Gernot Plank is Professor of Computational Cardiology at the Medical University of Graz, Austria. He received an M.Sc. Degree in Electrical Engineering in 1996 and a Ph.D. degree in Biomedical Engineering in 2000, both from the Technical University of Graz, Austria. He has been a Postdoctoral Fellow at Technical University of Valencia, Spain (2000-2002), at the University of Calgary, Canada (2003) in the lab of Profs. Leon and Vigmond and, as a Marie Curie Fellow, he held a Visiting Faculty position at the Johns Hopkins University, USA (2006-2008) in the Trayanova lab. In 2008 he became Academic Fellow at the Oxford e-Research Centre and the Oxford Computing Laboratory at the University of Oxford, U.K before being appointed as Associate Professor in 2011 at the Medical University of Graz. Since 2018 he is Professor of Computational Cardiology and head of the Computational Cardiology Laboratory.

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Robert Arnold is Senior Lecturer at the Medical University of Graz since 2014. He received his M.Sc. in Electrical Engineering from Graz University of Technology, Austria in 2009 and a Ph.D. degree in Cardiovascular Research from Medical University of Graz, Austria in 2013. He was Research Fellow and Assistant Lecturer at Karlsruhe Institute of Technology (KIT), Germany in 2014. He built up expertise in intra- and extracellular potential measurements at cell, tissue and whole organ (Langendorff) level.

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In 2015 I received my Master's degree in Computer Science from Graz University of Technology for my thesis "Optimization Algorithms for Satellite Communication Systems". I continued working in the field of Satellite Communication in Graz and Simulation of Health Care Logistics in Stockholm (KTH). From 2017 until 2021, I was working on the ILearnHeart project under the supervision of Thomas Pock, where I spent the latter half of 2019 at the Center for Computational Medicine in Cardiology in Lugano, collaborating with Rolf Krause at the Università della Svizzera italiana and Angelo Aurrichio at the Cardiocentro Ticino to build patient-specific electrophysiological models from endocardial measurements of patients being treated for atrial fibrillation. I concluded my PhD in 2021 with my thesis "Optimization and Machine Learning for Inverse Problems in Cardiac Electrophysiology". My research interests include Simulations, Machine Learning and Numerical Optimization.

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Christoph Augustin is Associate Professor in Computational Cardiovascular Mechanics at the Medical University of Graz, Austria. He received his M.Sc. and Ph.D. in mathematics and biomechanics from Graz University of Technology under the supervision of Prof. Olaf Steinbach and Prof. Gerhard Holzapfel.
He has been Postdoctoral researcher at the Institute of Biophysics at the Medical University of Graz, Austria in the lab of Prof. Gernot Plank and as Marie Curie Fellow in the computational fluid mechanics lab of Prof. Shawn Shadden at Department of Mechanical Engineering, UC Berkeley.
His main research interests are multi-physics problems, in particular the electro-mechano-fluidic modeling of the heart, and their numerical simulation using high-performance and massively parallel computing.

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Matthias Gsell received his Bachelor’s degree in Applied Mathematics and his Master's degree in Industrial Mathematics at the Graz University of Technology (Austria). He was a member of the International Research Training Group IGDK, which is a joint project of four Universities located in Graz (Austria) and Munich (Germany). During this time he had several research stays at the Technical University of Munich (Germany) in the group of Prof. Dr. Barbara Wohlmuth. In 2017 he received his PhD in Industrial Mathematics at the Graz University of Technology (Austria) under the supervision of Prof. Dr. Olaf Steinbach. Since May 2016, he is a member of the Computational Cardiology Laboratory, with focus on the electromechanics of the heart and the personalization of the underlying models.

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Toni is a Senior Scientist at the Medical University of Graz. He received a Master's degree in Electrical Engineering from University of Technology Graz, Austria, in 2003 and a Ph.D degree in Biomedical Engineering in 2008 at the same University. Profs Pfurtscheller and Müller-Putz supervised his master thesis dealing with biosignal processing and real-time analysis in an industrial application. During his PhD (2003-2008), guided by Prof. Gernot Plank, Toni build up expertise in image based FE mesh generation, parametrization methods and modelling of the specialized cardiac conduction system. He held a visiting scholar position at Johns Hopkins University, USA (2006-2007) in Prof. Trayanova's Lab. In 2010 Toni joined the Computational Cardiology Laboratory as a Postdoctoral Fellow and accepted a Senior Scientist position in 2014 at the Medical University of Graz. He currently focuses on patient-specific models being generated from high resolution imaging data which are used to simulate patient physiology, pathophysiology and response to medical treatment.

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Elena Zappon earned her bachelor’s degree in Mathematics from the University of Ferrara (Italy) and her master’s degree in Applied Mathematics for Biomedical Applications from the University of Trento (Italy). She completed an internship at the Laboratoire Jean Alexandre Dieudonné in Nice (France) for her master's thesis, supervised by Ana Alonso Rodrigez and Francesca Rapetti. She holds a Ph.D. in Mathematical Models and Methods in Engineering from Politecnico of Milano (Italy). Her Ph.D. was held at the MOX - modeling and scientific computing laboratory, in the the successful ERC project iHEART, under the supervision of Alfio Quarteroni and Andrea Manzoni. Her doctoral research focused on developing efficient and reliable full-order and reduced-order models applied to cardiac electrophysiology and electromechanics, with a specific interest in the generation of electrocardiograms. Currently, her research concentrates on developing fully automated and machine-learning-based methods for personalizing and calibrating atrial electrophysiological models.

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Alexander holds a Bachelor's and Master's degree in Biomedical Engineering from the FH Aachen, Germany, and has specialised in computational biophysics. The Bachelor's thesis was in cooperation with the Medical University of Graz (Institute of Biophysics), Austria, and supported by a PROMOS scholarship from the German Academic Exchange Service, the Master's thesis was in cooperation with the University of Oxford (Oxford Orthopaedic Engineering Centre), United Kingdom. Then, he started a joint PhD program between the FH Aachen (Institute of Bioengineering), and the University Duisburg-Essen (Institute of Mechanics), Germany and received the degree in 2021. Based on experiments with beating hiPSC-derived cardiomyocyte monolayers, he developed computer models of multiscale cardiac electromechanics to investigate effects of drugs. This project caught his interest for computational approaches in cardiology and pharmacology and to study how computer models of cardiac function can improve efficacy and safety screenings in drug development, he joined the Computational Cardiology Laboratory in 2020.

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Colleen Longhi joined the Computational Cardiology Laboratory in March 2022. Her contributions have been considered essential from the very beginning and she has quickly built a solid reputation as source of inspiration. From early morning until late night her productivity is outstanding and not only can the team members always count on her warm support in difficult times but she also knows how to enrich every single scientific and not so scientific meeting. Therefore, we are very happy to have her with us.

Michael Hudler finished his bachelors degree in Biomedical Engineering at the University of Technology Graz in 2023. For his master's programme he is concentrating on Computational Neuroscience and Medical Imaging. Under the supervision of Dr. Martin Urschler, he is writing his master thesis about the evaluation of shape models for deep learning based cardiac image segmentation. He is highly enthusiastic about the potential of artificial intelligence in medicine, envisioning a future where AI revolutionizes healthcare delivery and patient outcomes. His passion extends to the advancement of personalized medicine, where tailored treatments and precision diagnostics become the norm, optimizing care for every individual and making healthcare more effective.

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Benedikt Alexander Klöckl is a biomedical engineer specializing in computational neuroscience and software development. He earned his Bachelor's degree in Biomedical Engineering from the Technical University of Graz and is currently pursuing a Master's in the same field, focusing on neuroscience alongside business and management. His academic and professional interests lie at the intersection of engineering, science, and technology, with a particular focus on developing practical solutions for complex challenges. He currently develops scientific software for computational cardiology at the Division of Medical Physics and Biophysics at the Medical University of Graz.

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Veronika Gößler is a biomedical engineering student specializing in computational neuroscience and bioimaging. After completing her Bachelor's degree in biomedical engineering at the Technical University of Graz, she is now pursuing a Master's with a focus on these interdisciplinary fields. For her Master's thesis, she is collaborating with the Computational Cardiology Lab at the Medical University of Graz, under the supervision of Dr. Matthias Gsell and Prof. Thomas Pock at the Institute of Computer Graphics at TU Graz. Her work focuses on mapping cardiac data using optimal transport methods.

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Sara Serafino earned her bachelor’s degree in Mathematics from the University of Trieste (Italy), where she is also completing her master’s degree in the same group of study, subgroup: Computational Mathematics and Modelling. She completed an internship at the Computational Cardiology Laboratory supervised by Dr. Elena Zappon and Prof. Gernot Plank, working on the development of cardiac statistical shape models for bi-atrial geometries using a universal reference system, with the aim of generating in-silico geometries suitable for electrophysiology simulations, including landmarks for anatomical structures. This research will be further developed in her master’s thesis, Dr. Pasquale Claudio Africa.

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Efraín Magaña Tapia earned a Bachelor’s in Engineering and the professional degree of Civil Mechanical Engineer from the Universidad de Chile in 2023, and in the same year began a PhD in Engineering Sciences (with a mention in Mechanical Engineering) at the Pontificia Universidad Católica de Chile under Prof. Francisco Sahli Costabal. His work centers on cardiac electrophysiology and inverse problems, including activation-time estimation from 12-lead ECGs, uncertainty analysis, and exploratory methods for inferring myocardial fiber architecture. He is currently a visiting researcher at the Computational Cardiology Laboratory, Medical University of Graz.

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Lore Van Santvliet obtained a Bachelor’s degree in Bioscience Engineering from the University of Antwerp (Belgum), in 2020. In 2022, she received a Master’s degree in Bioinformatics, followed by an Advanced Master’s degree in Artificial Intelligence in 2023, both from KU Leuven. Since 2023, she is pursuing a PhD at the Department of Electrical Engineering (ESAT) at KU Leuven, under supervision of Prof. Maarten De Vos and Prof. Bert Vandenberk. Her PhD project is centered around exploiting data-driven methods and AI in computational cardiology. During a research visit at the Computational Cardiology Lab in the Medical University of Graz, Austria (February-March 2026), she worked on biventricular statistical shape modeling for subjects with bundle branch block and building a simulation database for the development of AI algorithms.

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Flaminia Mignini earned her BSc in Biomedical Engineering in 2024 and is currently pursuing a MSc in Biomedical Engineering at EPFL, with a focus on biomechanics, statistics and image processing. For her bachelor’s project, she worked on lumped parameter models of the cardiovascular system under the supervision of Prof. Simone Deparis. She also completed an internship at the University Hospital of Lausanne, under the supervision of Prof. Janowczyk, focusing on the segmentation of molar pregnancies using U-Nets and classical morphological operations.

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Karli Gillette received dual undergraduate degrees in Applied Mathematics and Bioengineering from the University of Utah, Salt Lake City, Utah in May 2015. She received a Master's degree in December 2016 under the supervision of Dr. Rob MacLeod at the SCI Institute focusing on the correction and processing of experimentally-recorded canine signals measured using an epericardial sock for use in algorithm validation of implantable cardio defibrillators. In Dec 2021, Karli received a PhD on the automation and functionalization of personalized cardiac models of electrophysiology. Currently, she is working as a PostDoc on extending these personalized models to various clinical and industrial applications.

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Mohammadreza received his undergraduate degree in Biomedical Engineering from the University of Birmingham in 2011. He also received an MSc degree in Biomechanics from the University of Manchester under the supervision of Professor Holly Shiels with a particular attention to the properties of cardiac electrophysiology in different temperatures. In 2018, he joined Professor Peter Weinberg’s Lab at Imperial College London to investigate the effect of aortic geometry on patterns of atherosclerotic lesions using Computational Fluid Dynamics. Mohammadreza’s main research interest is the electromechanical modelling of the human Heart for advanced and robust clinical applications. Currently, he is a member of Computational Cardiology Lab to study a PhD under the supervision of professor Gernot Plank focusing on the development of approaches for calibrating digital twin models of cardiac electrophysiology and mechanics to clinical data.

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Paolo Seghetti received the bachelor degree and MSc degree in biomedical engineering from the University of Pisa, in 2018 and 2021 respectively.

His MSc thesis focused on modeling the effect of pathological sodium channel reduction on synchronization properties of neuronal networks.

In his PhD project with the Health Science Interdisciplinary Center, Sant’Anna School of Advanced Studies, Paolo worked with computational models of cardiac electrophysiology to simulate the onset of arrhythmia, dedicating a particular attention to possible pathological markers for risk stratification in Brugada Syndrome.

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Zorica received her Bachelor's degree in 2017 from the Faculty of Physics, University of Belgrade, group of study: Theoretical and Experimental Physics. In 2018, she completed her Master's study within the same group of study, subgroup: Condensed matter and solid state physic. Her research interests at the time focused on the topology of quantum state spaces and their potential impact on quantum computation, particularly in relation to biological systems.

From October 2019 to April 2023, Zorica was a part of the Marie Curie Action ITN 'CALIPER', researching particle interactions in granular materials and the possibility of information localization using fabric tensors of such systems.

At the moment, she is persuing a PhD under the supervision of Prof. Christoph Augustin. Her research involves integrating biomechanical and hemodynamical model components into the CCL's in-silico modeling framework. Additionally, she is working on data assimilation techniques to personalize combined electro-mechano-fluidic models using multimodal clinical datasets.

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Moritz earned his bachelor's degree in Information and Computer Engineering from Graz University of Technology in 2020. In 2024, he successfully completed his master's degree in Information and Computer Engineering, specializing in Visual Computing and machine learning. His master's thesis, supervised by Professor Thomas Pock and Martin Zach, focused on the utilization of generative diffusion models in MRI reconstruction. At the moment, Moritz is a member of the Computational Cardiology Lab, where he is pursuing his PhD under the supervision of Professor Gernot Plank, focusing on advancing techniques for the personalization of cardiac digital twins. This involves exploring ways to automate and expedite model calibration to align simulated data with clinically observed information. Furthermore, he is working on establishing a framework for quantifying uncertainties in clinical data on model predictions.

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Guadalupe García Isla, Ph.D., is a postdoctoral researcher at the Center for Research and Innovation in Bioengineering (Ci2B), Universitat Politècnica de València (Spain). Her work focuses on the personalization of electrophysiological cardiac computational models using machine learning techniques. She earned a bachelor's degree in Biomedical Engineering from Universidad Carlos III de Madrid (Spain) and an M.Sc. in Computational Biomedical Engineering from Universitat Pompeu Fabra (Spain). She completed a Ph.D. in Biomedical Engineering at Politecnico di Milano (Italy) in 2022, supported by a Marie Skłodowska-Curie fellowship within the MY-ATRIA ITN consortium. Her doctoral research focused on the development of signal processing techniques and AI models for the detection of anomalies and arrhythmias in the ECG, with a research stay at the Medtronic Bakken Research Center (The Netherlands) and collaborations with Lund University (Sweden) and Ospedale Ca' Granda di Milano (Italy). She subsequently worked as a postdoctoral researcher at Politecnico di Milano within the European project PerCard, where she developed multimodal machine learning models for cardiovascular biomarker detection and their integration into clinical decision support systems. In 2024, she was awarded a Juan de la Cierva fellowship to continue her research at Ci2B on the optimization and uncertainty quantification of cardiac digital twins.

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Davide Navarri earned a Bachelor’s degree in Mathematics from the University of Ferrara in 2022 and completed an MSc in Mathematics and Statistics at the University of Trento in 2025, graduating with top marks. His studies focused on applied mathematics, scientific computing, data analysis, and numerical methods for partial differential equations. During his MSc thesis work at The University of Texas at Austin, he investigated neural operator frameworks for PDEs on varying geometries, combining finite element simulations with machine learning methods in high-performance computing environments. He is currently a BioTechMed Guest Researcher at the Computational Cardiology Laboratory, Medical University of Graz, where he works on shape modeling of bi-atrial anatomies using neural implicit representation models.

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In 2018 I received my bachelors dregree in Information and Computer Engineering at the Graz University of Technology. During my master's programme I specialized in Computer Graphics and Vision with an increased focus on machine learning and optimization problems. I concluded my master's degree in 2021 with my thesis about Video Style Transfer using Generative Adversarial Networks, supervised under Prof. Pock at the Institute of Computer Graphics and Vision. In 2022 I started my PhD within the Doctoral School of Mathematics and Scientific Computing at the Computational Cardiology Laboratory where I'm currently working on a novel real-time electro-anatomical mapping system for the online simulation of clinical therapies. I'm highly interested in novel methods, especially in the fields of machine learning, optimization, high performance and quantum computing.

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Franz Thaler is a PhD student under the supervision of Prof. Horst Bischof at the Institute of Computer Graphics and Vision at Graz University of Technology (TU Graz) and collaborates closely with the Computational Cardiology Laboratory at Medical University of Graz. He graduated with a master's degree in Software Engineering and Management from TU Graz with specialization in Computer Vision and Computer Graphics as well as Economics in 2019. Currently, he his investigating novel methods to automatically segment multiple anatomical structures from CT and MR images and has special interest in segmenting various substructures of the heart. In synergy with his previous work his primary research interests consolidate to medical imaging and computer vision as well as to machine and especially deep learning.

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Enia Ottavi received her Bachelor’s degree in Mathematics from the University of Padova (Italy) and her Master’s degree in Applied Mathematics for Biomedical Applications at the University of Trento (Italy). Her Master’s thesis, supervised by Prof. Simone Pezzuto, focused on reconstructing fiber distributions in atrial geometries for electrophysiological simulations. During her Master’s, she also completed an internship at the CARIM institute in Maastricht (Netherlands). In 2025, Enia worked as a research fellow at the University of Trento within the MicroCard project, collaborating with the openCARP platform on cardiac electrophysiology simulations and computational modeling. In 2026, she started her PhD under the supervision of Dr. Elena Zappon within the Doctoral School of Mathematics and Scientific Computing. Her research focuses on patient-specific digital twins for atrial fibrillation, with an emphasis on the role of fibrosis in arrhythmogenesis.

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Alice Ragonesi holds an MSc in Mathematical Engineering from Politecnico di Milano. Her master’s thesis, developed at the Computational Cardiology Lab and Politecnico di Milano under the supervision of Dr. Elena Zappon and Prof. Stefania Fresca, focused on classifying ECG signals affected by Wolff-Parkinson-White syndrome using deep learning models. A key part of her work involved applying eXplainable Artificial Intelligence techniques to better understand model decisions and enhance trust in AI-assisted clinical tools. She is currently preparing a publication based on the main results of her thesis. In the coming year, she will start a PhD at the University of Washington, continuing her collaboration with Prof. Fresca and Dr. Zappon.

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Adrian is currently studying a bachelor degree in Biomedical Engineering at the Universitat Politècnica de València (UPV). He worked as a Research Assistant at the Quantitative EP Lab in ITACA Institute under the supervision of José Millet and Paco Castells. He is doing a 5 semester stay in Graz to finish his studies at University of Technology Graz (TUGraz), and to complete his final bachelor project. Currently, he is being supervised by Dr. Gernot Plank and by Postdoc Karli Gillette as he is working on signals retrieved by the HD-Grid from Abbott and on cardiac simulation in patients with Wolf-Parkinson-White disease, that causes the formation of accessory pathways in the heart.

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Elisa Ramírez holds a degree in Biomedical Engineering from the Universitat Politècnica de València and a Master's in Artificial Intelligence Applied to Health from Universidad Carlos III de Madrid. She is currently pursuing her PhD in the EP Analytics Lab research group at the Universitat Politècnica de València, under the supervision of José Millet and Francisco Castells. She is focusing on cardiac electrophysiology, specifically, in the processing of intracavitary signals to guide ablation procedures in the treatment of arrhythmias. She completed a three-month research stay at the Medical University of Graz, where she worked on the development of cardiac models to validate different methods aimed at improving the accuracy of Omnipolar Technology calculations in HD-Grid catheters.

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Federica Caforio obtained her bachelor's degree in Mathematics at the University of Bari (Italy) and her master's degree in Applied Mathematics at the University of Trento (Italy). She did an internship at the Weierstrass Institute for Applied Analysis and Stochastics (WIAS) in Berlin (Germany) for her master thesis, that was focused on inverse methods for one-dimensional blood-flow modeling, under the supervision of Alfonso Caiazzo and Eleuterio F. Toro. She holds a Phd in Applied mathematics from the Paris-Saclay University (France). Her Phd was held in the M3disim research team, that is a joint team between the research centre Inria and École polytechnique, under the supervision of Dominique Chapelle and Sébastien Imperiale. Her PhD focused on the mathematical analysis and the numerical simulation of elastic wave propagation in soft tissues, with application to cardiac ultrasound elastography. Her current focus lies in the coupling of a three-dimensional code for heart biomechanics with one-dimensional solvers for the human circulation, with application to Pulmonary Hypertension.

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Elias Karabelas received his Bachelor’s degree in Applied Mathematics and his Master's degree in Industrial Mathematics at Graz University of Technology (Austria). He received his PhD in Applied Mathematics in 2015 from Graz University of Technology under the supervison of Prof Olaf Steinbach, Prof Ulrich Langer, and Prof Gernot Plank. During his PhD he was member of the SFB "Mathematical Optimization and Application in Medical Science" (MOBIS). Elias Karabelas is a member of the CCL since 2015. Currently, Elias Karabelas is a visiting Research Associate in the group of Steve Niederer at King's College London. His main research interests are computational fluid dynamics on moving/non-moving domains with particular focus on hemodynamics, non-linear solid dynamics in the context of electromechanics of the human heart, and the simulation of those problems using high performance computing.

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Aurel Neic was a member of the CCL from 2014 to 2019. He has received a PhD in Mathematics, under the supervision of Prof. Gundolf Haase , from the University of Graz in 2015. He has a background in High Performance Computing and Iterative Solver Methods, but his expertise also includes GPU computing, parallelization techniques, software architecture design and mesh generation techniques. Currently, he is the CEO and co-founder of NumeriCor GmbH.

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Justyna holds a Bachelor's and Master's degree in Mechanical Engineering from the RWTH Aachen University, Germany where she focused on Plastics and Medical Engineering. She spent the last year of her studies at the University of Auckland, New Zealand where she was introduced to soft tissue mechanics. There she also worked on her Master Thesis in the Heart Mechanics group under supervision of Prof. Martyn Nash and Dr. Vicky Wang. Her Thesis dealt with the development of a structure-based constitutive modeling framework for heart failure mechanics. After completing her studies Justyna started her PhD in Biomechanics in January 2014 at the Institute of Biomechanics, Graz University of Technology, Austria, under the direction of Prof. Gerhard A. Holzapfel. Her work focused on the experimental and computational analysis of abdominal aortic aneurysms. In November 2018 Justyna joined the Computational Cardiology Laboratory as a Postdoctoral Fellow. She works on the establishment of a growth and remodeling framework to capture the heart's response to pressure overload.

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