جست‌وجوی استاد و پژوهشگر

Lori Isomمشاهده پروفایل

استاد

• Neuroscience
• Pharmacology
• Epilepsy Research
• +۵ مورد دیگر

Lori Isom is the Maurice H. Seevers Professor and Chair of the Department of Pharmacology at the University of Michigan Medical School. She also holds professorships in Molecular and Integrative Physiology and Neurology. Dr. Isom has served as Chair of Pharmacology since 2015, following a national search, after serving as Interim Chair from 2014. Prior to this, she was Director of the Program in Biomedical Sciences and Assistant Dean for Graduate Education from 2008-2014. She serves on many institutional committees including as an elected member of the Medical School Executive Committee. Dr. Isom received her PhD in Pharmacology at Vanderbilt University School of Medicine and completed her postdoctoral training in the laboratory of Dr. William A. Catterall at the University of Washington, a renowned expert in ion channel research whose recent passing (2024) she memorialized in publications. Dr. Isom's research program focuses on voltage-gated sodium channel function and the roles of sodium channel gene variants in developmental and epileptic encephalopathy (DEE), including Dravet syndrome. Her lab investigates SCN1A, SCN1B, and SCN8A DEE variants in mouse models and in human induced pluripotent stem cell (iPSC) neurons and cardiac myocytes. She showed, in collaboration with Dr. Jack Parent, that the high risk of SUDEP in Dravet syndrome may result from cardiac arrhythmias in addition to neuronal hyperexcitability. Most recently, she has collaborated with Stoke Therapeutics to develop the first antisense oligonucleotide precision therapeutic agent for Dravet syndrome, which is now in clinical trials. Her recent publications (2023-2025) demonstrate a strong focus on sodium channelopathies, particularly related to Dravet syndrome and other developmental and epileptic encephalopathies. Her work spans molecular mechanisms, animal models, gene therapy approaches, and translational applications. A notable trend is the expansion of her research into cardiac manifestations of sodium channel disorders, reflecting her discovery that Dravet syndrome involves not just neuronal hyperexcitability but also cardiac arrhythmia risks. Her work on SCN1B-related Dravet syndrome has shown that neonatal gene therapy can reduce seizures and prolong lifespan in mouse models. NINDS Javits R37 MERIT award University of Michigan Rackham Distinguished Graduate Mentoring Award Fellow of the American Association for the Advancement of Science Fellow of the American Society for Pharmacology and Experimental Therapeutics Fellow of the American Epilepsy Society Elected to the National Academy of Medicine (2021) American Epilepsy Society Basic Science Award (2022) Dr. Isom serves as PI of the NIH-funded Pharmacological Sciences Training Program T32 grant and is Co-PI of the NINDS-funded EpiMVP Center Without Walls. She has mentored numerous graduate students and postdoctoral fellows, with several of her trainees now holding independent positions. Her mentorship excellence was recognized with the University of Michigan Rackham Distinguished Graduate Mentoring Award. She served as Director of the Program in Biomedical Sciences and Assistant Dean for Graduate Education from 2008-2014, demonstrating her commitment to academic training. Dr. Isom leads a research laboratory focused on sodium channel function and its implications for neurological and cardiac disorders. Her team includes graduate students, postdoctoral fellows, and research staff working on mouse models of sodium channelopathies and human iPSC-derived neurons and cardiac myocytes. She collaborates extensively with clinicians and researchers both within the University of Michigan and internationally, particularly through her leadership roles in epilepsy research organizations including the Dravet Syndrome Foundation Scientific Advisory Board, American Epilepsy Society, and International League Against Epilepsy Translational Task Force.

Alejo J Nevado-Holgadoمشاهده پروفایل

دانشیار

• Artificial Intelligence in Healthcare
• Bioinformatics
• Mental Health Informatics
• +۶ مورد دیگر

Alejo J Nevado-Holgado is an Associate Professor at the University of Oxford, holding joint appointments in the Department of Psychiatry and the Big Data Institute. He is a key member of Dementia Research Oxford and co-heads the Computational and Molecular Neuroscience laboratory alongside Professor Noel Buckley. His interdisciplinary research team comprises approximately 20 scientists specializing in AI, biochemistry, and bioinformatics, working at the intersection of computational methods and neurological health. Dr. Nevado-Holgado completed his PhD in the University of Bristol, Department of Computer Science, under the supervision of Dr. Rafal Bogacz and Dr. John Terry. His doctoral research focused on mathematical modeling, signal analysis, and machine learning applied to the study of the basal ganglia and Parkinson's disease. Following experimental training at Cambridge, he shifted his focus to applying machine learning and bioinformatics to neurodegeneration research, particularly investigating biomarkers and metabolic networks in Alzheimer's and Parkinson's diseases. Dr. Nevado-Holgado's research program centers on leveraging artificial intelligence and bioinformatics to transform mental health care and drug discovery. His laboratory develops and applies state-of-the-art iPSC, AI, and bioinformatic techniques to better understand neurological disorders. The team's work spans multiple domains including: Neural networks applied to genetics, transcriptomics, proteomics, and iPSC cell microscopy Analysis of Electronic Health Records using natural language processing Integration of biotech laboratory data with real-world clinical evidence Development of personalized medicine approaches and drug repurposing strategies High-performance computing solutions for large-scale biomedical data analysis His recent publication record demonstrates a strong focus on applying AI to mental health diagnostics, neurodegenerative disease biomarkers, and multi-omics data integration. Notable trends include the increasing application of large language models to clinical text analysis, the development of proteomic aging clocks, and the integration of environmental and genetic factors in understanding aging and mortality. His work consistently bridges computational innovation with clinical relevance, seeking to detect neurological disorders in their prodromal stages when interventions could be most effective. Dr. Nevado-Holgado leads or participates in multiple significant research initiatives: Virtual Brain Cloud (EU H2020): €1.5 million European consortium investigating computational simulations for Alzheimer's diagnosis Microbiome in depression (NIH U19): $27 million consortium studying microbiome's role in depression Metabolomics in dementia (MOVE-AD): Consortium investigating metabolomics of dementia Industry projects: £900,000 in funding for applying neural networks to genomics data Blood-brain axis of Alzheimer's disease (AMP-AD): $330,000 project investigating protein levels in Alzheimer's His laboratory team includes lead scientists Laura Winchester (bioinformatics) and Andrey Kormilitzin (AI), along with researchers specializing in genetics, AI microscopy, AI NLP, AI imaging, and iPSC models. The lab actively recruits additional researchers in AI NLP and bioinformatics, reflecting the growing scope of their computational neuroscience work.

Hussein Rashid Al-Khalidiمشاهده پروفایل

استاد

• Cardiovascular Clinical Trials
• Medical Devices
• Survival Analysis
• +۱۱ مورد دیگر

Hussein Rashid Al-Khalidi is a Professor of Biostatistics & Bioinformatics at Duke University, with a primary affiliation in the Division of Biostatistics, Epidemiology, and Research Design (BERD) Methods Core. He serves as a Master of Biostatistics Instructor and is a member of the Duke Clinical Research Institute (DCRI). Education : Ph.D. in Statistics from Texas A&M University (1988) Research Interests : Dr. Al-Khalidi specializes in cardiovascular clinical trials and medical device evaluation, with methodological expertise in survival analysis, group-sequential methods, and continuous-time Markov modeling. His work spans time-to-recurrent events analysis, stochastic processes, linear models, adaptive trial designs, and dose-response modeling for clinical experiments. Current projects include statistical analysis for cardiac arrest interventions and urinary stone disease research. Publication Trends : Recent articles demonstrate interdisciplinary applications of biostatistics in Urology (STENTS study pain modeling) Cardiology (SGLT-2i/GLP-1RA discontinuation analysis) Neurology (rTMS and dystonia research) Emergency Medicine (regional cardiovascular care trials) His methodological contributions appear in predictive modeling, recurrent event analysis, and clinical trial design. Scientific Awards & Grants : American Heart Association (Drone-delivered AEDs) National Institutes of Health (RACE-CARS, STICHES, PROMISE-SAFER, Urinary Stone Network) Medtronic Foundation (Heart Rescue) Columbia University (PROMISE-SAFER) Claret Medical, Inc. (Sentinel System Analysis) Collaborations : Dr. Al-Khalidi collaborates extensively with urology, neurology, and cardiology departments across multiple institutions including University of Washington, Columbia University, and academic hospitals.

• Mathematical and Computational Biomedical Engineering
• Drug Delivery Systems
• Cardiovascular Medical Implant Design
• +۵ مورد دیگر

Dr. Sean Mcginty is a Reader in Biomedical Engineering at the University of Glasgow's School of Engineering, where he leads research at the intersection of mathematical modeling, cardiovascular medicine, and drug delivery systems. He also serves as Senior Senate Assessor for Student Conduct within Academic Services. Previously, he directed the Centre for Mathematics applied to the Life Sciences (CMALS) from 2016-2024 and has held leadership roles in several professional organizations. Mcginty's research focuses on developing mathematical and computational tools to understand biological processes, disease mechanisms, and treatment approaches. His work particularly emphasizes cardiovascular medical implant design, drug delivery systems, and mathematical modeling of percutaneous coronary intervention with stents and balloons. He is renowned for pioneering work in computational modeling of drug-eluting stents, including developing the first predictive model of in vivo drug-eluting stent performance and the first continuum computational model of restenosis subject to drug delivery from stents. His research group, MaCBE (Mathematical and Computational Biomedical Engineering), collaborates with experimental groups, clinical centers, and industry partners to advance healthcare through machine learning and AI applications. Analysis of Dr. Mcginty's recent publications reveals a strong focus on computational modeling of drug delivery systems, particularly for cardiovascular applications. His work spans from fundamental mathematical approaches like constrained Bayesian optimization and Laplace transform modeling to practical applications in stent and balloon-based drug delivery. A consistent theme is the application of mathematical rigor to solve complex biomedical problems, with increasing emphasis on patient-specific modeling and multiscale approaches that bridge molecular mechanisms with clinical outcomes. Prof Tom Gibson Memorial Prize for pioneering work in mathematical modeling of PCI procedures and devices Fellow of The Institute of Mathematics & its Applications (FIMA) Chartered Mathematician (CMath) Dr. Mcginty has extensive experience in knowledge exchange and impact culture, having served as Director of CMALS from 2016-2024 and as School lead for Impact Culture since 2022. He has collaborated with numerous companies and clinicians to ensure his research remains relevant and driven by clinical need. His work has resulted in significant grants, including a major EPSRC grant enabling the creation of The EPSRC Centre for Future PCI Planning. He actively engages with the public through events like the Glasgow Pint of Science festival and has organized the College-wide Images of Impact Competition. As director of the European Special Interest Group on 'Implantable Devices and Drug Delivery Systems' under the European Consortium for Mathematics in Industry (ECMI), Dr. Mcginty leads an international team advancing research in cardiovascular medical devices. His laboratory combines mathematical modeling expertise with experimental validation through collaborations with clinical partners and industry, creating a robust ecosystem for translating theoretical advances into practical medical solutions.

Rory McCrimmonمشاهده پروفایل

استاد

• Diabetes Research
• Hypoglycemia
• Type 1 Diabetes
• +۵ مورد دیگر

Professor Rory McCrimmon is an internationally renowned physician-scientist and academic leader, currently serving as Dean of the School of Medicine at the University of Dundee. With a distinguished career spanning clinical medicine, diabetes research, and academic leadership, he is recognized for his pioneering work in understanding the brain's response to hypoglycaemia and its implications in type 1 diabetes. Professor McCrimmon received his medical education at the University of Edinburgh, where he completed his medical training and obtained an MD focused on the cognitive impact of acute hypoglycaemia. He further developed his research expertise through academic positions at Yale University before returning to the UK to pursue his career at the University of Dundee. His research focuses on the fundamental mechanisms by which the brain detects low glucose levels (hypoglycaemia) and how these mechanisms are disrupted in type 1 diabetes. Professor McCrimmon has made key discoveries establishing roles for AMP-activated protein kinase and the ATP-sensitive potassium channel in glucose sensing, and demonstrated that impaired awareness of hypoglycaemia develops as a result of a specialized form of memory called Habituation. His work bridges basic science and clinical applications, significantly advancing our understanding of diabetes complications. Professor McCrimmon's extensive publication record, with over 20,000 citations, demonstrates his significant impact in diabetes research. His recent work spans diverse areas including Type 1 and Type 2 diabetes complications, cardiovascular outcomes, advanced monitoring technologies, and pharmacological interventions. His research shows a clear trajectory toward translational applications that improve clinical diabetes management and patient outcomes. His scientific achievements have been recognized with numerous prestigious awards: Dorothy Hodgkin Lecture from Diabetes UK (2022) RD Lawrence Lecture from Diabetes UK (2015) Fellow of the Royal Society of Edinburgh (2020) Fellowship of the Royal College of Physicians (Edinburgh) (2010) As an academic leader and mentor, Professor McCrimmon has supervised numerous PhD students, postdoctoral fellows, and academic trainees. He has served in key educational roles including Programme Lead for the Academic Foundation Doctors in the Eastern Deanery and as a member of the Scottish Translational Medicine Training Initiative. His contributions to medical education include co-authoring the Chapter on Diabetes in Davidson's Principles and Practice of Medicine, a foundational text read by over 2 million medical students. As Dean, he jointly chairs the ScotGEM post-graduate Entry Medical Programme and works to advance medical education through curriculum development and inter-institutional collaboration. Professor McCrimmon plays a central role in advancing diabetes research in Scotland as the Diabetes Champion for the Scottish Diabetes Research Network (SDRN), leading efforts to support and coordinate high-quality clinical trials across the country. He has secured substantial funding to promote collaborative, translational research and has served as the UK Chief Investigator in multiple multi-centre international clinical trials. His leadership extends to national and international advisory roles with organizations including the Juvenile Diabetes Research Foundation, Medical Research Council, and various editorial boards.

Jonathan Cohenمشاهده پروفایل

استاد

• Cognitive Control
• Computational Neuroscience
• Psychiatric Disorders
• +۵ مورد دیگر

Jonathan Cohen serves as the Robert Bendheim and Lynn Bendheim Thoman Professor in Neuroscience at Princeton University's Princeton Neuroscience Institute, where he leads groundbreaking research on the neurobiological foundations of cognitive control and its disruption in psychiatric disorders. His work bridges computational modeling, cognitive science, and clinical neuroscience to unravel how distributed neural systems enable goal-directed behavior. Education: M.D. from the University of Pennsylvania Ph.D. from Carnegie Mellon University Cohen's research centers on cognitive control mechanisms involving prefrontal cortex, anterior cingulate cortex, basal ganglia, and neuromodulatory systems, with direct applications to schizophrenia and depression. His lab develops mechanistically explicit computational models to explain how billions of neurons coordinate purposeful behavior, seeking to establish a theoretical foundation for psychiatric research. This integrative approach combines empirical neuroimaging with rigorous mathematical frameworks to decode the neural basis of executive function. Analysis of his recent publications (2022-2025) reveals a compelling evolution toward interdisciplinary synthesis, where computational neuroscience increasingly intersects with artificial intelligence. His work now explores emergent symbolic reasoning in neural networks, cerebellar-cortical interactions in neurodevelopmental disorders, and the neural reconfiguration underlying task switching – all while maintaining clinical relevance to mental illness. Scientific Awards: Election to American Academy of Arts and Sciences APS William James Award Cohen mentors graduate students including Younes Strittmatter and directs the Neuroscience of Cognitive Control Lab, which has secured substantial funding such as a $16M Princeton-Rutgers Collaboration Grant for mental illness research. His lab actively investigates how disturbances in brain function manifest as psychiatric symptoms, with recent projects examining cognitive control allocation in depression and neural mechanisms of grief. The Neuroscience of Cognitive Control Lab employs a multidisciplinary framework combining computational modeling, fMRI, behavioral experiments, and machine learning to dissect the architecture of executive function. Current initiatives explore cerebellar contributions to cognitive aging, abstract reasoning mechanisms, and the development of theoretically grounded interventions for psychiatric disorders through collaborative neuroscience initiatives.

• Biomedical Engineering
• Optical Spectroscopy
• Medical Instrumentation
• +۳ مورد دیگر

B.H.W. Hendriks is a Professor in the Department of Mechanical Engineering at Delft University of Technology, specializing in Medical Instruments & Bio-Inspired Technology. His research develops optical and signal processing solutions for medical applications, particularly in surgical environments and tissue analysis. His primary research domains include: Biomedical Engineering Optical Spectroscopy (Diffuse Reflectance) Medical Device Development Surgical Technology Cardiac Signal Processing Tissue Characterization Analysis of his 55+ publications reveals dual expertise: (1) Intraoperative optical sensing (e.g., fiber-optic tissue identification during spine surgery and electrosurgery), and (2) Advanced signal processing for cardiac diagnostics (atrial fibrillation mapping via electrograms/ECG). His work bridges mechanical engineering with clinical practice through real-time surgical workflow analysis and tissue-mimicking phantoms. Hendriks actively supervises research students and has generated 3 significant datasets for tissue characterization. His fingerprint shows dominant activity in spectroscopy (100%), surgery (93%), and tissue analysis (91%), with emerging work in human pose tracking for cardiac catheterization laboratories.

Evgueni Smirnovمشاهده پروفایل

استادیار

• Machine Learning
• Conformal Prediction
• Time Series Forecasting
• +۳ مورد دیگر

Evgueni Smirnov is an Assistant Professor in the Artificial Intelligence Department of Advanced Computing Sciences within the Faculty of Science and Engineering . His research focuses on Machine Learning , Conformal Prediction , Time Series Forecasting , and Biomedical Data Analysis . Key research areas include data prediction , classification , instance transfer , and conformal prediction with applications in both computer science and biomedical domains. His work spans predictive modeling , gene expression analysis , and inflammatory response mechanisms in cardiovascular diseases. He has contributed to editorial activities, including co-editing books through ML Research Press , and organized academic events like the Symposium on Conformal and Probabilistic Prediction with Applications . His publications demonstrate expertise in transfer learning , multivariate time-series forecasting , and cross-species biomedical modeling .

Beining Chenمشاهده پروفایل

استاد

• Medicinal Chemistry
• Computer-Aided Molecular Design
• Combinatorial Chemistry
• +۷ مورد دیگر

Prof. Beining Chen is a Professor of Medicinal Chemistry at the School of Mathematical and Physical Sciences , University of Sheffield. Holding a PhD in Chemistry from the University of Glasgow (1991), she has pioneered research in computer-aided molecular design and combinatorial chemistry for drug discovery targeting prion diseases (TSEs) and neurodegenerative disorders like Alzheimer’s. Education: BSc (1984), MSc (1987) - China; PhD (1991) - University of Glasgow Appointments: Research Fellow (Oxford), Lecturer (Cranfield), Lecturer (Sheffield), Professor (Sheffield, 2014) Her research focuses on stabilizing prion protein conformations and targeting amyloid pathways , securing over £1.15M in Department of Health funding. She also explores natural product chemistry for lead compounds in cardiovascular, CNS, and antiviral research. Recent publications emphasize de novo drug design , computational proteomics , and structure-activity relationship studies for neurodegenerative diseases. Teaching areas include Medicinal Chemistry , Chemical Biology , and molecular modeling across undergraduate and postgraduate levels.

Jon Viventiمشاهده پروفایل

دانشیار

• Biomedical Engineering
• Neuroscience
• Flexible Electronics
• +۳ مورد دیگر

Jon Viventi is the Hawkins Family Associate Professor of Biomedical Engineering at Duke University. He holds secondary appointments as Assistant Professor in Neurosurgery and Assistant Professor of Neurobiology , and is a Faculty Network Member of the Duke Institute for Brain Sciences . His research focuses on developing flexible electronics for high-resolution neural interfaces, with applications in diagnosing/treating epilepsy and advancing brain-machine interfaces . Research Interests Dr. Viventi's work combines flexible electronics and high-density neural recording to address clinical challenges. His innovations include µECoG arrays for cortical mapping, low-power neural interfaces , and bioresorbable devices . Collaborations span neurology, neurosurgery, and materials science , with industrial partnerships yielding five patents. Scientific Recognition MIT Technology Review Innovators Under 35 (2014) Popular Science Brilliant 10 (2014) Publications Recent work includes high-density µECoG arrays for stroke monitoring (2024), artifact-free neural interfaces (2019), and foundational flexible electronics for neurophysiological mapping (2011). Articles appear in Nature Neuroscience , Science Translational Medicine , and Nature Materials .

• Biomedical Engineering
• Cardiovascular Mechanics
• Computational Fluid Dynamics
• +۵ مورد دیگر

Fiona Malone is a Lecturer in the Department of Mechanical & Industrial Engineering at the University of Galway, Ireland, where she also serves as a Principal Investigator for both the Engineering Research Group (ERG) and the Medical and Engineering Technologies Gateway (MET). Her research bridges mechanical engineering principles with medical applications, focusing on cardiovascular mechanics and stroke-related phenomena. Dr. Malone's research interests center on the intersection of biomedical engineering and cardiovascular mechanics, with particular emphasis on embolism, atrial fibrillation, and aortic arch hemodynamics. She employs patient-specific modeling approaches to investigate blood flow patterns and emboli trajectory paths under various physiological conditions. Her work combines experimental in vitro studies with computational methods to better understand stroke mechanisms and develop potential interventions. Analysis of Dr. Malone's publications reveals a consistent focus on cardiovascular biomechanics with increasing integration of machine learning techniques in recent years. Her earlier work concentrated on mechanical characterization of embolus analogues and hemodynamics in patient-specific models, while her more recent publications incorporate computational methods like gradient boosting algorithms to address class imbalance problems in medical data analysis. Dr. Malone has achieved significant recognition in her field with an h-index of 78 according to Scopus metrics. Her publications have garnered citations across multiple disciplines, demonstrating the interdisciplinary impact of her research. As a Principal Investigator, Dr. Malone leads research initiatives within the Engineering Research Group and the Medical and Engineering Technologies Gateway. Her collaborative network spans multiple institutions and disciplines, with frequent co-authorship with researchers specializing in both engineering and medical fields. Her research has practical implications for understanding stroke mechanisms and developing improved diagnostic and therapeutic approaches.

Jinqiang Houمشاهده پروفایل

دانشیار

• Radiochemistry
• Medicinal Chemistry
• Molecular Imaging
• +۶ مورد دیگر

Dr. Jinqiang Hou serves as an Associate Professor and LU-TBRHRI Research Chair in the Department of Chemistry at Lakehead University, where he has been faculty since October 2018. His work bridges radiochemistry, medicinal chemistry, and organic synthesis to develop molecular tools for disease imaging and therapy, with laboratory facilities in CB4019, CB2029, and TBRHRI 3115. Education: Ph.D. in Medicinal Chemistry, Sun Yat-sen University (2012) Postdoctoral training at University of South Australia, London Health Sciences Centre, and Western University Research Focus: Dr. Hou pioneers radio-labelled compounds for PET imaging of diseases and computational drug design targeting disease-relevant proteins. His lab integrates molecular modeling, organic synthesis, and biological evaluation to create theranostic agents, with emphasis on oncology applications and the strategic integration of PET imaging into drug discovery pipelines. Publication Trends: Recent work (2023-2025) demonstrates convergence of AI-driven molecular optimization, G-quadruplex-targeted cancer imaging probes, and precision PET radioligands for cardiac and tumor diagnostics. Key themes include metastasis inhibition via LPA1 antagonists, kinase-targeted therapies, and transformer-based multi-objective drug design. Laboratory Operations: The Hou Lab maintains active research in radiochemistry and medicinal chemistry, supported by external funding and equipped for synthetic chemistry, molecular imaging, and preclinical evaluation. The team engages in interdisciplinary collaborations and recruits new members through university channels.

Emrah Irmakمشاهده پروفایل

دانشیار

• Biomedical Image Processing
• Signal Processing
• Medical Image Registration
• +۳ مورد دیگر

Assoc. Prof. Emrah Irmak serves as Associate Professor and Deputy Head of Department (2020-2023) at the Department of Electrical and Electronic Engineering, Rafet Kayış Faculty of Engineering, Alanya Alaaddin Keykubat University, where he currently holds board membership (2024). Previously, he was Doctor Lecturer and Research Assistant at Karabük University's Department of Biomedical Engineering (2012-2019). His academic credentials include: Doctorate in Electrical-Electronic Engineering, Karabük University (2018) Master's in Electrical and Electronics Engineering, Gaziantep University (2014) Bachelor's degree, Opole University of Technology (2011) Dr. Irmak's research pioneers biomedical image processing with applications in brain tumor progression analysis, cancer diagnosis, and Alzheimer's disease detection. His work integrates deep learning with traditional image processing techniques for medical applications, while extending to tribocorrosion analysis of orthopedic implants and IoT systems for healthcare and mining safety. Key innovations include 3D medical image registration frameworks and novel convolutional neural network architectures for automated pathology detection. His publication trajectory demonstrates consistent advancement in applying AI to critical healthcare challenges, with recent focus on multi-modal diagnostic systems for cancer and neurological disorders through integration of image processing, signal analysis, and deep learning. His scientific recognitions include: Distinction in Scholarship in Physiological Genomics (2020) TÜBİTAK Publication Incentive Award (2021) The World's Most Influential Scientists (Stanford University, 2023 & 2024) Dr. Irmak has supervised Master's students Mustafa Burak Turköz (3D medical image registration for brain tumors) and Ergun Ercelebi (medical image registration for tumor growth analysis), and served as main jury for five graduate thesis defenses at Karabük and Gaziantep Universities. His research projects include: National project on Tribocorrosion Properties of Titanium Implants (2021-2022) National project on 3D Medical Image Registration for Brain Tumor Evolution (2017-2018) He actively contributes to scientific advancement as reviewer for Current Medical Imaging, Health Informatics Journal, Plos One, and Turkish Journal of Electrical Engineering and Computer Sciences, while maintaining international collaboration through Erasmus exchange programs.

Brooke N. Wolfordمشاهده پروفایل

پژوهشگر ارشد

• Statistical Genetics
• Precision Public Health
• Cardiovascular Disease Epidemiology
• +۵ مورد دیگر

Brooke N. Wolford is a Marie Skłodowska-Curie Postdoctoral Fellow at the Norwegian University of Science and Technology (NTNU), affiliated with the Department of Public Health and Nursing within the Faculty of Medicine and Health Sciences. She leads the ProtectHearts and HUNT AI for Heart Health projects at the HUNT Center for Molecular and Clinical Epidemiology, while also contributing to the EU-funded INTERVENE project through the Finnish Institute for Molecular Medicine. Her work bridges statistical genetics, computational biology, and clinical applications to advance precision public health initiatives. Dr. Wolford earned her PhD in Bioinformatics and Master's in Statistics from the University of Michigan, where she completed her dissertation on 'Genetic Discovery and Precision Medicine in Cardiovascular Diseases Using Electronic Health Record-linked Biobanks' under Dr. Cristen Willer and Dr. Michael Boehnke. Her undergraduate training includes a Bachelor of Science in Quantitative Biology with highest honors from the University of North Carolina at Chapel Hill, where she was a Phi Beta Kappa honors graduate. Her research program focuses on artificial intelligence-driven precision public health, particularly in cardiovascular disease prediction and prevention. By integrating genomics, proteomics, and clinical data from large biobanks like HUNT, UK Biobank, and FinnGen, she develops novel risk prediction models that address critical gaps in women's heart health and young adult disease prevention. Her work on polygenic risk scores and proteomic biomarkers aims to transform population-scale screening programs through explainable AI methodologies. Dr. Wolford's recent publications demonstrate significant contributions to genetic epidemiology, with high-impact work in Nature Genetics, Nature Communications, and Circulation: Genomic and Precision Medicine. Her research outputs reveal consistent themes in cross-population polygenic score development, sex-specific disease mechanisms, and innovative biobank data integration approaches that enhance cardiovascular risk prediction across diverse populations. 2022/2023 Best Dissemination Award (K.G. Jebsen Centers) 2022 ASHG Trainee Research Excellence Award Finalist 2021 ASHG Trainee Research Excellence Award Semi-Finalist National Science Foundation Graduate Research Fellowship Genome Sciences Predoctoral Traineeship University of Michigan Program in Biomedical Sciences 20th Anniversary Award As a dedicated mentor, Dr. Wolford supervises multiple graduate students across Master's and PhD programs at NTNU, focusing on proteomic risk prediction for diabetes, cardiovascular-Alzheimer's disease connections, and polygenic scoring for women's heart health. She actively promotes open science through R-ladies Trondheim leadership and develops educational resources like the Health AI in R workshop. Her ongoing projects with INTERVENE and ProtectHearts secure substantial European research funding for translational genomics initiatives. Dr. Wolford co-leads the HUNT AI for Heart Health initiative and ProtectHearts project within the HUNT Center for Molecular and Clinical Epidemiology. These teams integrate computational biologists, clinicians, and epidemiologists to develop explainable AI models that translate genomic discoveries into clinical prevention strategies, with particular emphasis on addressing health disparities in cardiovascular outcomes for women and younger populations.

Einar Heibergمشاهده پروفایل

مدرس ارشد

• Medical Image Processing
• Deep Learning
• Cardiovascular Magnetic Res
• +۷ مورد دیگر

Einar Heiberg is a Senior Lecturer at Lund University , Faculty of Medicine, Department of Clinical Physiology. He serves as Project Manager of the Lund Cardiac MR Group and Director of the 3D Centre at Skåne University Hospital. His academic appointments include Associate Senior Lecturer at WCMM (Wallenberg Centre for Molecular Medicine) and affiliation with the LTH Profile Area 'Engineering Health.' Senior Lecturer, Clinical Physiology (Lund University) Project Manager, Lund Cardiac MR Group Director, 3D Centre @ Skåne University Hospital Associate Senior Lecturer, WCMM Research Interests : Heiberg specializes in medical image processing , combining classical image analysis with deep learning techniques. His work focuses on cardiovascular MRI applications, particularly software development for cardiac modeling and segmentation. Key areas include: Deep learning for 3D medical imaging Cardiac MRI feature tracking Tricuspid/right ventricle flow dynamics AI in surgical planning Segmentation of cardiovascular structures Modeling left ventricular mechanics Scientific Contributions : Heiberg's 160+ research outputs show expertise in: Cardiac Magnetic Resonance Imaging Left Ventricle and Myocardial Analysis Deep Learning in Clinical Applications 3D Printing for Medical Use Awards & Appointments : Clinical Fellow, WCMM Labs & Collaborations : He leads the 3D Centre (LinkedIn, website) and contributes to AI research through Lund's AIML@LU network and AI Lund: Lund University AI Research .