جست‌وجوی استاد و پژوهشگر

• Machine Learning
• IoT Security
• Deep Learning
• +۴ مورد دیگر

Ponnusamy Vijayakumar is a researcher affiliated with SRM University in Kanchipuram, India, within the College of Engineering and Department of Electrical & Computer Engineering . His work spans interdisciplinary domains including Machine Learning , IoT Security , and Deep Learning , with additional expertise in Blockchain , Augmented Reality , and Cyber-Physical Systems . Research Interests : Vijayakumar focuses on applying advanced machine learning techniques to real-world problems such as energy sector optimization , food safety , and medical diagnostics . His recent work explores federated learning for secure IoT environments, predictive analysis using stochastic methods, and computer vision for rehabilitation and security applications. Article Trends : Over the past five years, he has contributed to IoT security through anomaly detection frameworks, augmented reality for plant disease detection, and blockchain for credentialing systems. His publications also address deep learning applications in agricultural quality analysis and medical imaging for musculoskeletal disorders. Collaborations : Vijayakumar has collaborated extensively with experts in Serbia, India, and Germany, particularly with researchers like Nemanja Zdravkovic , Aman Kumar Mishra , and Sowmya Natarajan , across conferences such as BISEC and journals like IEEE Access .

• Machine Learning
• Deep Learning
• Wireless Communications
• +۵ مورد دیگر

Ashit Kumar Dutta is an Associate Professor in the Department of Computer Science at King Saud University's College of Computer and Information Sciences. With over 40 publications spanning 2020-2025, his research bridges artificial intelligence with practical applications in healthcare, wireless communications, and cybersecurity. His collaborative work involves extensive partnerships with Saudi researchers and institutions, particularly in King Saud University's healthcare technology initiatives. Dr. Dutta's research interests focus on cutting-edge applications of machine learning and deep learning across multiple domains. His primary expertise lies in developing AI-driven solutions for healthcare challenges including cardiovascular disease detection, brain tumor segmentation, ALS diagnosis, and osteosarcoma identification using medical imaging. He also specializes in next-generation wireless communications, particularly 6G resource allocation, vehicular networks, and Internet of Things applications. His cybersecurity work emphasizes malware detection and network security using bio-inspired optimization techniques. The interdisciplinary nature of his research demonstrates a strong commitment to solving real-world problems through computational approaches. Analysis of his recent publications reveals a clear trend toward increasingly sophisticated AI architectures applied to healthcare challenges, with particular emphasis on federated learning approaches that maintain data privacy. His work on 6G communications shows growing sophistication in handling complex resource allocation problems across multiple dimensions. The consistent publication output across multiple high-impact venues demonstrates both productivity and recognition within his fields of expertise. Dr. Dutta maintains an active research program with significant contributions to both theoretical and applied aspects of computer science. His work on healthcare applications demonstrates particular promise for real-world implementation, with several papers focusing on practical deployment of AI solutions in medical settings. His expertise in both wireless communications and healthcare technology positions him uniquely to address emerging challenges in connected health systems.

• Osteoarthritis
• Magnetic Resonance Imaging
• Biomarkers
• +۳ مورد دیگر

Jeffrey B Driban, PhD, AT Ret, CSCS, is a Professor in the Department of Population and Quantitative Health Sciences at UMass Chan Medical School. He holds secondary appointments in Epidemiology at the T.H. Chan School of Medicine and Population Health Sciences at the Morningside Graduate School of Biomedical Sciences. His academic background includes a BS in Athletic Training from the University of Delaware, and both a Master of Education and Doctor of Philosophy in Kinesiology with an Emphasis in Athletic Training from Temple University, followed by a post-doctoral fellowship in Rheumatology at Tufts Medical Center. Dr. Driban's research focuses on novel risk factors, biomarkers, and imaging markers for osteoarthritis. His work aims to optimize clinical trials and deepen understanding of osteoarthritis pathophysiology, phenotypes, and prevention strategies. He envisions a streamlined therapeutic pipeline using targeted population subsets and sensitive outcome measures to reduce the global burden of osteoarthritis. Key research areas include: Accelerated osteoarthritis progression mechanisms Imaging biomarkers for early detection Lifestyle interventions for primary/secondary prevention Environmental factors in hand osteoarthritis Machine learning applications in prognosis His publication portfolio demonstrates consistent focus on osteoarthritis pathophysiology, diagnostic innovations (especially MRI and radiomics), and non-pharmacological interventions. Recent work emphasizes deep learning applications for automated lesion segmentation, biomechanical influences of activities like cycling/swimming, and prognostic modeling for end-stage disease. Longitudinal cohort analyses (e.g., Osteoarthritis Initiative) underpin much of this research. Dr. Driban has secured multiple NIH grants as Principal Investigator, including R01AR076411 (2021-2026) on composite structural endpoints in knee osteoarthritis and R01AR081791 (2023-2026) investigating environmental factors in hand osteoarthritis. He chairs task groups for the Osteoarthritis Action Alliance and serves on editorial boards for the Journal of Rheumatology, BMC Musculoskeletal Disorders, Journal of Athletic Training, and Arthritis Care & Research.

Jinan Fiaidhiمشاهده پروفایل

استاد

• Thick Data Analytics
• Deep Learning
• Few Shots Learning
• +۱۲ مورد دیگر

Dr. Jinan Fiaidhi is a Professor of Computer Science at Lakehead University, Canada since 2001. She served as Graduate Coordinator for the MSc and PhD programs in Computer Science and Biotechnology. She holds adjunct positions at the University of Western Ontario. Her academic journey includes degrees from Essex University (PgD, 1983) and Brunel University (PhD, 1986). She has held academic roles at institutions like Sultan Qaboos University and Philadelphia University prior to Lakehead. Her research focuses on Thick Data Analytics , Deep Learning , and Collaborative Learning , with applications in healthcare, medical imaging, and AI-driven diagnostics. She is a Professional Engineer (PEng) in Ontario and a Senior Member of IEEE. She chairs the IEEE Special Interest Group on Big and Thick Data for eHealth and founded the International Journal of Extreme Automation and Connectivity in Healthcare (IJEACH) as its Emeritus Editor-in-Chief. Her research is funded by NSERC and MITACS grants. Key projects include developing frameworks like QL4POMR for problem-oriented medical records and applying thick data analytics to Crohn’s disease, ulcerative colitis, and cataract severity analysis. Education: PhD in Computer Science, Brunel University (1986) PgD in Computer Science, Essex University (1983) Awards: None explicitly listed, but holds professional designations: PEng, IEEE Senior Member, ISP (CIPS), and MBCS (Chartered Computing). Grants: NSERC, MITACS (specific projects unspecified). Labs/Teams: Leads IEEE eHealth initiatives and collaborates on projects involving thick data analytics in healthcare interoperability and extreme automation.

• Healthcare Technology
• Digital Health Literacy
• Movement Disorders
• +۴ مورد دیگر

Inge Tuitert serves as a Lecturer in the Health Innovation master's program and researcher at the Digital Innovations in Healthcare and Welfare research group at NHL Stenden University of Applied Sciences. She maintains a significant research collaboration with the Neurology Department of the University Medical Center Groningen (UMCG), where she contributes to projects improving hyperkinetic movement disorder diagnostics. Her academic foundation includes a PhD in Human Movement Sciences from a collaborative program between UMCG and Aix-Marseille University focused on arm motor control. Education PhD in Human Movement Sciences (collaborative program), University Medical Center Groningen and Aix-Marseille University Research Interests Dr. Tuitert's work centers on healthcare technology implementation and digital health literacy, with specialized focus on movement disorders and motor control mechanisms. She investigates socio-economic determinants of digital health adoption in regional populations and develops computational approaches for movement disorder diagnostics. Her research uniquely bridges clinical neurology, human movement science, and digital innovation to create accessible healthcare solutions. Research Trends Her publication record demonstrates a clear trajectory toward computational methods in movement neuroscience, with increasing emphasis on machine learning applications for clinical diagnostics. Recent work shows strong interdisciplinary collaboration between movement scientists, neurologists, and computer scientists, particularly in developing quantitative tools for hyperkinetic disorder classification. She consistently integrates fundamental motor control principles with practical healthcare technology implementation. Research Projects Healthcare Technology in Frisian Population : Collaborative project with Friesland Planning Agency examining healthcare technology adoption patterns and their relationship to socio-economic factors and digital health literacy NEMO (Next Move in Movement Disorders) : UMCG-based initiative developing computer-aided classification tools for hyperkinetic movement disorders using quantitative movement analysis Professional Affiliations Lecturer, Health Innovation Master's Program, NHL Stenden University of Applied Sciences Researcher, Digital Innovations in Healthcare and Welfare Research Group Collaborating Researcher, Neurology Department, University Medical Center Groningen Advising and Grants As a master's program lecturer, Dr. Tuitert mentors students in digital health innovation projects. She secures research funding through institutional partnerships, including the Friesland Planning Agency collaboration, and participates in grant-funded initiatives at UMCG focused on movement disorder diagnostics. Her work demonstrates consistent success in obtaining support for interdisciplinary health technology research. Research Environment Dr. Tuitert operates within the Lectorate Digital Innovation in Healthcare and Welfare, which drives translational research in digital health solutions. She collaborates with multidisciplinary teams including neurologists, movement scientists, computer engineers, and public health researchers across NHL Stenden and UMCG, creating a robust ecosystem for healthcare technology innovation.

• High Voltage Technology
• Power Systems
• Energy Transmission and Distribution
• +۲ مورد دیگر

Celal Fadıl KUMRU is a Lecturer at the Department of Electrical and Electronics Engineering, Faculty of Engineering and Natural Sciences at Yildiz Technical University. He holds a Ph.D. in Electrical Facilities from the same institution (2016). His research focuses on High Voltage Technology, Power Systems, and Energy Transmission, with emphasis on cable insulation, dielectric properties, and smart grid technologies. He has conducted postdoctoral research at the University of Waterloo (2022-2023) under TÜBİTAK's International Postdoctoral Fellowship Program. Education: Bachelor's in Electrical Engineering (Yildiz Technical University, 2007) Master's in Electrical Facilities (Thesis, 2009) Doctorate in Electrical Facilities (2016) Research Interests: Dr. KUMRU specializes in high voltage cable systems, partial discharge detection using AI, and IoT-based monitoring solutions. His work bridges experimental testing (e.g., thermal analysis of underground cables) with computational modeling (finite element method applications). Recent studies include non-intrusive sensor systems for insulator defect diagnosis and adaptive relay coordination designs. Publications Trends: Focus areas include dielectric properties under varying conditions, cable aging analysis, and smart grid instrumentation. Machine learning methods (CNN, ANN) are increasingly applied in his recent works (2022-2024). Over 30 peer-reviewed articles published in journals like IEEE Transactions on Dielectrics and Electrical Insulation and Electric Power Systems Research. Awards: No specific awards listed, but maintains a h-index of 7 with 274 citations (Google Scholar). Teaching: Instructs core courses including Finite Element Method, Computer Aided Design, and specialized graduate seminars. Lab courses include Electrical and Circuit Laboratory and High Voltage Testing setups. Infrastructure: Developed an IoT-based weather station for high voltage labs and experimental setups for creep characteristic measurements in transformers. Collaborates on projects like dual-core transformer design and graphene-based cable materials. Future Works: Expanding research on AI-driven diagnostic systems for power infrastructure and sustainable insulation materials.

Diana Mateusمشاهده پروفایل

استاد

• Medical Image Analysis
• Machine Learning
• Geometric Computer Vision
• +۵ مورد دیگر

Dr. Diana Mateus is a Full Professor (Professeur des universités) at Ecole Centrale Nantes, France, affiliated with the LS2N laboratory and the Signal Image et Son research team. Her primary research focuses on medical image analysis, machine learning, geometric computer vision, and shape analysis. She leads projects in computational sonography, surgical data science, and vision-language integration in medical contexts. Dr. Mateus has extensive experience in medical imaging applications, including PET-based lesion analysis, ultrasound segmentation, and deep learning for healthcare. Her teaching includes courses on computer-aided medical procedures, medical augmented reality, and surgical robotics at TU Munich (noted in past sections). Research projects span computational surgineering, cross-modality image synthesis, and patient monitoring using wearable sensors. Key contributions include developing IFSS-Net for muscle segmentation in ultrasound, curriculum learning for fracture classification, and graph-based frameworks for treatment response prediction in lymphoma. Her work bridges clinical needs with advanced AI techniques, addressing challenges in low-count PET imaging and weakly supervised learning. Publications highlight innovations in medical imaging modalities (e.g., PET, ultrasound), with a focus on improving diagnostic accuracy and treatment planning. Collaborations include clinical institutions like the Deutsches Herzzentrum München (DHM) and teams at INRIA and MIT.

• Obstructive Sleep Apnea
• Cognitive Disorders
• Meta-Analysis
• +۴ مورد دیگر

Michelle Olaithe serves as an Honorary Research Fellow at the School of Psychological Science, The University of Western Australia. With an active research profile spanning sleep medicine, cognitive disorders, and audiology, she contributes significantly to understanding obstructive sleep apnea (OSA) mechanisms and behavioral interventions. Her research interests focus on Obstructive Sleep Apnea diagnostics , cognitive impacts of sleep disorders , meta-analytical approaches to behavioral interventions, and hearing loss rehabilitation . Using methodologies ranging from algorithm development to qualitative investigations grounded in Leventhal's self-regulation theory, her work addresses critical gaps in sleep and sensory health. Analysis of her recent publications reveals a strong trend toward algorithmic solutions for OSA prediction and evidence-based youth sleep interventions . Her 2024 meta-review in Behavioral Sleep Medicine synthesizes behavioral approaches for adolescent sleep issues, while her OSA-Onset algorithm series demonstrates technical innovation in sleep diagnostics. Helen Bearpark Memorial Scholarship (Australasian Sleep Association) Dr. Olaithe actively supervises Honours and Masters students while contributing to major research initiatives including the MRFF-funded project on OSA management in First Nations communities and the Raine Foundation's youth sleep intervention study. Her current projects emphasize community co-design and low-barrier solutions for sleep health disparities. She maintains active clinical roles as a psychologist at The Olive Branch Wellness Centre and Sleep W.A., bridging research with clinical practice in sleep medicine and cognitive behavioral therapy for insomnia.

• Medical Education
• Pathology
• Thyroiditis
• +۴ مورد دیگر

Collin O'Hara, MD is an Assistant Professor of Medical Education & Health Systems Science at the Texas College of Osteopathic Medicine, part of the University of North Texas Health Science Center. He holds board certifications in Anatomic Pathology, Clinical Pathology, and Cytopathology. Education: BS in Occupational Therapy (East Carolina University), MD (Wright State University), Residencies in Anatomic & Clinical Pathology (Georgetown University Medical Center & UT Southwestern Medical Center), and a Cytopathology Fellowship (Georgetown University). His expertise includes teaching pathology to first- and second-year osteopathic medical students. Research focuses on thyroid pathology in immunocompromised patients, rare kidney disorders like Goodpasture Syndrome, and diagnostic applications of imaging technologies. His work has contributed to understanding thyroiditis markers in AIDS patients and atypical presentations of autoimmune kidney diseases. Publications highlight clinical case studies bridging radiology and pathology, emphasizing diagnostic challenges in complex medical cases. No listed scientific awards or grants are noted in the provided materials.

• Education Policy
• Economics of Education
• Development Economics
• +۴ مورد دیگر

Alejandro J. Ganimian is an Associate Professor of Applied Psychology and Economics at New York University's Steinhardt School of Culture, Education, and Human Development, with a concurrent role as Visiting Associate Professor of Education at Harvard University's Graduate School of Education. He holds a Ph.D. in Quantitative Policy Analysis in Education from Harvard, an M.Sc. in Educational Research from the University of Cambridge (as a Gates Scholar), and a B.A. in International Politics from Georgetown University. His postdoctoral work included a fellowship at J-PAL South Asia. His research focuses on addressing educational challenges in low- and middle-income countries, particularly transitioning schooling systems to prioritize learning outcomes for first-generation learners. Methodologically, he combines randomized controlled trials (RCTs) with innovative metrics in psychology and economics. Key areas include teacher preparation for heterogeneous classrooms, school management strategies, and policy evaluation. Education: Ph.D. in Quantitative Policy Analysis in Education (Harvard University) M.Sc. in Educational Research (University of Cambridge) B.A. in International Politics (Georgetown University) Dr. Ganimian’s work has been published in top-tier journals like Nature , American Economic Review , and World Bank Economic Review . His research emphasizes scalable solutions, such as technology-aided instruction, mentorship programs, and diagnostic feedback systems for schools. He collaborates with governments and NGOs in Latin America and South Asia, advising initiatives like India’s Integrated Child Development Services (ICDS) and Argentina’s scholarship-mentoring programs. Awards and Fellowships: Jacobs Foundation Research Fellow National Academy of Education/Spencer Foundation Post-Doctoral Fellow Non-Resident Fellow at Brookings Institution His research on education technology highlights gaps between applied and formal learning (e.g., market vs. classroom math skills in India) and evaluates large-scale interventions for policy impact. He co-founded Enseñá por Argentina and Educar y Crecer , programs addressing educational equity. His current projects focus on school accountability mechanisms, teacher training, and leveraging data for systemic improvements.

Shuming Nieمشاهده پروفایل

استاد

• Analytical Chemistry
• Nanotechnology
• Bioengineering
• +۴ مورد دیگر

Shuming Nie is the Grainger Distinguished Chair in Bioengineering and Professor of Chemistry at the University of Illinois at Urbana-Champaign. He holds additional professorships in Bioengineering, Micro and Nanotechnology Lab, Electrical and Computer Engineering, and Materials Science and Engineering. His research focuses on nanotechnology, biomedical imaging, and materials science with applications in cancer diagnostics and therapy. Nie leads interdisciplinary efforts in developing advanced optical sensors, plasmonic nanoparticles, and SERS-based imaging systems for precision medicine. His work spans innovations in perovskite nanocrystals for multispectral imaging, biomimetic nanoparticle design, and machine learning-aided diagnostic tools. He has pioneered techniques like intraoperative molecular imaging for real-time tumor detection during surgery. Nie's contributions include over 400 publications and inventions in nanomedicine, including US patents for targeted drug delivery systems and bioconjugated nanocarriers. Research interests include: 1) Nanoparticle engineering for biodiagnostics 2) Optical biosensors 3) Photothermal therapy materials 4) Image-guided surgery platforms 5) Cancer nanotechnology 6) Biocompatible materials development. His lab collaborates across disciplines to bridge nanoscience with clinical applications.

• Medical Physics
• Quality Assurance in Radiology
• Radiation Dosimetry
• +۶ مورد دیگر

Hilde Bosmans is an Associate Professor at the Faculty of Medicine, KU Leuven, heading the Medical Physics & Quality Assessment unit within the Department of Imaging & Pathology. She holds key roles in the Division of Medical Imaging, OMFS-IMPATH, iSi Health Institute, and KU Leuven Cancer Institute, with committee memberships spanning radiation protection, medical physics, and faculty governance. Her research centers on medical physics innovation, specializing in quality assurance systems, patient radiation dose optimization, and advanced x-ray/CT techniques. Current emphases include AI-driven synthetic data applications for breast imaging, virtual modeling of microcalcification detection, and dose monitoring in lung cancer screening protocols. She bridges physics-based modeling with clinical radiology to enhance diagnostic accuracy while minimizing radiation exposure across modalities. Recent publications reveal a concentrated focus on breast cancer imaging advancements through AI and radiomics, with significant work on synthetic data validation, pectoral muscle segmentation impacts, and virtual phantom comparisons. Parallel efforts optimize CT protocols for renal and cardiac applications while maintaining rigorous dose control. Dr. Bosmans actively supervises doctoral candidates including Van Camp, A., Houbrechts, K., and Koukoutegos, K., and leads major funded projects through 2028 such as AI-driven breast cancer staging algorithms, photon-counting CT cardiac imaging, and lung cancer screening optimization. Her grants consistently integrate clinical translation with physics-based modeling. She directs the Medical Physics & Quality Assessment unit while contributing to interdisciplinary teams at iSi Health and the Cancer Institute, where her virtual imaging trials inform both educational frameworks and clinical protocol development for dento-maxillofacial CBCT and mammography systems.

George Kinnearمشاهده پروفایل

مدرس

• Mathematics Education
• Technology in Education
• Online Assessment Systems
• +۳ مورد دیگر

Dr. George Kinnear is a Lecturer in Technology-Enhanced Mathematics Education at the University of Edinburgh's School of Mathematics. He holds an MA in Pure Mathematics and a PhD in Analysis from the University of Edinburgh, where his doctoral research explored foundational mathematical concepts. Transitioning from pure mathematics research to education, he now focuses on optimizing computer-based assessment systems like STACK, aiming to enhance student learning experiences through technology. His work bridges pedagogy and digital tools, particularly in undergraduate mathematics. Education: PhD in Analysis, University of Edinburgh MA in Pure Mathematics, University of Edinburgh Research Interests: George’s research centers on how students learn mathematics through technology, particularly in online assessment systems. He investigates tools like STACK to improve feedback mechanisms, digital exercise design, and large-class instructional practices. His recent projects include developing interactive course materials and workshops to familiarize educators with e-assessment platforms, driven by post-pandemic educational demands. Grants & Projects: He is currently funded to convert traditional workbooks into interactive STACK-based resources, with plans to share these tools across universities by 2025. Collaborations with Professor Chris Sangwin (STACK developer) and colleagues aim to refine computer-aided assessment through teacher feedback and experimental studies. Labs/Teams: His work is embedded within the University of Edinburgh’s School of Mathematics, focusing on Technology-Enhanced Mathematical Education initiatives. He contributes to interdisciplinary efforts to modernize mathematics education through digital innovation.

Monali Malvankarمشاهده پروفایل

استادیار

• Health Economics
• Cost-effectiveness Analysis
• Health Policy
• +۳ مورد دیگر

Monali Malvankar, PhD, serves as Assistant Professor at Western University's Schulich School of Medicine & Dentistry with dual appointments in the Department of Ophthalmology and Department of Epidemiology and Biostatistics. Her research bridges clinical ophthalmology with health economics, focusing on cost-effectiveness analysis and resource allocation for surgical interventions and public health programs. She earned her PhD in Management Science from the Richard Ivey School of Business at the University of Western Ontario, establishing her foundation in quantitative modeling and optimization techniques. Dr. Malvankar's research portfolio centers on Health Economics and Cost-effectiveness Analysis , with significant contributions to Health Policy development, HIV Prevention Resource Allocation , and Simulation Modeling . Her work employs systematic reviews, meta-analyses, and mathematical optimization to evaluate healthcare technologies and protocols, particularly in glaucoma management and cataract surgery. She integrates management science principles with clinical outcomes to inform evidence-based policy decisions. Analysis of her publication record reveals two dominant research trajectories: ophthalmic interventions (comprising 70% of her work) focusing on glaucoma devices and cataract surgical protocols, and HIV prevention resource allocation (30%) emphasizing incentive structures and multi-level optimization. Her ophthalmology research consistently demonstrates cost-benefit advantages of new technologies like iStent within Canadian healthcare frameworks, while her public health work develops novel allocation models for HIV prevention resources across diverse populations. Her scientific contributions have been recognized through: Translational Science Award from the Canadian Glaucoma Society (2015) Drance Award from the Canadian Ophthalmology Society (2013) TOP 10 Publication designation at the World Glaucoma Congress (2013) Dr. Malvankar has secured competitive research funding from multiple sources: Lawson Health Research Institute Internal Research Fund (2014) Air Force Office of Scientific Research (AFOSR-LRIR) Air Force Research Lab Mathematical Modeling Institute USDA NIFA National Robotics Initiative Canadian National Institute for the Blind Baker New Researcher Award (2011) Her collaborative research involves interdisciplinary teams across ophthalmology, epidemiology, and engineering departments at Western University, with strong partnerships at Lawson Health Research Institute. Current projects focus on expanding economic evaluations of emerging ophthalmic technologies and refining resource allocation models for infectious disease prevention within constrained healthcare budgets.

• Oral Surgery
• Regenerative Medicine
• Biomaterials
• +۶ مورد دیگر

Prof. Dr. Ralf Smeets is a leading academic in regenerative orofacial medicine at the University Medical Center Hamburg-Eppendorf , holding the Heisenberg Professorship from the German Research Foundation (DFG). As Head of the Section for Regenerative Orofacial Medicine and Research Leader in Oral and Maxillofacial Surgery , his work bridges clinical practice with translational research in biomaterials, dental implants, and tissue engineering. Research Interests include: Biocompatibility of implant materials Regenerative strategies for bone and soft tissue Surface modification of titanium/zirconia implants Stem cell applications in dentistry Medical imaging artifact analysis Oral manifestations of systemic diseases Scientific Contributions span 15+ peer-reviewed publications (2025-2016) covering: Novel implant coatings (silver/zinc, PEO) Silk fibroin-based wound dressings 3D-printed prosthetics for cleft patients Magnesium implant degradation mechanisms Immunotherapy targets in head/neck cancer Bone augmentation techniques Awards : Heisenberg Professorship (DFG). Collaborations include interdisciplinary teams in materials science, oncology, and radiology. Contact : r.smeets@uke.de