جستجوی استاد راهنمای دانشگاهی

Abduzhappar Gaipovمشاهده پروفایل

دانشیار

• Nephrology
• Dialysis
• Kidney Transplantation
• +۷ مورد دیگر

Abduzhappar Gaipov, MD, PhD , is a board-certified nephrologist and Associate Professor at Nazarbayev University School of Medicine . He holds a PhD in Clinical Science (Internal Medicine) from the National Scientific Medical Center (Kazakhstan) and has completed postdoctoral research at the University of Tennessee Health Science Center (USA). His career spans leadership roles, including Department Chair at the National Scientific Medical Research Center (2012–2018) and collaborations with institutions in Turkey, USA, and Kazakhstan. Education : MD (Akhmet Yassawi University, 2004); PhD in Clinical Science (Internal Medicine, National Scientific Medical Center, 2008). Dr. Gaipov’s research focuses on chronic kidney disease , dialysis , renal regeneration , and big data epidemiology . His work integrates urinary proteomics , extracorporeal blood purification , and AI-driven healthcare analytics . Recent projects include forecasting cancer trends in Kazakhstan and identifying biomarkers for diabetic kidney disease via mass spectrometry. He has published over 90 peer-reviewed papers and leads multi-center studies on cardiovascular-kidney-metabolic syndrome. His peer-reviewed work spans machine learning in critical care , renal replacement therapies , and epidemiology of non-communicable diseases . As chair of the ISN NIS&Russia region board (2020–2022), he advocates for nephrology advancements in Central Asia. Dr. Gaipov serves as an editor/reviewer for journals like Theranostics and Clinical Medicine Insights , and supervises graduate researchers in nephrology and data science.

Tim Friedeمشاهده پروفایل

استاد

• Clinical Biostatistics
• Adaptive Designs for Clinical Trials
• Systematic Reviews/Meta-Analyses
• +۳ مورد دیگر

Tim Friede is a Professor of Biostatistics and Director of the Department of Medical Statistics at the University Medical Center Göttingen. He holds a Master’s in Mathematics from the University of Karlsruhe (1998) and a Dr.sc.hum. (PhD) in Medical Statistics from Heidelberg University (2001). His career includes roles at Lancaster University (2001–2004), Novartis Pharma AG (2004–2006), and the University of Warwick (2006–2010) before joining Göttingen in 2010. Friede specializes in clinical biostatistics, focusing on adaptive trial designs, meta-analyses, and applications in rare diseases and cardiovascular medicine. He leads the FAIR-HF2-DZHK05 trial on iron deficiency in heart failure and co-developed the SAVVY methodology for adverse event analysis. His work spans over 200 peer-reviewed publications and includes awards such as the Paul-Martini-Preis (2012) and Susanne-Dahms-Medaille (2024). He chairs editorial boards for Statistics in Medicine , ESC Heart Failure , and Biometrical Journal , and holds leadership roles in global organizations like the International Society for Clinical Biostatistics and Deutsche Region der Internationalen Biometrischen Gesellschaft. Education highlights include postdoc/lecturer positions in Lancaster and his NHS Training Fellowship in Medical Statistics. He advises multiple clinical trials, including the RESHAPE-HF2 mitral valve trial and the METAPANC pancreatic cancer study. His research integrates statistical innovation with clinical impact, emphasizing methodological rigor and practical applicability.

• Pediatric Hematology
• Oncology
• Neuro-oncology
• +۴ مورد دیگر

Prof. Dr. Michael Bockmayr is a Professor of Pediatrics and Youth Medicine at the Hamburg University Medical Center (Universitätsklinikum Eppendorf), affiliated with the Department of Pediatric Hematology and Oncology within the Faculty of Medicine. He holds a Medical Specialist certification in Pediatric Hematology and Oncology. His work focuses on molecular and computational approaches to neuro-oncology, including tumor classification using advanced genomic and proteomic techniques. Research interests span pediatric and adult brain tumors, with emphasis on ependymoma subtyping, medulloblastoma molecular profiling, and AI-driven pathology diagnostics. Key contributions include DNA methylation-based tumor classification systems and integrative analyses of cancer immune microenvironments. His team employs machine learning to improve diagnostic accuracy and predict treatment responses in cancers like gliomas and head/neck tumors. Recent studies highlight work on nanopore sequencing applications, CSF-based liquid biopsies, and explainable AI models for histopathological analysis. He collaborates with interdisciplinary teams across Europe in initiatives like the European Liquid Biopsy Society (ELBS), advancing translational research in oncology and hematology. Professional roles include leadership in clinical trials and multidisciplinary tumor boards. He actively participates in the German HIT-MED consortium for pediatric brain tumor research. His lab is part of the Center for Molecular Neurobiology Hamburg (ZMNH), emphasizing systems biology approaches in pediatric oncology.

Linda Baumbachمشاهده پروفایل

پژوهشگر ارشد

• Health Economics
• Musculoskeletal Disorders
• Public Health
• +۳ مورد دیگر

Linda Baumbach is a Research Fellow at the Universitätsklinikum Hamburg-Eppendorf (UKE), affiliated with the Institute of Health Economics and Health Care Research within the Faculty of Medicine. Her work focuses on health economics, musculoskeletal disorders, and the application of federated machine learning in biomedical research while addressing data privacy challenges. Her research interests include evaluating the cost-effectiveness of physiotherapy treatments, analyzing patient outcomes in osteoarthritis management, and exploring the role of technology like large language models in systematic reviews. She also investigates social determinants of health, such as migration background and physical activity's impact on loneliness. Baumbach has contributed to studies on personalized pain prognosis using predictive models and federated learning approaches to preserve data privacy. Her work often integrates interdisciplinary methods, combining clinical data with advanced computational techniques. She has published extensively on topics ranging from musculoskeletal care optimization to the ethical implications of genomic research. Her research spans clinical and methodological domains, emphasizing practical solutions for healthcare challenges while maintaining rigorous scientific standards. Collaborations with international teams highlight her commitment to advancing translational research in health economics and biomedical informatics.

Alexander Roeschمشاهده پروفایل

استاد

• Oncology
• Cancer Biology
• Melanoma Research
• +۶ مورد دیگر

Prof. Dr. Alexander Roesch is a Professor at the University of Duisburg-Essen's Medical Faculty, leading the Tumor Heterogeneity & Plasticity Group within the Clinic for Dermatology . His research focuses on melanoma biology, therapy resistance mechanisms, and liquid biopsy technologies. He coordinates the Clinical Research Unit CRU/KFO 337 (PhenoTImE) and participates in the EU Horizon 2020 MELGEN training program. Education: No explicit details provided; inferred expertise from publications and clinical roles. Research interests include tumor cell state plasticity, epigenetic regulation (e.g., KDM5B), and non-invasive liquid biopsy platforms for real-time monitoring. His work bridges basic science and clinical translation, with contributions to understanding therapy resistance via phenotypic switching and metabolic reprogramming. Key projects involve multiplexed imaging (CODEX™), mass spectrometry, and CRISPR-based approaches. Publications highlight advancements in melanoma therapy optimization, biomarker discovery (e.g., ctDNA), and immunotherapy efficacy prediction. Recent work emphasizes IL-17's role in checkpoint inhibitor response and spatial proteomics in tumor immunity. Grants/Awards: DFG-funded CRU/KFO 337 extension (€4M), EU Horizon 2020 MELGEN funding. Labs/Teams: Tumor Heterogeneity & Plasticity Group, collaboration with European Liquid Biopsy Society (ELBS) .

• Medical Biometry
• Epidemiology
• Clinical Research
• +۴ مورد دیگر

Eik Vettorazzi is a Research Fellow at the University Medical Center Hamburg-Eppendorf (UKE), affiliated with the Institute of Medical Biometry and Epidemiology within the Faculty of Medicine. His work focuses on medical biometry, epidemiology, and clinical research. Key areas include statistical methodology, health outcomes analysis, and translational research in oncology, cardiology, and neurology. He holds a Diplom in Mathematics (Dipl.-Math. oec.) and has extensive experience in designing and analyzing clinical trials, observational studies, and biomarker research. His expertise includes biostatistical methods, health economics, and interdisciplinary collaborations across multiple medical disciplines. Research interests emphasize improving diagnostic and prognostic tools through advanced statistical techniques and AI integration. He has contributed to studies on heart failure management (TIM-HF2 trial), multiple sclerosis decision coaching (DECIMS trial), and cancer survivorship programs (CARE for CAYA). Publications span topics like telemedicine efficacy, immune cell profiling in urothelial cancer, and biomechanical analyses of musculoskeletal disorders. Collaborations include the German Atrial Fibrillation Network (AFNET), European Liquid Biopsy Society (ELBS), and interdisciplinary teams addressing clinical and translational challenges.

Bernhard Meyerمشاهده پروفایل

استاد

• Vascular Neurosurgery
• Oncological Neurosurgery
• Spinal Neurosurgery
• +۳ مورد دیگر

Prof. Bernhard Meyer is a Professor of Neurosurgery at the Technische Universität München (TUM), leading the Chair of Neurosurgery since 2006. His research focuses on vascular, oncological, and spinal neurosurgery, with notable contributions to stereotactic radiotherapy for brain metastases and spinal tumor management. Meyer studied medicine at the Universities of Padua and Erlangen-Nürnberg, with international training at institutions like the Northwestern University in Chicago and completed his habilitation in neurosurgery at the University of Bonn. Professional roles include former President of the Deutsche Gesellschaft für Wirbelsäulenchirurgie (2019) and leadership in EuroSpine and the European Association of Neurosurgical Societies. His work emphasizes translational research, surgical innovation, and clinical outcomes in neuro-oncology and spinal disorders. Key publications address tumor control strategies, surgical techniques for spinal pathologies, and the impact of biotic factors on neurological conditions. Education: MD: Universities of Padua (Italy) and Erlangen-Nürnberg (Germany) PhD: Institute of Human Genetics, University of Erlangen-Nürnberg (1989) Neurosurgical Training: Tübingen, Duisburg, Bonn, with international stints in Zurich and Phoenix, AZ Meyer’s research integrates clinical practice with cutting-edge technologies, such as radiomics and robotic-assisted surgery. His studies on postoperative outcomes, such as in cerebellar infarction and spinal infections, highlight his commitment to improving patient care through evidence-based practices.

• Radiation Oncology
• High Precision Radiation Therapy
• Radiobiology
• +۹ مورد دیگر

Stephanie E. Combs is a renowned Professor and Chair of the Department of Radiation Oncology at the Faculty of Medicine, Technical University of Munich (TUM) , Germany, and serves as the Director of the Institute of Radiation Medicine (IRM) at Helmholtz Munich. She holds leadership roles including Dean of TUM's Faculty of Medicine (since 2022) and Chair of the Senate at TUM (since 2019). Studied medicine at the University of Heidelberg, Germany, with international training at Eastern Virginia Medical School and the University of Texas (UTHSCSA). Obtained board certification in radiation oncology (2009) and completed her Habilitation at Heidelberg, Germany. Her research spans high-precision radiation therapies (e.g., stereotactic radiosurgery, proton therapy), radiobiology , and combination therapies (radioimmunotherapy, radiochemotherapy). She focuses on optimizing treatment for brain tumors , gastrointestinal cancers , and pediatric oncology , while pioneering biomarker development and advanced imaging techniques (e.g., PSMA-PET, delta-radiomics). Recent publications highlight her work on radiomics for sarcoma response prediction , machine learning in glioblastoma targeting , and integrating immunotherapy with radiation . She also designed the Master of Radiation Biology program (2015) to bridge clinical and preclinical disciplines. 2019: Basic/Translational Senior Science Award, American Society of Radiation Oncology 2012: Robert Janker Award for Palliative Care 2010: Herrmann Holthusen Award, German Society for Radiation Oncology (DEGRO) 2010: Behnken-Berger Prize Prof. Combs leads interdisciplinary teams across institutions, fostering collaborations between the IRM, TUM's University Hospital 'rechts der Isar', and national/EU research networks like the German Cancer Consortium (DKTK).

• Radiation Oncology
• MRI-guided Radiotherapy
• Adaptive Radiation Therapy
• +۸ مورد دیگر

Claus Belka is a Professor in the Department of Radiation Oncology at the Faculty of Medicine, Ludwig-Maximilians-Universität München. His work focuses on advancing MRI-guided radiotherapy, adaptive treatment strategies, and the integration of artificial intelligence in radiation oncology. Research Interests: His research spans radiation oncology, deep learning applications in medical imaging, MRI-guided and adaptive radiotherapy, proton therapy, and dosimetric optimization. He investigates real-time tumor tracking, auto-segmentation, motion prediction, and radiomics for prognostic modeling in cancers of the lung, head and neck, prostate, and liver. The recent publications reflect a strong trend toward leveraging deep learning for segmentation, motion prediction, synthetic imaging, and outcome modeling in MRI- and PET-guided radiotherapy. Key themes include uncertainty calibration, patient-specific modeling, low-field MR-Linac applications, and dose accumulation in adaptive settings. Scientific Awards: Advising and Grants: While specific students and funding sources are not listed in the provided text, his extensive publication record across multi-institutional and technical-clinical domains suggests active mentorship and leadership in major research initiatives, including clinical trials like the PUMA trial for pulmonary MR-guided radiotherapy. Labs and Teams: He is associated with a leading radiation oncology research group at LMU Munich, focusing on medical physics innovation, AI integration, and clinical translation of advanced radiotherapy techniques.

• Translational Oncology
• Radiation Biology
• Head and Neck Cancer
• +۵ مورد دیگر

Horst Zitzelsberger is Head of the Research Unit Translational Metabolic Oncology at Helmholtz Zentrum München and an Associate Professor at the Medical Faculty of Ludwig Maximilian University (LMU) Munich. He earned his diploma in human genetics and doctorate in biology. His research focuses on translational radiation oncology with specialization in head and neck cancer, molecular mechanisms of radiation-induced carcinogenesis, multi-omics approaches, and personalized cancer treatment. Key interests include: Molecular cytogenetics and tumor heterogeneity Development of prognostic markers for therapeutic stratification Tumor metabolic processes and immune escape mechanisms Translational bioinformatics for precision oncology Recent publications (2017-2022) demonstrate strong emphasis on head and neck cancer biomarkers, miRNA signatures, transcriptomic classification, and therapy resistance mechanisms. Research consistently integrates multi-omics data with clinical outcomes to develop predictive models and therapeutic targets. He leads a translational research team comprising two laboratory groups: Translational Bioinformatics (Dr. Martin Selmansberger) Experimental Translational Oncology (Dr. Julia Hess) and maintains clinical collaborations with LMU University Clinics and national/international partners. The unit focuses on molecular characterization of therapy-resistant tumors and development of precision treatment strategies.

Jan Baumbachمشاهده پروفایل

استاد

• Computational Systems Biology
• Bioinformatics
• Network Medicine
• +۵ مورد دیگر

Prof. Jan Baumbach is a Professor and Director of the CoSy.Bio Institute at the University of Hamburg (since 2021), holding a part-time position as head of the Computational BioMedicine group at the University of Southern Denmark (since 2012). He leads the Computational Systems Biology department within the Faculty of Mathematics, Informatics and Natural Sciences. His academic journey includes roles as Chair of Experimental Bioinformatics at TU Munich, Junior Research Group Leader at the Max Planck Institute for Informatics, and postdoctoral research at UC Berkeley. He holds a doctoral degree from Bielefeld University, where he specialized in genome informatics and systems biology. His research focuses on computational systems biology, network medicine, and AI-driven biomedical applications. Key areas include drug repurposing via network-based analysis, federated learning for privacy-preserving multi-institutional studies, and bioinformatics tools like NeDRex and Drugst.One. Notable contributions include methodologies for differential co-expression analysis (DRaCOon), disease module identification (DysRegNet), and proteomic data harmonization (ProHarMeD). Prof. Baumbach’s work bridges algorithm development and clinical translation, addressing challenges in personalized medicine, metabolic disorders, and regenerative biology. His team actively develops open-source platforms to democratize access to advanced computational tools in biomedicine. His publications span 2025–2023, with a focus on genomic/proteomic analysis, federated learning applications, and AI-driven insights into disease mechanisms. Collaborative projects include multi-omics studies of multiple sclerosis, diabetic bone healing, and antiviral strategies against influenza. Labs/Teams: CoSy.Bio Institute (Hamburg), Computational BioMedicine Group (SDU), and collaborations with institutions like ZBH (Center for Bioinformatics Hamburg).

Olga Zolotarevaمشاهده پروفایل

پژوهشگر

• Computational Systems Biology
• Bioinformatics
• Federated Machine Learning
• +۵ مورد دیگر

Dr. Olga Zolotareva is a Group Leader at the University of Hamburg's Faculty of Mathematics, Informatics and Natural Sciences, within the Department of Computational Systems Biology. She holds a postdoctoral position at TU Munich's Chair of Experimental Bioinformatics, focusing on federated machine learning and proteomics analysis in Alzheimer's disease. Her research integrates multi-omics data, drug repurposing strategies, and privacy-preserving computational methods across institutions. Education and Training: She is completing her PhD at Bielefeld University's DiDy Research Training Group under Professors Ralf Hofestaedt and Martin Ester (Simon Fraser University, Canada). Her doctoral work developed a network-constrained biclustering method applied to breast cancer expression data. In 2018, she conducted visiting research at Simon Fraser University, contributing to multi-omics integration for drug response prediction. Research Interests: Her work bridges computational biology and federated learning, emphasizing privacy-aware tools for collaborative biomedical research. Key areas include: Federated learning frameworks for omics data analysis Drug repurposing via heterogeneous molecular networks Unsupervised patient stratification using biclustering Privacy-preserving differential expression analysis Publications Highlight Trends: Recent work emphasizes federated learning applications (e.g., FedRBE, FedProt), drug discovery tools (NeDRex-Web, ProHarMeD), and precision medicine strategies. Her articles span proteomics normalization, oncology biomarkers, and AI-driven biomedical collaboration. Grants and Collaborations: She contributes to projects like CLINSPECT-M and FeatureCloud, advancing decentralized healthcare analytics. Her tools like Flimma and DESMOND 2.0 exemplify methodological innovations in distributed biomedical research. Labs and Teams: Part of the Experimental Bioinformatics group at TU Munich and the Computational Systems Biology unit at Hamburg, she collaborates internationally on federated learning and omics integration initiatives.

Peter Schüfflerمشاهده پروفایل

استاد

• Digital Pathology
• Computational Pathology
• Machine Learning
• +۵ مورد دیگر

Prof. Peter Schüffler is a Professor of Computational Pathology at the Technical University of Munich (TUM), holding joint appointments in the TUM School of Medicine and Health and the TUM School of Computation, Information and Technology. His research focuses on applying machine learning to digital pathology, including cancer detection, prognostic marker identification, and AI-driven diagnostic tools. He earned an MSc in Bioinformatics from Saarland University and a PhD in Machine Learning for Medical Image Analysis from ETH Zurich. As a postdoc and senior ML scientist at Memorial Sloan Kettering Cancer Center, he co-founded Paige, a digital pathology company. He joined TUM in 2021. Education: MSc in Bioinformatics and Computational Biology, Saarland University and Max Planck Institute (MPI Saarbrücken) PhD in Machine Learning for Medical Image Analysis, ETH Zurich (2015) Research Interests: His work spans machine learning applications in pathology, including AI-driven diagnosis, automated quality assurance, and ergonomic systems for pathologists. Key areas include: Cancer detection and segmentation in pathology images Prognostic marker discovery for treatment success Efficient visualization of digital histopathology slides Integration of AI into clinical and educational workflows Awards: Best Paper Award (2014): Computer Aided Crohn's Disease Severity Assessment in MRI Outstanding Paper Award (2013): Crohn's Disease Severity Assessment Model Advising & Grants: No specific student advisees or grants are listed in the provided text. Labs/Teams: Co-founder of Paige, a leader in AI-driven digital pathology systems. Active in TUM's computational pathology research groups.

Karl-Ludwig Laugwitzمشاهده پروفایل

استاد

• Cardiology
• Cardiac Regeneration
• Stem Cell Research
• +۳ مورد دیگر

Prof. Dr. Karl-Ludwig Laugwitz is a leading cardiologist and Director of the Department of Internal Medicine I (Cardiology, Angiology, and Pulmonology) at the Klinikum rechts der Isar, Technical University of Munich (TUM). His work bridges basic cardiac research and clinical translation, focusing on cardiac regeneration via induced pluripotent stem cells (iPSCs), cardiovascular progenitor cell therapies, and stent innovation. He leads the Munich Heart Alliance within the DZHK and coordinates national/international trials like the ISAR Research Center. Educations: M.D. from Berlin, 1996 Habilitation at TUM Medical School, 2002 Heisenberg Fellowship at UC San Diego (2002–2005) Professorship at Harvard Medical School (2005–2012) Research Interests: Cardiac development, gene editing for Duchenne muscular dystrophy, bioengineered heart tissues, anti-restenosis stent coatings, and AI-driven cardiovascular diagnostics. His research has produced 450+ publications (h-index 52), 8 patents, and major grants including ERC and DFG funding. Clinical work emphasizes stent design, anti-platelet therapies, and molecular imaging of myocardial healing. Awards: ERC Principal Investigator Grant (2011) DFG Research Group 923 Leadership (2009–2014) Louis N. Katz Award (2004) Recent studies focus on AI phenotyping for mitral regurgitation outcomes, gene therapy for heart failure in DMD pigs, and VEGF mRNA myocardial injections during CABG. He also investigates long-term effects of drug-eluting stents and sex-based differences in cardiac outcomes.

Philipp Paprottkaمشاهده پروفایل

استاد

• Interventional Radiology
• Oncological Therapies
• Medical Technology Development
• +۳ مورد دیگر

Prof. Philipp Paprottka is a Professor of Interventional Radiology at the Technische Universität München (TUM), affiliated with the TUM School of Medicine and Health. He leads research integrating physics and engineering to develop novel techniques and medical products for interventional radiology. His work emphasizes preclinical and clinical studies on oncological therapies, as well as innovative teaching methods for manual interventional skills to establish a 'simulator culture' in German universities. Previously, he held leadership roles at Ludwig-Maximilians-Universität (LMU) and was awarded an extraordinary professorship there in 2018 before moving to TUM. He is also a board member of the Deutsche Gesellschaft für Interventionelle Radiologie. Education: Studied and earned his PhD at the Westfälische Wilhelms-Universität Münster. Transitioned to LMU in 2008, where he directed interventional radiology at Klinikum Großhadern. Awards include the Nachwuchspreis (2012, 2010) and a poster prize at the Österreichisch-Bayerischen Radiologiekongress (2010). Research focuses on radioembolization therapies, liver metastasis treatment, and optimizing clinical procedures. His publications emphasize predictive models for therapeutic outcomes and procedural safety improvements. He actively contributes to advancing interventional radiology through interdisciplinary collaboration and educational innovation.