جستجوی استاد راهنمای دانشگاهی

Dr. Michel Dumontier is a Distinguished Professor of Data Science at Maastricht University, where he serves as the founder and Director of the Institute of Data Science. He is internationally recognized as a co-founder of the FAIR (Findable, Accessible, Interoperable and Reusable) data principles, which have transformed scientific data management globally. His academic background includes: BSc in Biochemistry from the University of Manitoba (1999) PhD in Bioinformatics from the University of Toronto (2004) Assistant/Associate Professor at Carleton University (2005-2013) Associate Professor at Stanford University (2013-2016) Distinguished Professor at Maastricht University (2017-present) Dr. Dumontier's research focuses on unlocking data potential for scientific discovery, with expertise in knowledge graphs for drug discovery and personalized medicine. His work spans FAIR data principles, generative AI, machine learning, semantic technologies, ontology, and data integration. His recent publications reveal a strong trend toward applying generative AI to healthcare data, with increasing focus on synthetic health data generation, privacy-preserving techniques, and knowledge graph applications in drug repurposing. His work bridges computer science, biomedical informatics, and clinical applications across multiple medical domains. Dr. Dumontier has secured significant research funding as a principal investigator: NWO (Dutch Research Council) Horizon Europe MCSA NIH/NCATS ARPA-H He coordinates the AIDAVA and REALM projects, leads the NCATS Biomedical Data Translator, and directs the GENIUS AI lab. As editor-in-chief of the journal Data Science, he shapes discourse in the field. Dr. Dumontier maintains active industry connections through: Minderheidsaandeelhouder at Data2Discovery Inc Scientific advisor and minority shareholder at OntoForce NV Scientific advisor, board member, and minority shareholder at Comunicare Editor-in-chief of Data Science Journal at Sage Publishing

• FAIR data
• generative artificial intelligence
• machine learning
• +۹ مورد دیگر

Srirang Manohar is a Full Professor at the TechMed Centre , University of Twente, specializing in Multi-Modality Medical Imaging . His work focuses on photoacoustic imaging, ultrasound, and tomography, with clinical applications in breast cancer, prostate cancer, and thyroid disorders.

• Photoacoustic Imaging
• Ultrasound
• Tomography
• +۳ مورد دیگر

Ivo Schoots is a Researcher at Erasmus MC in the Radiology & Nuclear Medicine department. His work focuses on prostate cancer , magnetic resonance imaging (MRI) , and artificial intelligence applications in medical imaging . Recent research trends include: AI-driven MRI reconstruction for cancer screening Comparative analysis of AI vs manual prostate cancer detection Radiomics for Gleason score differentiation Standardization of PI-RADS protocols Meta-analytic approaches to biopsy techniques

• Prostate Cancer
• Magnetic Resonance Imaging
• Artificial Intelligence in Medical Imaging
• +۵ مورد دیگر

Renee Hoekzema is an Assistant Professor in the Department of Mathematics within the Faculty of Science at Vrije Universiteit Amsterdam (VU Amsterdam). Her research spans multiple disciplines including mathematics, biology, and cognitive science, with a particular focus on topological structures and their applications across scientific domains. Dr. Hoekzema's research interests encompass a diverse range of mathematical and interdisciplinary topics: Algebraic Topology and Manifold Theory Geometric Analysis and Spectral Methods K-Theory and Cobordism Invariants Mathematical Biology and Developmental Patterns Mathematical Cognition and Spatial Reasoning Feature Selection and Unsupervised Learning Methods Her recent publications demonstrate a strong interdisciplinary approach, bridging pure mathematics with applications in biology, medical imaging, and cognitive science. Dr. Hoekzema frequently applies topological and geometric methods to problems in developmental biology and mathematical cognition, showing how abstract mathematical structures can illuminate concrete scientific questions. Her work on manifolds with odd Euler characteristic represents significant contributions to geometric topology, while her research on visuo-spatial thinking explores the cognitive foundations of mathematical expertise across multiple dimensions of analysis. Dr. Hoekzema serves as Principal Investigator for the research project "Shapes inside shapes in mathematics, physics, and biology" (2022-2025), which has generated substantial academic and public engagement across multiple platforms including news outlets, social media, and Wikipedia. She also teaches "Elements of Geometry" and maintains an active research profile with publications spanning mathematical topology, biological applications, and cognitive aspects of mathematical thinking, demonstrating her commitment to both theoretical advancement and practical scientific applications.

• Algebraic Topology
• Manifold Theory
• Mathematical Biology
• +۶ مورد دیگر

Mitko Veta is an Associate Professor in the Department of Biomedical Engineering at Eindhoven University of Technology (TU/e), specializing in medical image analysis. His research focuses on developing deep learning methods for histopathology image analysis to enhance diagnostic accuracy and reduce pathologist workload. He leads the Medical Image Analysis group, contributing to automated quantitative tools for pathology reporting and treatment planning. Academic Background: Veta earned his M.Sc. in Electrical Engineering from Ss. Cyril and Methodius University (Macedonia, 2009), followed by a Ph.D. in histopathology image analysis at University Medical Center Utrecht (2014). He joined TU/e as a postdoc in 2014 and became an assistant professor in 2016, advancing to his current role in 2021. Research Interests: His work spans histopathology image analysis, deep learning, domain adaptation, and applications in oncology (e.g., breast cancer, melanoma). He develops algorithms for mitosis detection, tumor-infiltrating lymphocyte assessment, and AI-driven clinical decision support. Key contributions include the MIDOG++ dataset and the LYSTO benchmark. Projects: He co-leads the Spectralligence AI project (2021–2024), focusing on AI-driven medical imaging solutions. His research addresses clinical challenges like myocardial scar quantification and checkpoint inhibitor treatment outcomes. Teaching: Veta teaches courses such as Machine Learning in Medical Imaging and Biology and AI for Medical Image Analysis , emphasizing practical applications of AI in healthcare.

• Medical Image Analysis
• Deep Learning
• Histopathology
• +۳ مورد دیگر

Fons van der Sommen is an Associate Professor in Electrical Engineering at Eindhoven University of Technology, specializing in Video Coding & Architectures. He leads research on computer-aided detection systems for early cancer diagnosis, particularly focusing on esophageal and colorectal neoplasia through advanced AI and computer vision techniques. His research interests span medical image analysis, AI-assisted diagnostics, and developing robust systems for clinical deployment. Recent publications focus on overcoming real-world implementation challenges of AI in endoscopy and enhancing the trustworthiness of diagnostic systems. Recent research trends show strong emphasis on surgical AI applications (robot-assisted procedures), generative models for medical data augmentation, and quality assurance frameworks for clinical AI deployment. His work integrates deep learning with clinical validation across gastrointestinal and pulmonary oncology. TU/e Best PhD Thesis Award (2018) Best Poster Presentation (2017, 2013) He coordinates multiple research projects including TASTI-XECS221002 (Advanced AR for AI-based Servitization) and XL-ARGOS (extended reality solutions). Manages collaborations with medical centers on AI implementation for cancer screening.

• Medical Image Analysis
• Computer-Aided Diagnosis
• Artificial Intelligence
• +۲ مورد دیگر

Prof. dr. Barbara van Leeuwen is a full professor at the University of Groningen's Faculty of Medical Sciences, where she leads research in surgical oncology and geriatric care. Her work focuses on optimizing outcomes for elderly cancer patients through innovative surgical approaches and patient-centered care models. Her research spans: Oncologic surgery outcomes and risk stratification Geriatric oncology and frailty assessment Shared decision-making in cancer treatment Arts in health interventions (music therapy) Health economics in surgical oncology Recent publications demonstrate strong focus on melanoma management, sarcoma diagnostics, and perioperative care optimization, with emerging work on non-pharmacological interventions like music therapy for surgical patients. Scientific Recognition: National representative for the International Society of Geriatric Oncology (SIOG) since 2020 She leads two research groups: 'Innovative Clinical Studies and Long-term Treatment Consequences in Cancer' (InClinS) and 'Cure and Care in the Community Context' (FOUR-C), supervising multiple research projects on surgical outcomes and patient-centered care.

• Oncology
• Geriatric Surgery
• Surgical Outcomes
• +۵ مورد دیگر

Prof. Riemer Slart is a Professor in Molecular Imaging at the University of Groningen's Faculty of Medical Sciences. He holds positions at the Cardiovascular Centre (CVC), Translational Immunology Groningen (TRIGR), and the Basic and Translational Research and Imaging Methodology Development in Groningen (BRIDGE). His work contributes to UN Sustainable Development Goals related to health and well-being. Education: Principal Investigator at Groningen University Institute for Drug Exploration (GUIDE) since 2012. External roles include Committee member of EULAR's Vasculitis working group and EANM's Cardiovascular working group. Research interests focus on molecular imaging techniques like PET/CT, particularly in cardiovascular and inflammatory diseases. Recent work includes FDG-PET/CT applications in critical illness, polymyalgia rheumatica, and giant cell arteritis. He has supervised 23 research projects and contributed to over 577 publications. Awards include the Zaret-Beller Elite Reviewer Award (2024) and the Frans J Th Wackers Award (2020). He actively collaborates internationally, organizing academic events and consulting on nuclear imaging advancements.

• Molecular Imaging
• Nuclear Medicine
• Cardiovascular Diseases
• +۳ مورد دیگر

Luis Juarez Orozco is a researcher specializing in nuclear cardiology, cardiovascular imaging, and artificial intelligence applications in medical diagnostics. His work bridges machine learning with cardiac PET/CT imaging and hybrid cardiovascular imaging techniques, contributing to survival analysis and disease characterization. Active in Positron Emission Tomography , Myocardial Infarction , and Vasculome research Collaborates across institutions like University of Turku and University Medical Center Groningen He explores modern AI implementations for analyzing cardiac function, geometric indexes, and perfusion data, while maintaining affiliations with academic institutions focused on cardiovascular research. His recent outputs highlight trends in machine learning for clinical decision-making and image processing.

• Positron Emission Tomography
• Cardiovascular Disease
• Machine Learning
• +۶ مورد دیگر

Dana Pisica is an active Researcher in the Neurosurgery department at Erasmus Medical Center, with significant contributions to traumatic brain injury research. Her work focuses on neurotrauma classification systems, intracranial pressure monitoring, and mental health outcomes following brain injuries through large-scale collaborative studies including CENTER-TBI and TRACK-TBI. Her research interests span the critical domains of traumatic brain injury, neurotrauma, nervous system injury, cohort analysis, intracranial pressure management, and intensive care unit protocols. These areas reflect her focus on both the immediate neurological consequences and long-term psychiatric outcomes of brain trauma. Analysis of her recent publication trends reveals a strong emphasis on developing standardized classification systems for traumatic brain injury, creating predictive models for intracranial hypertension using advanced radiomic techniques, and investigating the complex relationship between brain trauma and subsequent mental health conditions including depression and PTSD. Her work bridges clinical neuroscience with data science methodologies. Dana Pisica actively participates in major international research consortia including CENTER-TBI and TRACK-TBI, contributing to large-scale collaborative efforts that involve multiple institutions across different countries. Her research has garnered significant attention with publications being picked up by 18 news outlets and shared across various social media platforms.

• Traumatic Brain Injury
• Neurotrauma
• Nervous System Injury
• +۵ مورد دیگر

Baoqiang Ma is a researcher at the University of Groningen specializing in medical imaging and artificial intelligence for cancer prognosis. His work focuses on oropharyngeal cancer, utilizing multimodal imaging techniques like PET-CT and MRI for tumor segmentation and outcome prediction in radiotherapy contexts. Education: PhD in Medical Imaging, University of Groningen (2025) Research Interests: Ma develops deep learning frameworks for precision oncology, with expertise in nnU-Net architectures, radiomics, and prognostic modeling. His research bridges medical physics and AI to improve diagnostic accuracy in head and neck cancers, directly contributing to UN Sustainable Development Goals in healthcare innovation. Publication Trends: His 2025 publications reveal a concentrated focus on AI-enhanced medical imaging, featuring hippocampal subfield segmentation datasets, nnU-Net tumor segmentation ensembles, and deep learning models for lymph node analysis. These works emphasize clinical translation of AI tools for radiotherapy planning and survival prediction in oropharyngeal cancer. Academic Activities: Presenter at ESTRO 2023 (European Society for Radiotherapy & Oncology) DLinRT conference speaker (January 2024) Advising and Grants: No documented student supervision or grant funding details available in current records.

• Medical Imaging
• Oncology
• Artificial Intelligence
• +۳ مورد دیگر

Roy Dwarkasing is a researcher at Erasmus MC's Department of Radiology & Nuclear Medicine, specializing in magnetic resonance imaging (MRI) applications for oncology and gastrointestinal diseases. His work spans hepatocellular carcinoma surveillance, fistula treatment optimization, and clinical decision-making frameworks. Active in Medical Imaging (MRI, PET-MRI) and Oncology (HCC, cholangiocarcinoma, esophageal cancer) Key collaborations in Gastroenterology and Surgical Outcomes Research Trends His recent publications focus on MRI's role in cancer surveillance, including Current Problems in Diagnostic Radiology (2024) and The Lancet Oncology (2025). Collaborative studies with institutions like Erasmus MC address fistula repair techniques (Bioengineering, 2025) and diagnostic classification systems (Abdominal Radiology, 2024).

• Magnetic Resonance Imaging
• Hepatocellular Carcinoma
• Radiomics
• +۵ مورد دیگر

Sunil Choenni is a Lecturer in Future Information & Communication Technology at the Rotterdam University of Applied Sciences and an active researcher within the Creating010 Knowledge Center . He leads and participates in the Data Driven Society project, where his work centers on algorithmic transparency, big-data analytics, large language models, and privacy & security engineering. Research Interests: Algorithmic transparency and explainable AI Big-data analytics for smart government and justice systems Privacy engineering and data minimization technologies Security architectures, including Zero-Trust models Open and semi-open data governance Ethical implications of AI and machine learning in society Across nearly 50 refereed contributions since 2013, Choenni’s publications reveal a sustained focus on leveraging data science to enhance public-sector decision-making while rigorously safeguarding individual privacy and fairness. His 2024 pre-print on explainable ML using concept activation vectors, together with articles on Zero-Trust smart-shipping architectures and privacy-minimization in public organizations, exemplify his forward-looking research agenda. Scientific Awards & Recognition: No specific awards or fellowships are listed in the provided materials. Advising & Grants: While the text does not enumerate PhD or Master’s advisees, Choenni actively mentors students and practitioners through Rotterdam University’s internship and graduation-research programs. External grant details are not supplied. Labs & Teams: Choenni is embedded in the Creating010 Knowledge Center , an interdisciplinary research environment that integrates ICT, media, and behavioural sciences to foster innovation in the digital society.

• Algorithm transparency
• Big data analytics
• Large Language Models (LLM)
• +۶ مورد دیگر

Kim Sanders is a Researcher in the Department of General Practice at Erasmus MC, Erasmus University Rotterdam, specializing in interdisciplinary health research bridging intellectual disability care and oncology. Her primary research focuses on intellectual disabilities in aging populations , particularly dysphagia epidemiology in older adults with intellectual impairments, and radiomics applications in oncology for predicting skeletal muscle responses to lung cancer chemotherapy. These domains reflect strong collaboration across nursing, medical specialties, and health professions as evidenced by her fingerprint topics including Prevalence, Odds Ratio, and Skeletal Muscle. Recent publications demonstrate dual-track impact: the 2024 study advances geriatric care for intellectually disabled populations through dysphagia prevalence analysis, while the highly cited 2019 radiomics research pioneers predictive modeling in stage IV lung cancer treatment, showcasing methodological innovation in medical imaging and cancer therapeutics.

• Intellectual Disabilities
• Dysphagia
• Radiomics
• +۴ مورد دیگر

Marc H.W.A. Wijnen serves as a Full Professor at Erasmus University Rotterdam within the Cancer strategic program, focusing on translational research to improve outcomes for pediatric cancer patients. His work bridges clinical oncology with advanced technological applications. Research interests center on high-impact pediatric malignancies including neuroblastoma and Wilms tumor, with emphasis on molecular diagnostics, precision radiotherapy, and surgical innovation. Current investigations explore drug sensitivity testing in tumor organoids, AI-driven imaging for surgical guidance, and risk-adapted treatment protocols for relapsed disease. Recent 2025 publications reveal a pronounced shift toward integrating computational methods with molecular profiling—evident in deep learning applications for surgical oncology and genomic analysis of neuroblastoma risk stratification—signaling a strategic move toward data-driven personalized therapy frameworks. Scientific recognition: No awards explicitly documented in source materials Academic mentorship and funding details remain unspecified, though extensive multinational collaborations (evident across 15+ co-authored studies) suggest leadership in large consortia addressing pediatric oncology challenges. Key partnerships include Princess Máxima Center and European neuroblastoma research networks. Operates within Erasmus MC Cancer Institute’s strategic framework, contributing to high-precision surgery and image-guided therapy initiatives through multidisciplinary teams spanning radiology, molecular biology, and clinical oncology.

• Pediatric Oncology
• Cancer Research
• Neuroblastoma
• +۳ مورد دیگر