جست‌وجوی استاد و پژوهشگر

Sara Maloniمشاهده پروفایل

دانشیار

• Low-dimensional Topology
• Hyperbolic Geometry
• Geometry
• +۵ مورد دیگر

Sara Maloni is an Associate Professor in the Department of Mathematics at the University of Virginia, part of the College of Arts and Sciences. Her office is located in Kerchof Hall, and she is actively engaged in research and graduate mentoring. Position: Associate Professor Institution: University of Virginia Department: Mathematics Email: sm4cw@virginia.edu She earned her Ph.D. from a leading institution in mathematics, though specific details are not provided in the current text. Research Focus: Low-dimensional Topology, Hyperbolic Geometry, Representation Theory Subfields: Character varieties, geometric structures on surfaces, Teichmüller theory Her research explores the interplay between geometry, topology, and algebra, particularly in two- and three-dimensional spaces. She investigates hyperbolic structures on surfaces and their representations into Lie groups, contributing to the understanding of moduli spaces and geometric invariants. Her work often involves computational and visual approaches to abstract mathematical concepts. Although no list of recent articles is provided in the scraped content, her research is supported by major NSF grants, indicating active publication and scholarly output in geometric topology and related fields. She has received significant recognition through competitive federal funding: NSF CAREER Award (DMS-1848346) NSF Research Training Group (RTG) Grant (DMS-1839968) Dr. Maloni is actively involved in mentoring the next generation of mathematicians. She advises multiple Ph.D. students with expected graduations from 2024 to 2028 and has guided master’s students through the Distinguished Major Program. Her advising spans topics in hyperbolic geometry and character varieties, reflecting her research expertise. She also mentored postdoc Filippo Mazzoli from 2020 to 2023. She is committed to inclusiveness in mathematics and aligns with Federico Ardila’s axioms, emphasizing equity, joy, and empowerment in mathematical education and research.

Pratik Shahمشاهده پروفایل

استادیار

• Artificial Intelligence in Medicine
• Computational Medicine
• Biomedical Imaging
• +۱۳ مورد دیگر

Dr. Pratik Shah is an Assistant Professor in the Department of Pathology at the University of California, Irvine (UCI) School of Medicine. He leads a cutting-edge research group focused on translational artificial intelligence and biomedical technologies to advance diagnostic imaging, uncover biological mechanisms, and enable clinical deployment of digital therapeutics. Institution: University of California, Irvine School: School of Medicine Department: Department of Pathology Academic Rank: Assistant Professor Email: pratik.shah@uci.edu Dr. Shah's research lies at the intersection of computational medicine, artificial intelligence, and biomedical imaging. His work emphasizes developing interpretable and explainable AI systems that enhance model effectiveness, safety, and clinical utility. Key research areas include generative AI for nondestructive histopathology, deep learning for medical image analysis, AI-driven clinical decision support for infectious diseases, and multimodal imaging for biological insights. His lab is dedicated to creating equitable and responsible technologies to improve diagnosis and treatment of cancer, infectious diseases, and neurological disorders. The recent publications highlight a strong trend in applying deep learning to digital pathology, particularly in computational staining and tumor detection from non-stained images. There is a consistent focus on developing interpretable AI tools for medical image segmentation, with applications in cancer diagnostics, sepsis detection, and dental imaging. The research spans from foundational AI methods to clinical validation, showing a trajectory toward regulatory science and real-world deployment of AI in healthcare. MIT NEWS feature on computational staining research SPIE publication selected for Deep-Dive spotlight session SPIE publication selected for oral presentation IEEE BioInformatics and BioEngineering publication selected for oral presentation Dr. Shah has mentored a diverse group of students and postdoctoral associates, including PhD candidates in Mechanical Engineering at MIT and undergraduate researchers in Electrical Engineering and Computer Science. His trainees have contributed to high-impact publications in journals like JAMA Network and conferences like IEEE EMBC. He has fostered collaborations with institutions including Stanford, UCSF, and the FDA, indicating strong research outreach and interdisciplinary partnerships. His lab has received recognition through media features and conference selections, reflecting the significance and innovation of his work in AI for healthcare. Dr. Shah leads a multidisciplinary research team comprising postdoctoral associates, graduate students, research staff, and student researchers, primarily focused on machine learning and medicine. The lab has strong ties to MIT, where much of the prior research was conducted, and maintains collaborations with clinical and engineering experts across the US.

Andreas Eckhardtمشاهده پروفایل

استاد

• Digital Transformation
• Information Systems Security
• Social Media Analysis
• +۳ مورد دیگر

Andreas Eckhardt is a Full Professor of Information Systems at the University of Innsbruck since 2020, previously holding roles at GGS Heilbronn and visiting positions at the University of Hong Kong and Washington State University. He earned his Ph.D. (summa cum laude) in Information Systems from Goethe University Frankfurt and previously worked as a project manager for DaimlerChrysler Taiwan. Research Focus: His work centers on digital transformation, misinformation dynamics on social media (including deepfake impacts), cybersecurity in generative AI, and decentralized virtual organizations. He has published over 100 articles in top journals like MIS Quarterly and Information Systems Journal , authored two books, and received awards such as the Magid Igbaria Outstanding Paper Award. Editorial Roles: Senior Editor at Information Systems Journal and editorial board member of AIS Transactions on Human-Computer Interaction . He chairs AIS SIGADIT and BAFIT Network committees. Awards & Recognition: ECIS Best Research in Progress Paper Award (2018), SIGADIT Best Paper Award (2021), and contributions to editorial review processes for major IS conferences (ICIS, ECIS, AMCIS). Grants & Collaboration: Active in design science research, with projects on digital ethics, AI governance, and organizational innovation. His work bridges technical and social aspects of IT adoption in complex organizational environments.

• Osteoarthritis
• Degenerative Joint Diseases
• Chronic Pain Mechanisms
• +۷ مورد دیگر

Kyle Allen is a Professor at the University of Florida's Herbert Wertheim College of Engineering, specializing in Biomedical Engineering. His research focuses on understanding how degenerative musculoskeletal diseases like osteoarthritis (OA) and intervertebral disc degeneration lead to chronic pain and disability. He employs rodent disease models and clinical studies in both veterinary and human patients to explore behavioral, molecular, and structural aspects of these conditions. Education: B.S. in Mechanical Engineering & Economics, Rose-Hulman Institute of Technology (2002) Ph.D. in Bioengineering, Rice University (2006) Post-doctoral Fellowship in Orthopedic Surgery, Duke University (2011) Research Interests: Dr. Allen’s lab develops novel behavioral assays, magnetic nanoparticle-based diagnostic tools, and tissue engineering strategies to improve osteoarthritis treatment and preclinical-to-clinical translation. His work intersects biomechanics, molecular biology, and neurophysiology to address unmet clinical needs in joint disease management. Publications: His recent work includes AI-driven gait analysis in equine and rodent models, nanoparticle-based therapies, and proteomic studies of disease mechanisms. Key trends include leveraging machine learning for phenotypic analysis and exploring nanotechnology for targeted drug delivery. Awards: UF Doctoral Mentoring Award (2022-2023) NIH K99/R00 Pathways to Independence Award (2014) J. Crayton Pruitt Family Term Fellow (2017-2020) Advising & Grants: While specific student names are not listed, Dr. Allen’s lab focuses on training interdisciplinary researchers. His grants support studies on neuroimmune interactions in pain and translational biomaterials development. He chairs the Young Investigator Subcommittee for the Osteoarthritis Research Society International. Labs/Teams: The Orthopaedic Biomedical Engineering Laboratory collaborates with veterinary and clinical partners to bridge basic science and clinical applications in musculoskeletal health.

Gabriel Pereiraمشاهده پروفایل

استادیار

• Critical Algorithm Studies
• Computer Vision
• Surveillance Studies
• +۵ مورد دیگر

Gabriel Pereira is Assistant Professor in AI & Digital Culture at the University of Amsterdam (UvA), based at the Media Studies department and the Institute for Logic, Language and Computation (ILLC). His primary affiliation is with the Natural Language Processing & Digital Humanities (NLP&DH) group. Pereira's research focuses on the critical study of data and algorithms, particularly as they intersect with vision, images, and surveillance systems. He brings an interdisciplinary approach that combines Science and Technology Studies (STS), critical algorithm studies, platform studies, and artistic interventions to examine how computational systems shape social relations and power structures. Pereira's research interests center on critical perspectives of computer vision and algorithmic governance, with particular attention to how these technologies operate in contexts of surveillance, platform labor, and digital culture. His work critically examines hegemonic computer vision systems that reinforce surveillance capitalism while exploring alternative ways of seeing and engaging with technology. He has conducted extensive research on Automated License Plate Recognition systems, WhatsApp disruptions in Brazil, and the political economy of smart surveillance projects like Curitiba's 'Digital Wall.' His methodology combines qualitative research with practice-based inquiry, including arts-based and interventionist approaches that challenge dominant technological narratives. His publication trends reveal a consistent focus on critical examinations of algorithmic systems, with growing attention to resistance practices, decolonial perspectives, and situated knowledge from the Global South. The articles show a trajectory from analyzing specific surveillance technologies toward broader theoretical frameworks for understanding algorithmic antagonisms and developing critical technical practices. His work consistently bridges theory and practice, often collaborating with artists and activists to create interventions that make visible the hidden operations of algorithmic systems. Independent Research Fund Denmark International Postdoc grant Deviant Practice Grant (Van Abbemuseum) Pereira actively organizes academic and artistic events, serving as Secretary of the Association of Internet Researchers and participating in the Tierra Común network. He co-organized the Con/Crit/Tec residency in São Paulo that brought together over 80 transdisciplinary researchers to explore alternative geographies of digital consciousness. His collaborative approach extends to numerous grant-funded projects examining platform labor, algorithmic surveillance, and critical data literacy. Pereira emphasizes organizing as an essential element of research work, facilitating knowledge exchange between academic, artistic, and activist communities. He is affiliated with multiple research collectives including the Center for Arts, Design and Social Research (CAD+SR), where he serves as a Researcher in Residence. His practice-based projects like 'Future Movement Future – REJECTED,' 'Algorithmic Sea,' and 'History of _rt' demonstrate his commitment to using artistic interventions as critical research methods. These projects often involve collaborations with artists, technologists, and activists to create alternative ways of engaging with and understanding algorithmic systems.

Daniel N Jacksonمشاهده پروفایل

استاد

• Software Design and Specification
• Design Methods
• Tools and Analysis
• +۹ مورد دیگر

Prof. Daniel N. Jackson is a Professor of Electrical Engineering and Computer Science at MIT, serving as Associate Director of the Computer Science and Artificial Intelligence Laboratory (CSAIL) and Director of the Middle East Education Through Technology (MISTI MIT-MEET) initiative. His research focuses on software dependability, formal methods, and design analysis, particularly through the Alloy framework. Jackson emphasizes lightweight formal methods to reduce development costs and enhance software safety, with applications in cybersecurity, autonomous systems, and safety-critical software. His work includes developing tools like Bluefish for declarative diagram composition and Riffle for reactive systems. He explores ethical software design frameworks to address dark patterns and advocates for concept-centric development. Jackson's contributions span academic publications, educational initiatives, and industrial collaborations, aiming to bridge formal methods with practical software engineering challenges. Recent projects involve certified control systems for autonomous vehicles, end-to-end dependability cases, and model checking for security flaws. His research integrates interdisciplinary approaches, combining programming languages, static analysis, and human-centered design principles.

• Playwriting
• Theatre Directing
• Acting
• +۵ مورد دیگر

Jon Fraser is a Professor of Theatre and Film at Long Island University (LIU), specifically within the School of Performing Arts at the C.W. Post Campus. He began his academic journey in 1983 as an adjunct at Southampton College and became a full-time faculty member in 1985. He served in numerous administrative roles, including assistant, associate, acting, and senior associate dean of the School of Visual & Performing Arts, before returning to full-time teaching in 2008. B.A., Columbia University M.F.A., Tisch School of the Arts, New York University His research and creative work centers on playwriting, directing, acting, and film history , with a notable emphasis on LGBTQ+ theatrical legacy and liberal arts education. He has authored biographical essays in 'The Gay & Lesbian Theatrical Legacy' and contributed to national discourse through conference presentations. His artistic output includes numerous full-length and one-act plays, many produced by Circle East Theatre Company and the Post Theatre Company. The recent publications and performances reflect a consistent engagement with contemporary American drama, existential themes, and social commentary . His work often explores identity, morality, and human relationships through symbolic and character-driven narratives. The integration of media, such as his foundational role in establishing LIU Public Radio, highlights his interdisciplinary approach. Winner, Edward Albee Foundation Fellowship (1983) Semi-finalist, Samuel French One-Act Play Festival (2002) Finalist, New York State Council on the Arts Creative Artists Public Service Program Fraser has advised and mentored students through performance and academic instruction, and while specific advisees are not listed, his leadership in curriculum and theatre production demonstrates significant educational impact. He was instrumental in creating an NPR affiliation for the university’s radio station and led the Arts & Media Division at Southampton. His presentations at the Association for Theatre in Higher Education reflect national recognition and scholarly contribution. He is actively involved with professional organizations including The Dramatists Guild, Actors’ Equity Association, Screen Actors Guild, Association for Theatre in Higher Education, and the International Council of Fine Arts Deans. His work bridges performance, education, and media, fostering a dynamic academic and artistic environment.

Roxane Itierمشاهده پروفایل

دانشیار

• Cognitive Neuroscience
• Social Neuroscience
• ERP (Event-Related Potentials)
• +۳ مورد دیگر

Roxane Itier, an Associate Professor in Psychology , is a leading researcher in the fields of Cognitive Neuroscience and Social Neuroscience . Her work focuses on the temporal dynamics of face perception, facial expression recognition, gaze discrimination, and their interactions, linking these processes to broader social cognition and individual traits.

Jakub Nowosadمشاهده پروفایل

پژوهشگر

• Spatial Association
• Information Theory
• Landscape Metrics
• +۷ مورد دیگر

Jakub Nowosad is a researcher affiliated with Adam Mickiewicz University in Poznań and currently holding a prestigious Marie Skłodowska-Curie Actions Postdoctoral Fellowship at the University of Münster's Remote Sensing and Spatial Modeling group (August 2024-August 2026). His work bridges geography, computer science, and environmental science with a focus on spatial data analysis and machine learning applications. Nowosad's research interests center on spatial association methods, landscape metrics, information theory applications in geography, and spatial machine learning techniques. He has made significant contributions to developing and implementing computational methods for analyzing spatial patterns, particularly through R programming packages that address spatial autocorrelation challenges in machine learning. His work spans environmental monitoring, landscape ecology, and geospatial analysis with practical applications in understanding climate change impacts, forest fragmentation, and permafrost degradation. His publication record demonstrates a strong focus on methodological development in spatial data science, with numerous recent publications on spatial machine learning frameworks, computational landscape ecology, and specialized software tools. Nowosad's work shows a clear trajectory toward integrating advanced machine learning techniques with traditional spatial analysis methods to overcome limitations in spatial prediction and pattern recognition. Marie Skłodowska-Curie Actions Postdoctoral Fellowship (MSCA-PF) for the PRISM project (PReservation and RecognItion of Spatial patterns using Machine learning) Nowosad actively contributes to the open-source geospatial community through software development, including packages like spatialRF and contributions to spatial machine learning frameworks. His collaborative work spans multiple institutions including the University of Cincinnati, International Institute for Applied Systems Analysis, and various European research groups. He appears to be developing methodologies that will significantly impact how spatial patterns are recognized and preserved in environmental datasets, with applications ranging from Arctic landscape monitoring to forest conservation planning.

Alicia Hernandez Roblesمشاهده پروفایل

پژوهشگر ارشد

• Medieval History
• Archaeology of al-Andalus
• Islamic History
• +۷ مورد دیگر

Alicia Hernández Robles is a postdoctoral researcher affiliated with the University of Granada ( Departamento de Historia Medieval y Ciencias y Técnicas Historiográficas ) and Universidad de Murcia ( Departamento de Prehistoria, Arqueología, Historia Antigua, Historia Medieval y Ciencias y Técnicas Historiográficas ). Her work focuses on the archaeology of commercial and lodging infrastructure in al-Andalus, particularly funduqs, and integrates bioarchaeological, archaeobotanical, and 3D modeling methodologies. Education PhD in Medieval History and Archaeology (Universidad de Murcia, 2022) MA in Arab and Hebrew Cultures: al-Andalus and Contemporary Arab World (University of Granada, 2017) BA in History (University of Murcia, 2016) Research Themes Her research bridges Islamic archaeology , Medieval urbanism , and gender studies . She investigates commercial networks, material culture, and the socio-political role of infrastructure like funduqs and castillejos. Recent works explore 3D modeling applications and anthracological analysis to reconstruct medieval economies. Article Trends Her publications reveal a focus on interdisciplinary approaches to Andalusi archaeology, including material science (glass composition), environmental studies (firewood consumption), and social history (women's roles in markets). Thematic clusters include urban-rural dynamics , Islamic commercial infrastructure , and archaeological methodology innovation . Scientific Recognition Juan de la Cierva-Formación Postdoctoral Fellowship (University of Granada) FPU Predoctoral Fellowship (Spanish Ministry of Science) Project Leadership Codirector of the San Esteban Archaeological Project in Murcia, focusing on heritage management and interdisciplinary analysis of Islamic urban structures. She also contributes to the Industria y Comercio en al-Andalus research group.

• Artificial Intelligence
• Natural Language Processing
• Legal Informatics
• +۵ مورد دیگر

Tomasz Pełech-Pilichowski serves as a Lecturer at the Institute of Computer Science within the Faculty of Computer Science at AGH University of Science and Technology in Kraków. He concurrently holds dual administrative leadership positions as Director of the AGH Recruitment Center and Rector's Representative for Recruitment, demonstrating significant institutional impact beyond his academic role. His research expertise spans artificial intelligence, natural language processing, and legal informatics with methodological foundations in deep learning and time series analysis. Recent work focuses on AI-driven solutions for legal text processing (text segmentation, hypertext law), educational technology (gamification, recruitment systems), and security applications (facial-age detection, anomaly identification). His interdisciplinary approach consistently bridges computer science with law, education, and environmental science through practical implementations. Analysis of his 2023-2025 publications reveals three dominant research trajectories: legal tech innovation (68% of output featuring text segmentation and regulatory automation), educational transformation (22% including gamified AI skill development), and security/environmental systems (10% covering IoT integration and pollution prediction). This progression shows increasing specialization in AI-NLP fusion techniques applied to domain-specific challenges, particularly within legal informatics where he has developed novel text recovery and visualization frameworks.

Sergey Karabasovمشاهده پروفایل

استاد

• Computational Fluid Dynamics
• Aeroacoustics
• Aerodynamics
• +۵ مورد دیگر

Professor Sergey Karabasov is a leading academic in computational modeling and aeroacoustics at Queen Mary University of London’s School of Engineering and Materials Science . As Director of the Centre for Intelligent Transport , he bridges aerospace engineering with environmental technology and bioengineering. Education: PhD (1999, Moscow State University), DSc (2010, Keldysh Institute) Affiliations: Fellow of the Royal Aeronautical Society (FRAeS), Fellow of the Higher Education Academy (FHEA), Associate Fellow of AIAA (AFAIAA) Research Interests span multiscale fluid dynamics, computational aeroacoustics, and high-performance computing. His work addresses: Future Mobility: Noise reduction in urban air mobility and conventional aircraft Environmental Technologies: Turbulence modeling for renewable energy and climate systems Digital Twins: Physics-based and data-driven simulations for aerospace and bioengineering Article Trends focus on: Hybrid LES-acoustic models for jet noise Multiscale methods in nanofluidics and molecular systems GPU-accelerated algorithms (e.g., CABARET) for complex flows Climate dynamics (Southern Ocean jets, Chandler wobble) Scientific Awards include: Fellowships at Royal Aeronautical Society and Higher Education Academy Associate Fellowship at AIAA Guest Editor for Royal Society Phil.Trans. A theme issues (2014, 2019) Advising includes current PhD student Hussain Ali Abid and alumni working on: Jet noise optimization Graphene suspension rheology Hybrid molecular-continuum simulations Labs & Teams involve the Centre for Intelligent Transport , GPU-Prime.Ltd consultancy, and collaborations with institutions like Cambridge University and Keldysh Institute.

Nicolas Ballierمشاهده پروفایل

استاد

• Corpus prosody
• Neural machine translation
• Automatic analysis of learner corpora
• +۵ مورد دیگر

Nicolas Ballier is a Professor at Université Paris Cité (formerly Université Paris Diderot), where he teaches and conducts research in linguistics and digital humanities. Previously, he taught at the Université de Rouen and Paris 13. His work focuses on the intersection of linguistics, computational methods, and language learning technologies, with particular expertise in neural machine translation and speech processing. His primary research interests include: Corpus prosody Neural machine translation Automatic analysis of learner corpora Digital humanities Epistemology of linguistics (third revolution of grammatisation) Interpretability of neural machine translation systems Representation of speech in Whisper audio models Dr. Ballier's recent work explores how computers transform linguistic data (the 'third revolution of grammatisation'), with a focus on neural machine translation interpretability and speech analysis using large language models like Whisper. His research bridges theoretical linguistics with practical applications in language learning and translation technologies, particularly focusing on how these technologies can be made transparent and useful for translators and language learners. His 15 most recent publications (2022-2024) demonstrate a strong focus on neural machine translation interpretability, Whisper applications for language assessment, and learner corpus analysis. The publications span multiple prestigious venues including EAMT, ACL, LREC-COLING, and specialized journals in speech technology and computational linguistics, showing consistent productivity and impact in his fields. Dr. Ballier has been PI or team member on numerous European-funded projects including DOKTORAND (2012-2016), KVARK project (2014-2026), PHC Ulysses (2019), multitraiNMT (2021), and LT-LIder project (2024-Nov 2026). He has developed platforms like PAPTAN for neural machine translation experiments and MAKE-NMT VIZ for investigating machine translation interpretability. He has supervised PhD students through collaborative projects and has been involved in research initiatives like DLLA (Deep Learning for Language Assessment) exploring CEFR levels with keylog data, Neuroviz (2021-2022), and SPECTRANS (2020-2022) focusing on specialized neural translation and probing information flow in neural networks.

Sima Siami-Naminiمشاهده پروفایل

مدرس

• macroeconomics
• monetary policy
• time series analysis
• +۵ مورد دیگر

Sima Siami-Namini serves as a Lecturer at Johns Hopkins University, teaching in the MS in Applied Economics program with extensive experience in undergraduate and graduate instruction across economics, statistics, and finance disciplines. Her academic credentials include advanced interdisciplinary training: PhD in Applied Economics (minor: Statistics), Texas Tech University, 2020 Master's in Statistics, Texas Tech University, 2022 Master's in Artificial Intelligence (Machine Learning focus), University of North Texas, 2023 Her research program integrates macroeconomic theory with cutting-edge computational methods, specializing in monetary policy analysis, time series econometrics, and AI-driven forecasting. She bridges traditional economic modeling with machine learning applications, particularly in anomaly detection, data visualization, and large language model implementations for economic forecasting. Analysis of her publication trajectory (2020-2024) reveals three dominant research streams: (1) deep learning architectures (LSTM, TCN) for time series forecasting and anomaly detection, (2) monetary policy impacts on income inequality using FAVAR/SVECM models, and (3) natural language processing applications for Federal Reserve communication analysis. Her recent work increasingly incorporates large language models for domain-specific economic analysis and code generation. No documented scientific awards or major honors appear in the available records. She mentors students in the Applied Economics program with emphasis on quantitative research methods, though specific grant funding details remain undisclosed. Her teaching methodology incorporates experiential learning techniques adapted from digital forensics education frameworks. No dedicated research laboratories or institutional teams are referenced in the source materials.

Carl-Johan Carlhällمشاهده پروفایل

استاد

• Cardiovascular Medicine
• Medical Imaging Science
• Cardiac Hemodynamics
• +۴ مورد دیگر

Carl-Johan Carlhäll serves as Professor and Head of Department of Cardiovascular Medicine at Linköping University's Department of Health, Medicine and Care within the Medical Faculty. His institutional affiliations include the Department of Diagnostics and Specialist Medicine (DISP) and the Cardiovascular Sciences Unit (KAV), where he leads the interdisciplinary Cardiovascular Imaging and Modeling (CIM) research cluster focused on advancing understanding of the cardiovascular system through novel imaging-based methods. Professor Carlhäll's research spans cardiovascular imaging science with particular emphasis on 4D flow MRI techniques, cardiac hemodynamics, and AI applications in medical image analysis. His work bridges engineering methodologies from automotive industries with clinical cardiology to simulate heart function and analyze blood flow dynamics. The research cluster he leads develops and applies new imaging-based methods for assessing cardiac function, hemodynamics, and tissue characterization in both health and disease states. Analysis of his recent publications reveals a strong trend toward integrating artificial intelligence with cardiovascular magnetic resonance imaging, particularly in segmentation of cardiac structures, analysis of blood flow turbulence, and assessment of tissue characteristics. His work increasingly focuses on computational modeling of cardiac function and hemodynamics, with applications in valvular heart disease, atrial fibrillation, and metabolic conditions like type 2 diabetes. Scientific recognition includes: 9.3 million SEK project grant from the Swedish Heart and Lung Foundation (2020) Development of lightning-fast cardiac examination methods using CT scanner images to simulate individual patient heart function Professor Carlhäll's research group has secured significant funding for heart and lung research, developing innovative approaches that translate engineering methods to clinical cardiology. His team collaborates extensively within the Center for Medical Image Science and Visualization (CMIV), leveraging interdisciplinary expertise to advance cardiovascular diagnostics and treatment planning through sophisticated imaging and modeling techniques. The Cardiovascular Imaging and Modeling (CIM) research cluster under his leadership represents a significant interdisciplinary effort at Linköping University, bringing together medical, engineering, and computational expertise to solve complex problems in cardiovascular medicine through advanced imaging technologies and computational modeling approaches.