythmia classification and continual learning systems for longitudinal patient monitoring.

• Cardiac Electrophysiology
• Atrial Fibrillation
• Autonomic Nervous System
• +۳ مورد دیگر

Dr. Rishi Arora is a Professor in the Department of Medicine at the University of Chicago, specializing in cardiac electrophysiology and atrial fibrillation research. His work focuses on understanding the molecular and structural mechanisms underlying atrial fibrillation, with particular emphasis on the role of the autonomic nervous system and oxidative stress in cardiac remodeling. Dr. Arora's research program is supported by multiple NIH grants, including the R35HL161249 award (2022-2028) as Principal Investigator for "New and Disruptive Therapeutic Approaches to Target Fundamental Molecular Mechanisms Underlying Atrial Fibrillation." His laboratory has made significant contributions to understanding how autonomic pathways, calcium signaling, and structural changes in the atria contribute to the initiation and maintenance of atrial fibrillation. His publication record demonstrates a clear progression from basic mechanisms of atrial fibrillation to translational applications. Early work focused on autonomic neural remodeling in the left atrium, while more recent publications explore advanced imaging techniques, gene therapy approaches, and clinical risk prediction models for atrial fibrillation management. His team has developed novel methods for mapping electrical activity in the heart and investigating the molecular underpinnings of arrhythmia substrates. Dr. Arora's work has been widely cited, with several publications exceeding 50 citations, indicating significant impact in the field of cardiac electrophysiology. His research bridges basic science and clinical applications, with numerous studies examining practical aspects of atrial fibrillation treatment including cryoballoon ablation techniques, drug therapies, and risk prediction models.

• Signal Processing
• Algorithms
• Biomedical Engineering
• +۵ مورد دیگر

A.J. van der Veen is a full Professor at the Signal Processing Systems department within the College of Electrical Engineering, Mathematics and Computer Science at Delft University of Technology. His research focuses on developing advanced algorithms for signal processing applications in medical imaging and wireless networks. Key research areas: Signal Processing , Biomedical Engineering , Tensor Decomposition Recent contributions include speckle denoising techniques in ultrasound imaging and novel phase-based distance determination methods for wireless networks. Active editorial roles in IEEE Signal Processing Magazine and IEEE Journal on Selected Topics in Signal Processing .