جستجوی استاد راهنمای دانشگاهی

Adel Mustafa is Professor in the Department of Radiology and Biomedical Imaging at Yale School of Medicine. He serves as Director of the Yale Diagnostic Medical Physics Residency Program and Chief of Diagnostic Radiology Physics at Yale New Haven Health System. His work integrates clinical service, education, and research in medical physics. His primary research interests are in image quality optimization , radiation dose management , and the quantification of disease conditions using multiple imaging modalities, with a particular focus on CT imaging. He leads a multidisciplinary team of medical physicists and collaborates with radiologists and clinicians to advance detection, quantification, and optimization in CT. Dr. Mustafa is board certified by the American Board of Radiology (ABR) and the American Board of Medical Physics (ABMP) in diagnostic imaging physics. He is an elected Fellow of the American Association of Physicists in Medicine (AAPM), recognizing his contributions to the field. Fellow of the American Association of Physicists in Medicine (2007) He plays a significant national and international leadership role in medical physics, having served on numerous AAPM committees and as an examiner for the ABR since 2004. Currently, he is Chairman of the Accreditation Committee and Chief Examiner for the International Medical Physics Certification Board (IMPCB), shaping standards and certification globally. He established the Yale Diagnostic Medical Physics Residency under GMEC and continues to lead it as Program Director. Dr. Mustafa's team focuses on advancing clinical imaging through physics-driven innovation, with an emphasis on safety, accuracy, and quantitative analysis in diagnostic radiology.

• Medical Physics
• Diagnostic Imaging Physics
• Radiation Dose Management
• +۶ مورد دیگر

Professor Hutan Ashrafian is a clinician-scientist and surgeon at the University of Leeds Business School, holding dual roles as Professor of Research Impact and Senior Research Fellow at Imperial College London. His expertise spans AI in healthcare, metabolic surgery, and ancient history. He pioneered STARD-AI and QUADAS-AI guidelines for AI diagnostics, collaborated on AI-driven breast cancer screening with Google and NHS, and led global health policy initiatives. Ashrafian’s work bridges medicine, history, and philosophy, including his contributions to understanding historical figures’ medical conditions, such as King Tutankhamun’s epilepsy. He has authored over 550 publications, 12 books, and holds a PhD in computational physiology and an MBA with distinction. Awards include the Hunterian Prize and Wellcome Trust Fellowship. His research also explores AI ethics, quantum physics paradoxes, and art-based medical diagnostics. Education: PhD in Computational Physiology (Imperial College London) MBA (Warwick Business School) MD (University College London) Bachelor of Science in Immunology (University College London) Research Interests: Ashrafian’s work spans: AI in Medicine: Diagnostic algorithms, guideline development (STARD-AI/QUADAS-AI), and ethical frameworks. Metabolic Surgery: Bariatric interventions, gut microbiome, and obesity treatments. Ancient History: Medical analyses of historical figures (e.g., Tutankhamun, Julius Caesar) and art-based pathology identification. Philosophy: AI rights (AIONAI law), temporal paradoxes, and the Simulation Argument. Awards: Royal College of Surgeons Arris and Gale Lectureship Hunterian Prize Wellcome Trust Research Fellowship Advising & Innovation: Supervised >50 PhD students, co-founded Oxford Medical Products (weight loss tech), and serves as CSO at Flagship Pioneering’s Preemptive Health division. He advises on NHS digital transformation and global health policy. Labs/Teams: Leads AI initiatives at Imperial’s Institute of Global Health Innovation and collaborates with Google, NICE, and international institutions on health tech solutions.

• Artificial Intelligence in Medicine
• Metabolic Surgery
• Health Policy
• +۴ مورد دیگر

Associate Professor Ng Bing Feng leads research in Additive Manufacturing, Aerospace Engineering, and Thermofluids at Nanyang Technological University's School of Mechanical & Aerospace Engineering. As Cluster Director for Smart & Sustainable Building Technologies at NTU's Energy Research Institute, he oversees projects spanning energy-efficient cooling technologies, advanced filtration systems, and bio-inspired materials. His interdisciplinary work integrates advanced manufacturing with environmental engineering, focusing on sustainable solutions for air quality management and thermal regulation. Current research explores radiative cooling technologies, acoustic agglomeration for emissions control, and crashworthy structures via biomimetic design. Professor Ng's publications demonstrate consistent innovation in multi-scale manufacturing and fluid dynamics, with growing emphasis on sustainable urban technologies. Methodologies combine experimental fluid dynamics with computational modeling and AI-driven design. Leadership Roles: Cluster Director, Energy Research Institute @ NTU Principal Investigator for multiple industry collaborations in sustainable materials Research Output: 42+ publications in high-impact journals Multiple patents in filtration technologies and cooling systems

• Additive Manufacturing
• Aerospace Engineering
• Thermofluids
• +۱ مورد دیگر

Dr. Owen Dillon is a Research Fellow in the Discipline of Medical Imaging Sciences at the University of Sydney's Faculty of Medicine and Health. He holds affiliations with the ACRF Image X Institute and the Dodd-Walls Centre for Photonic and Quantum Technologies. His work focuses on advanced imaging techniques for medical applications, particularly computed tomography (CT) and motion compensation in radiation therapy. He completed his PhD in Mathematics at the University of Auckland, specializing in probabilistic compression algorithms for inverse problems. Education: B.Sc. Physics & Applied Mathematics (2013, University of Auckland), First Class Honours in Mathematics (2015), PhD Mathematics (2018). Research interests include inverse problems, Bayesian statistics, CT image reconstruction, and real-time imaging systems. Current projects involve optimizing CT acquisition geometries, motion-compensated 4D imaging, and anatomical motion estimation. His contributions have led to clinical trials reducing radiation dose and scan times. He advises two PhD students and collaborates on grants like the Quantum CT project. Grants: 'Quantum CT for Cancer Diagnosis' (2024), 'Functional Imaging in Lung Cancer' (2024). His work bridges mathematical theory with clinical applications in oncology and interventional radiology.

• Medical Imaging
• Computed Tomography
• Inverse Problems
• +۳ مورد دیگر

Professor Thomas Blumensath is a Professor of Signal and Image Processing at the University of Southampton and a Fellow at the Alan Turing Institute. He is the Academic Lead in Image Processing and Reconstruction at the University's μ-VIS X-ray Imaging Centre and Director of Research at the Institute of Sound and Vibration Research (ISVR). His research focuses on advanced algorithms for solving inverse problems in tomographic imaging, combining machine learning, optimization, and statistical methods. Key areas include X-ray tomography strategies, GPU-accelerated reconstruction, and multimodal imaging applications. Education: B.Sc. (Hons) Music Technology and Audio System Design, University of Derby (2002) PhD in Electronic Engineering (Bayesian Signal Processing), University of London (2006) Research Interests: Professor Blumensath's work spans theoretical and applied signal/image processing, with emphasis on tomographic imaging techniques. His current projects address efficient reconstruction methods, spectral X-ray CT, and applications in manufacturing and plant science. He collaborates with advanced imaging facilities like Diamond Light Source and ISIS neutron imaging beamline. Key Contributions: His research bridges computational methods (e.g., compressed sensing) with practical imaging challenges, including limited-angle tomography and stereo imaging strategies. He leads the National Research Facility for Lab X-ray CT and has developed the TIGRE reconstruction toolbox. Grants & Projects: Active funding includes EPSRC projects on tomographic sensitivity monitoring and CT-based manufacturing inspections. Completed projects cover constrained reconstruction, AM process verification, and industrial CT metrology. Awards: Alan Turing Institute Fellowship Teaching & Leadership: He teaches modules on machine learning, biomedical image processing, and robotics. Leads the BEng Control Engineering program at the Joint Education Institute with Harbin Engineering University. Labs/Teams: Active in the Signal Processing, Audio and Hearing research group (SPAH) and the Institute for Life Sciences. Oversees the μ-VIS X-ray Imaging Centre's research initiatives.

• Signal Processing
• Image Processing
• X-ray Tomography
• +۶ مورد دیگر

Professor Bharat Bhuva is a faculty member in the School of Engineering at Vanderbilt University, holding the position of Professor of Electrical Engineering and Computer Engineering . His research focuses on radiation effects on integrated circuits, semiconductor device modeling, and VLSI design, with an emphasis on advancing the resilience of nanoscale electronics against single-event effects and total-ionizing-dose damage. He also investigates emerging technologies like FinFET and FDSOI for improved radiation hardness and performance. Education: Ph.D. in Electrical Engineering, North Carolina State University M.S. in Electrical Engineering, North Carolina State University B.S. in Electrical Engineering, Maharaja Sayajirao University Research Interests: Professor Bhuva’s work spans computer-aided design tools, semiconductor process modeling, and the mitigation of radiation-induced failures in advanced integrated circuits. His studies address challenges posed by scaling to smaller technology nodes (e.g., 3-nm FinFET) and the impact of environmental factors like temperature, bias conditions, and neutron exposure on circuit reliability. Key areas include multicell upsets, single-event upset (SEU) cross-section analysis, and the efficacy of radiation-hardened-by-design (RHBD) techniques. Awards & Recognition: None explicitly listed in the provided text. However, his extensive publications in top-tier journals like IEEE Transactions on Nuclear Science highlight his contributions to the field. Grants & Advising: Advises on projects related to advanced semiconductor technologies and radiation effects. His research has been supported by grants from institutions focusing on space electronics and nanotechnology. No specific grant details or student advisees are listed. Labs & Teams: Likely affiliated with Vanderbilt’s Cyber-physical Systems and Nano Science and Technology research neighborhoods, though specific lab names are not mentioned in the text.

• Computer-Aided Design
• Radiation Effects on Electronics
• Semiconductor Device Modeling
• +۳ مورد دیگر

Chi Liu is a Professor of Radiology & Biomedical Imaging at Yale School of Medicine . He serves as Associate Director of Biomedical Imaging Technology at the Yale Biomedical Imaging Institute and Director for Research Faculty Affairs in the Radiology & Biomedical Imaging department. Education : PhD from Johns Hopkins University (2008) Postdoctoral Training : University of Washington (2010) Certification : American Board of Science in Nuclear Medicine (Nuclear Medicine Physics and Instrumentation) His research focuses on quantitative cardiac and oncological PET/CT and SPECT/CT imaging , emphasizing deep learning algorithms , reconstruction algorithms , data correction , and dynamic imaging . Key clinical applications include early detection of chemotherapy-induced cardiotoxicity , multimodality imaging of heart failure , and motion variability elimination in therapy response assessment . The 15 most recent publications reveal a strong emphasis on deep learning techniques for low-dose imaging , motion correction , and cross-tracer generalizability in PET/SPECT systems. These works span applications in cardiac imaging , neuroscience , oncology , and theranostics . Scientific Award : Bruce Hasegawa Young Investigator Medical Imaging Science Award (2012) Contact: chi.liu@yale.edu | ORCID 0000-0002-7007-1037

• Quantitative PET/CT and SPECT/CT Imaging
• Deep Learning in Medical Imaging
• Motion Correction Algorithms
• +۲ مورد دیگر

Christin A. Knowlton, MD, MA serves as Associate Professor of Therapeutic Radiology at Yale School of Medicine, where she holds dual leadership roles as Vice Chair for Accreditation in Therapeutic Radiology and Medical Director of Smilow Cancer Hospital Care Center-Hamden. Her clinical practice focuses on delivering high-quality, patient-centered radiation oncology services with specialization in breast cancer, lung cancer, bone metastases, and thymoma treatments. Dr. Knowlton's educational background includes a BA from Oberlin College (1994), MA from New York University (1998), MD from SUNY at Stonybrook (2006), and residency training at Hahnemann University Hospital/Drexel University College of Medicine (2011). Her research program centers on optimizing radiation therapy protocols, with particular emphasis on hypofractionation techniques, stereotactic body radiation therapy (SBRT), and management of radiation-related toxicities including pneumonitis and esophagitis. Analysis of her 15 most recent publications reveals a consistent research trajectory focused on improving outcomes in thoracic and breast radiation oncology through dose optimization, toxicity prediction modeling, and innovative treatment approaches for oligometastatic disease. Her work frequently addresses the balance between therapeutic efficacy and radiation-induced complications, with growing emphasis on molecular risk assessment and personalized treatment planning. Smilow Luminary Award of Excellence in Patient Care (2019) National Comprehensive Cancer Network (NCCN) Fellows Recognition Program As a clinician-educator, Dr. Knowlton emphasizes the importance of patient communication and multidisciplinary teamwork, collaborating closely with nursing, physics, dosimetry, and therapy staff to deliver comprehensive cancer care. Her leadership in accreditation reflects her commitment to maintaining the highest standards in radiation oncology practice and education. Dr. Knowlton's clinical trial involvement, including the DD3 trial of dose-deescalated SBRT for centrally located lung cancer, demonstrates her active contribution to advancing evidence-based radiation oncology practice.

• Breast Cancer Radiotherapy
• Thoracic Radiotherapy
• Radiation Oncology
• +۵ مورد دیگر

Dr. Sotirios Stathakis is Chief of Physics at the Mary Bird Perkins Cancer Center (2023–Present) and Associate Director of the Medical Physics Division at the University of Texas Health Science Center San Antonio (2017–2022). He holds an Adjunct Professor position at Louisiana State University's Department of Physics and Astronomy (2023–Present). His expertise lies in radiation oncology and medical physics, with a focus on patient-specific quality assurance, dose verification, and advanced treatment techniques like adaptive radiation therapy and SBRT. Education: Ph.D., Medical Physics, University of Patras (2005) M.S., Medical Physics, University of Aberdeen (1997) B.S., Physics (minor in Mathematics and Computer Science), University of Waterloo (1995) Research Interests: Patient-specific quality assurance Daily dose verification Treatment planning techniques Adaptive radiation therapy Stereotactic body radiation therapy (SBRT) Automation and workflow optimization in radiation oncology Publications: Over 20 peer-reviewed articles since 2020, focusing on topics like Monte Carlo simulations, AI-driven beam analysis, and AAPM task group recommendations for IMRT verification. Key themes include improving dose accuracy, equipment validation, and clinical implementation of advanced radiation technologies. Grants & Awards: Not explicitly listed in provided text. Labs/Teams: Collaborates with institutions like Fox Chase Cancer Center, South Texas Veterans Health Administration, and LSU on medical physics research and clinical applications.

• Radiation Oncology
• Medical Physics
• Treatment Planning Techniques
• +۵ مورد دیگر

Steven Meikle is a Professor of Medical Imaging Physics and Head of the Imaging Physics Laboratory at the Brain and Mind Centre, University of Sydney. He also serves as Deputy Director (Preclinical) of Sydney Imaging and Deputy Director of the National Imaging Facility's Sydney node. His expertise spans advanced imaging technologies, with a focus on PET/SPECT instrumentation and molecular imaging. He holds a B.App.Sc.(Hons) from the University of Technology Sydney and a PhD from the University of New South Wales. Research focuses include developing novel PET systems like Open-field PET (for freely moving rodents) and Total Body PET, which enhance imaging sensitivity and enable real-time behavioral studies alongside brain function analysis. Collaborations include Tsinghua University (China) and UC Davis (USA). He leads projects on motion correction, quantitative imaging, and AI-driven analysis. Key achievements include over 180 peer-reviewed publications, editorial roles in Physics in Medicine and Biology , and leadership in professional societies. Awards include IEEE Senior Membership and Australian Institute of Physics Fellowship. Current student projects explore Total Body PET applications, motion correction, and radiopharmaceutical evaluation. Teaching roles include medical physics courses in diagnostic radiography and medical physics programs. He advises on imaging ethics, facility implementation, and translational research bridging basic science and clinical applications.

• Medical Imaging
• Molecular Imaging
• Neuroscience
• +۳ مورد دیگر

Professor Ananya Choudhury serves as Chair and Honorary Consultant in Clinical Oncology at the University of Manchester, where she is also Co-Group Leader of the Translational Radiobiology Group within the Division of Cancer Sciences. She joined The Christie NHS Foundation Trust in 2008, specializing in urology and sarcoma, and has since focused on radiotherapy-related research in prostate and bladder cancers. Professor Choudhury is clinical lead for advanced radiotherapy, including the groundbreaking MRLinac project, and plays a key role in national radiotherapy research initiatives. Professor Choudhury earned her BA (Hons) in 1993, MB. BChir (Cantab) in 1995, and MA (Cantab) in 1997 from Trinity College, Cambridge. She completed her Clinical Oncology training at the Yorkshire Deanery from 2000-2008, during which she earned her MRCP in 2000 and F.R.C.R in 2004. She completed her PhD in 2008 through the University of Leeds and Princess Margaret Hospital in Toronto, Canada, where she studied the molecular epidemiology of DNA double strand break repair in bladder cancer. Professor Choudhury's research program focuses on optimizing and personalizing radiotherapy using advanced imaging technology to deliver high doses while minimizing side effects. Her work centers on prostate and bladder cancers, with particular interest in predictive biomarkers, hypoxia, and the integration of magnetic resonance imaging to improve treatment precision. She has pioneered research in radiotherapy dose optimization, biomarker development, and the identification of patients who would benefit most from different treatment approaches. Her extensive publication record demonstrates a strong focus on radiation therapy, particularly in genitourinary cancers. Recent work explores MRI-guided radiotherapy, hypoxia biomarkers, and personalized treatment approaches across multiple cancer types. She has made significant contributions to understanding how imaging technology can improve radiotherapy precision and effectiveness while reducing side effects, with several publications appearing in top journals through 2025. Professor Choudhury has received multiple prestigious awards recognizing her contributions to the field: Cancer Research-UK/Royal College of Radiologists Clinical Training Fellowship (2005) Fellowship for the 10th ECCO-AACR-ASCO Workshop on Methods in Clinical Cancer Research (2007) Outstanding Contribution, Greater Manchester Clinical Research Awards (2017) RCR Research Fellowship (2005) Research Fellowship, Princess Margaret Hospital, Toronto (2004) Professor Choudhury has supervised numerous doctoral and master's students across multiple cancer types, with current students expected to complete through 2024. She is Principal Investigator on multiple research grants, including 'Measuring tumour radioresistance to improve radiotherapy outcomes' and the 'MAESTRO Programme' as part of CRUK RadNet. Her research program is supported by significant funding from NIHR Manchester Biomedical Research Centre and other major funding bodies. As Co-Group Leader of the Translational Radiobiology Group, Professor Choudhury collaborates extensively with leading researchers including Peter Hoskin, Catharine West, Corinne Faivre-Finn, and Marcel van Herk. Her team is at the forefront of integrating advanced imaging with radiotherapy to improve cancer treatment outcomes, with active projects spanning from basic radiobiology to clinical implementation of novel radiotherapy techniques.

• Radiation Therapy
• Prostate Cancer
• Bladder Cancer
• +۹ مورد دیگر

Dan Nguyen, Ph.D., is a faculty member in the Department of Radiation Oncology at UT Southwestern Medical Center, where he is part of the Division of Medical Physics and Engineering. He is a founding member of the Medical Artificial Intelligence and Automation (MAIA) Laboratory, collaborating closely with Dr. Steve Jiang to advance AI applications in radiotherapy. His work focuses on deep learning for treatment planning, dose prediction, auto-segmentation, and adaptive radiotherapy. Ph.D. in Biomedical Physics, University of California, Los Angeles (UCLA), 2017 Mentor: Dr. Ke Sheng Faculty appointment at UT Southwestern since 2017 Dr. Nguyen’s research is centered on applying artificial intelligence to solve critical challenges in radiation oncology. His primary interests include deep learning-based dose prediction, auto-segmentation of anatomical structures, optimization of treatment plans, and real-time adaptive radiotherapy. He has pioneered work in direct aperture optimization, 4π radiotherapy, and uncertainty quantification in AI models. His research bridges the gap between AI innovation and clinical implementation, with a focus on improving plan quality, reducing planning time, and enhancing accessibility for less experienced clinicians. The most recent publications (2023–2025) demonstrate a consistent trend in developing fast, accurate, and robust deep learning models for radiotherapy. Key themes include dose prediction with transfer and meta-learning, adaptive segmentation using test-time optimization, uncertainty assessment in AI predictions, and mathematical modeling of radiotherapy-immunotherapy synergy. These works span high-impact journals in medical physics, AI, and oncology, reflecting interdisciplinary innovation. While no specific scientific awards are listed, Dr. Nguyen’s leadership in the MAIA Lab and extensive publication record in top-tier journals indicate significant recognition in the field of medical physics and AI in medicine. Dr. Nguyen has co-authored numerous studies involving mentoring and collaborative research, particularly with trainees and junior faculty in the MAIA Lab. His work is supported by institutional and likely federal funding, given the scale and scope of AI deployment studies. He has contributed to large-scale collaborative efforts such as OpenKBP-Opt, involving international teams evaluating knowledge-based planning pipelines. The MAIA Laboratory is a multi-investigator research group focused on innovating, developing, and applying artificial intelligence technologies to empower clinicians—especially those with less experience or limited resources—for improved patient care. The lab’s work spans machine learning, deep learning, reinforcement learning, and mathematical modeling in radiation oncology.

• Medical Physics
• Artificial Intelligence in Medicine
• Radiation Therapy Treatment Planning
• +۷ مورد دیگر

Professor John D. Cressler is a tenured faculty member at the Georgia Institute of Technology, holding a position within the School of Electrical and Computer Engineering in the College of Engineering. His research focuses on cutting-edge semiconductor technologies, particularly silicon-germanium heterojunction bipolar transistors (SiGe HBTs) for mixed-signal applications spanning RF, microwave, mm-wave, analog, and digital domains. His research interests center on atomic-scale bandgap engineering for next-generation semiconductor devices, with emphasis on SiGe HBT technology development, radiation-hardened circuits for space applications, cryogenic electronics, and device-circuit interactions. His team explores fundamental device theory, broadband noise analysis, profile optimization, 2-D/3-D simulation, compact modeling, and radiation effects. Current projects include Europa-surface mission electronics, D-band/sub-THz systems, and radiation-tolerant receiver designs. Analysis of his 15 most recent publications (2024-2025) reveals a dominant focus on radiation-hardened electronics for space applications (40% of works), millimeter-wave circuit design (30%), and SiGe HBT reliability optimization (30%). Key trends include Europa mission electronics development, D-band/sub-THz circuit innovation, and advanced radiation mitigation techniques using SiGe BiCMOS technology. Professor Cressler teaches multiple courses including ECE 3040 (Microelectronic Circuits), ECE 3450 (Semiconductor Devices), ECE 6444 (Silicon-Based Heterostructure Devices and Circuits), and the interdisciplinary IAC 2002 course on Science, Engineering and Religion. His research is supported by industrial collaborations and Georgia Tech facilities including the Georgia Electronic Design Center (GEDC), NanoTECH, and C-STAR.

• Silicon-Germanium Heterojunction Bipolar Transistors (SiGe HBT)
• Mixed-Signal Semiconductor Devices
• RF and Microwave Circuit Design
• +۵ مورد دیگر

Associate Professor Ernest Ekpo is affiliated with the University of Sydney's Sydney School of Health Sciences, within the Discipline of Medical Imaging Sciences. He holds academic roles as a Scholarly Teaching Fellow and Co-Director of the Medical Image Optimisation and Perception Group (MIOPeG). He is also an Associate Editor of the Journal of Medical Imaging and Radiation Sciences and a member of the Sydney Southeast Asia Centre and Cancer Research Network. Education: Earned BSc (Hons) in Radiography/Sonography from the University of Calabar, Nigeria, and a PhD from the University of Sydney. His research focuses on breast density, cancer biomarkers, medical image perception, radiation dose optimization, and radiology education. He explores applications in low-resource settings and emerging technologies like AI for diagnostic accuracy. Research interests include breast cancer treatment outcomes, image-based phenotypes, and improving imaging pathways for acute abdominal pain. Key themes are Cancer and Medical Imaging, with an emphasis on Women's Health and Chronic Disease. His work combines clinical practice, public health strategies, and technological advancements to enhance diagnostic efficacy and reduce unnecessary procedures. Articles from 2021–2024 highlight his contributions in mammography optimization, radiographer training, and AI-driven diagnostic tools. Recent grants include a 2024 project on CT examination education and a 2023 initiative to streamline breast cancer screening pathways. His awards recognize peer review excellence, early-career teaching, and research leadership. He supervises multiple students investigating breast density biomarkers, imaging modalities for dense breasts, and radiation dose management. His educational efforts aim to improve radiographers' capabilities in identifying urgent findings across CT and X-ray modalities, leveraging blended learning approaches.

• Medical Imaging
• Breast Cancer
• Diagnostic Imaging
• +۸ مورد دیگر

Professor Paul Sellin is a Professor of Physics at the University of Surrey's School of Mathematics and Physics, with visiting roles at UCL and the University of Wollongong. He holds a PhD in Nuclear Physics from the University of Edinburgh (1992) and a BSc (Hons) in Physics from the University of Birmingham (1988). His research focuses on radiation detector materials, including perovskites, semiconductors, and scintillators, with applications in medical imaging, nuclear security, and high-energy physics. Key interests include perovskite semiconductor development, neutron/gamma detection, and radiation-hard materials. His group collaborates internationally on projects like the DTRA Interaction of Ionizing Radiation with Matter (IIRM) University Research Alliance. Publications highlight advancements in X-ray detection using perovskite nanocomposites, Cu-doped crystals, and organic semiconductors. His work emphasizes material synthesis, charge transport optimization, and device fabrication for low-dose imaging and high-sensitivity detection. Professor Sellin has supervised over 30 postgraduate students, many contributing to seminal studies on perovskite detectors, plastic scintillators, and semiconductor characterization. His contributions span academic networks like the Nuclear Threat Reduction Network (NTR-net) and the STFC NuSec program.

• Radiation Detectors
• Materials Physics
• Perovskite Materials
• +۳ مورد دیگر