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.
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.
Yading Yuan, PhD is an Associate Professor of Radiation Oncology (Physics) at Columbia University Irving Medical Center and a member of the Data Science Institute. He holds a PhD in medical physics from the University of Chicago (2010) and completed clinical residency at Harvard Medical Physics Program (2013). His research focuses on AI-driven innovations in radiation oncology, including automated medical image analysis systems, federated learning frameworks for tumor segmentation, and data-driven approaches to personalized cancer treatment. He is certified by the American Board of Radiology and licensed in New York State. Education: PhD in Medical Physics (University of Chicago, 2010); Clinical Residency (Harvard Medical Physics Program, 2013). Research interests include: automated knowledge-based treatment planning, large-scale clinical AI systems, medical image reconstruction algorithms, and panomics integration for precision oncology. His work emphasizes translating data science advancements into clinical practice to improve patient outcomes. Key trends in his publications include federated learning for privacy-preserving medical AI, tumor segmentation in multi-modal imaging (PET/CT, MRI), and AI-driven prediction of treatment outcomes and recurrence risks. Recent work emphasizes decentralized learning architectures and cross-institutional collaboration systems. Scientific Awards: Distinguished Reviewers 2013 (selected by peer review committees) Advising/grants: No specific student names or grant details listed in provided text. His work is supported through institutional and collaborative research initiatives. Labs/teams: Active member of Columbia's Data Science Institute and Radiation Oncology department, contributing to interdisciplinary medical AI research groups.
Dr Emily Hewson is a Cancer Institute NSW Early Career Fellow and member of the Sydney School of Health Sciences at the University of Sydney's Faculty of Medicine and Health. Her research focuses on advancing real-time radiation therapy techniques, particularly in managing intrafraction motion for prostate and other cancers. She leads projects involving multileaf collimator (MLC) tracking, dose optimization, and deep learning integration in radiation oncology. Research interests include adaptive radiotherapy systems, kilovoltage intrafraction monitoring (KIM), and clinical trial implementation (e.g., TROG 15.01 SPARK trial). Her work emphasizes improving treatment accuracy through real-time dose-guided approaches and multitarget tracking for tumors with complex motion patterns. Developed experimental validations for MRI-linac integration and MLC tracking systems Authored a textbook chapter on Adaptive Radiation Therapy (ART) Recipient of Cancer Institute NSW Early Career Fellowship (2023) Recent grants include an AI platform for targeted radiotherapy (2024) and national critical infrastructure funding for lung cancer applications (2023). Her lab collaborates on real-time dose calculation algorithms and clinical trial implementation across multiple institutions.
Dr. Chad J. Brenner is an Associate Professor in the Department of Otolaryngology-Head and Neck Surgery and Pharmacology at the University of Michigan Medical School. He also directs the U-M Program in Cellular and Molecular Biology, the Otolaryngology Clinical Laboratory (CLIA), and the Head & Neck Oncology Program. His research focuses on developing liquid biopsy tools for cancer detection and precision therapy, particularly in HPV-driven head and neck cancers. Key roles include membership in the Rogel Cancer Center, Kresge Hearing Research Institute, and Center for Computational Medicine & Bioinformatics. Education: B.S. in Biomedical Engineering, M.S. in Bioelectrical Engineering, and Ph.D. in Cellular and Molecular Biology from the University of Michigan, with doctoral work on prostate cancer mechanisms. Research Interests: HPV integration and cancer heterogeneity Urine- and blood-based liquid biopsies for real-time cancer monitoring Combination immunotherapy strategies for improving checkpoint inhibitor responses Genetic engineering to identify cancer vulnerabilities Clinical trial innovation for adaptive therapies Recent Work Highlights: Development of the MyHPVscore blood test for HPV-related head and neck cancer detection, and exploration of tumor-immune interactions through PD-L1 and T-cell profiling. Ongoing projects include PET-guided radiotherapy optimization and multi-omics analyses of tumor heterogeneity. Labs & Teams: Leads the Michigan Otolaryngology and Translational Oncology (MiOTO) lab and collaborates with interdisciplinary teams across computational medicine, immunology, and clinical oncology.
Prof Scott Crowe is a leading academic and clinical researcher in radiation oncology medical physics, affiliated with the Royal Brisbane and Women’s Hospital and the Hudson Institute of Medical Research (HBI) Cancer Care Services. His work bridges clinical practice and advanced research in radiotherapy technologies. Clinical Role: Clinical Lead for Cancer Care Services at HBI, overseeing radiation oncology medical physics. Education: Post-doctoral fellowship at Queensland University of Technology (QUT). Research Interests focus on: 3D Printing: Developing patient-specific phantoms and devices for radiotherapy applications (e.g., lung, vaginal, and oral molds). Dosimetry: Advancing measurement techniques (ionization chambers, Monte Carlo simulations) and addressing challenges like small field dose corrections, skin dose enhancement, and secondary cancer risk assessment. Adaptive Radiotherapy: Real-time motion adaptation systems, including Radixact Synchrony and TomoTherapy, to improve treatment accuracy. Quality Assurance: Statistical process control for beam energy variations, gamma evaluation methods, and machine performance checks. Publication Trends highlight his expertise in integrating 3D printing with dosimetry, optimizing adaptive radiotherapy workflows, and improving quality assurance protocols. His work spans Monte Carlo simulations , proton therapy , and image-guided radiotherapy . Supervision: Mentors higher degree research students in radiation oncology physics. Conferences: Regular presenter at international scientific meetings. Labs & Collaborations: Manages the radiation oncology medical physics research portfolio at Royal Brisbane and Women’s Hospital, collaborating with Hudson Institute on clinical translation projects.
Carla Casulo, M.D. serves as Associate Professor of Medicine and Assistant Director of Cancer Research Training and Education at the Wilmot Cancer Institute, University of Rochester Medical Center. She holds dual board certification in Hematology and Medical Oncology from the American Board of Internal Medicine. Education and Training: Medical Degree: SUNY Downstate Health Sciences University (2004) Internship & Residency: Yale New Haven Hospital, Internal Medicine (2004-2007) Chief Residency: Yale University School of Medicine Fellowship: Memorial Sloan-Kettering Cancer Center, Hematology & Oncology (2008-2011) Dr. Casulo is an internationally recognized clinician-researcher specializing in all forms of lymphoma, with particular expertise in follicular lymphoma, Hodgkin lymphoma, and young adult lymphoma. Her research focuses on precision oncology approaches using real-world datasets and clinical trials to identify risk factors, optimize treatment sequencing, and improve survival outcomes. She has pioneered work in follicular lymphoma prognostication and transformation patterns. Her publication portfolio reveals strong emphasis on lymphoma subtyping, treatment resistance mechanisms, and novel therapeutic combinations. Recent work includes investigations into venetoclax combinations, T-cell lymphoma diagnostics, and outcomes in young follicular lymphoma patients. She actively leads multiple clinical trials including phase 3 studies in Hodgkin lymphoma and novel approaches for peripheral T-cell lymphoma. Major Awards: NIH K12 Career Development Award Lymphoma Research Foundation Clinical Research Mentoring Program Scholar Arthur W. Bauman Teaching Award Multiple patient care excellence awards including ICARE Patient Centered Bronze Star Dr. Casulo serves as Chair of lymphoma sessions at major international conferences (ASH, ASCO, ICL) and is Steering Committee Member for the Women in Lymphoma Global Organization. She has mentored numerous trainees, receiving the University of Rochester mentoring award for clinical programs. Her leadership extends to directing cancer research training at Wilmot Cancer Institute.
Kimberly L. Johung, MD, PhD is an Associate Professor of Therapeutic Radiology at Yale School of Medicine, holding multiple leadership positions including Vice Chair for Education, Director of the Residency Training Program, Chief of the Gastrointestinal Radiotherapy Program, and Chief of the VA Radiotherapy Program. She practices at Smilow Cancer Hospital and provides radiation oncology services at the Veteran Affairs Connecticut Healthcare System in West Haven. Dr. Johung completed her medical education at Yale University School of Medicine (MD, 2008) and earned her PhD from Yale University (2007). Her residency training was at Yale-New Haven Hospital (2013) following an internship there in 2009. Her undergraduate degree (BA) is also from Yale University (1999). Her primary research focus centers on gastrointestinal cancers, including esophageal, gastric, pancreatic, hepatic, rectal, and anal cancers, with special expertise in stereotactic body radiotherapy (SBRT) for tumors of the chest and abdomen. She also treats lung cancer, head and neck cancer, and prostate cancer. Her research aims to define molecular markers using retrospective studies, clinical trials, and translational research to guide treatment decisions and improve outcomes for patients with gastrointestinal malignancies. She is particularly interested in integrating biology-guided radiotherapy approaches and optimizing treatment protocols through clinical trials. Analysis of Dr. Johung's recent publication record reveals a strong focus on gastrointestinal malignancies, particularly pancreatic, rectal, and esophageal cancers. Her work spans clinical guidelines development (NCCN), translational research on molecular biomarkers, technical innovations in radiotherapy delivery (including SBRT and biology-guided radiotherapy), and clinical trial design. A notable trend is her increasing involvement in multi-institutional collaborations and national guideline committees, reflecting her growing influence in the field of radiation oncology for gastrointestinal cancers. Dr. Johung is an active participant in national cancer guideline development, serving on NCCN panels for Esophageal and Gastric Cancers. Her clinical expertise has been recognized through inclusion in Yale Medicine's 'Top Doctors' lists. She is also a member of the American Society for Radiation Oncology, contributing to the advancement of the field through professional engagement. As Director of the Residency Training Program, Dr. Johung oversees the education and development of future radiation oncologists at Yale. She has led research on resident evaluation methods and faculty assessment across radiation oncology programs nationally. Her clinical trials portfolio includes studies on stereotactic body radiation therapy for oligoprogression on immune checkpoint inhibitors in metastatic renal cell carcinoma (as Principal Investigator) and participation as Sub Investigator in trials for MRI brain surveillance versus prophylactic cranial irradiation in small-cell lung cancer and dose-deescalated SBRT for centrally located lung cancer. Dr. Johung is affiliated with multiple research teams including the Center for Gastrointestinal Cancers, DNA Damage and Genome Integrity team, Gastrointestinal Radiotherapy Program, Pancreatic Diseases Program, and Prostate & Genitourinary Radiotherapy team at Yale Cancer Center. These affiliations reflect her collaborative approach to cancer research and treatment across multiple disciplines within the Yale ecosystem.
Jie Deng, Ph.D., is a Professor in the Department of Radiation Oncology at UT Southwestern Medical Center, where she serves as faculty in the Division of Medical Physics & Engineering. She is a certified MRI and MRI for radiation therapy medical physicist by the American Board of Medical Physics and holds a leadership role as a magnetic resonance safety officer. Dr. Deng is actively involved in both clinical and research aspects of medical imaging and radiotherapy, with a strong emphasis on integrating advanced imaging technologies into therapeutic workflows. Dr. Deng earned her academic degrees from prestigious institutions: a Bachelor of Science in Biomedical Engineering from Southeast University in China, a Master’s in Bioengineering from the University of Illinois at Chicago, and a Ph.D. in Biomedical Engineering from Northwestern University. She further enhanced her expertise by obtaining a Master of Science in Law from the Northwestern Pritzker School of Law, reflecting a multidisciplinary approach to her scientific work. Her research interests center on MRI physics , quantitative imaging , oncological imaging , and the application of artificial intelligence in medical imaging. She has pioneered work in MRI-guided radiation therapy, imaging biomarkers for therapeutic response, and AI-driven image reconstruction and artifact reduction. Her recent publications demonstrate a consistent focus on improving imaging accuracy, speed, and clinical utility, particularly in liver, pediatric, and oncological applications. The analysis of her 15 most recent articles reveals a strong trend toward deep learning-based image reconstruction , quantitative MRI biomarkers , and synthetic image generation for radiotherapy planning. Topics such as 4D-MRI, synthetic CT, motion artifact reduction, and AI fusion models dominate her scholarly output, indicating a forward-looking research trajectory centered on intelligent, fast, and precise imaging for personalized cancer therapy. Dr. Deng actively contributes to the scientific community through presentations at major conferences including the International Society for Magnetic Resonance in Medicine (ISMRM) and the American Association of Physics in Medicine (AAPM), where she shares innovations in MRI, adaptive radiotherapy, and AI integration. As an educator, Dr. Deng mentors medical physics residents and graduate students, delivering lectures on MR-only simulation, MR-linear accelerator practices, and medical imaging fundamentals. While no specific grants are mentioned in the text, her extensive publication record in high-impact journals suggests active research funding and collaborative projects. She is affiliated with key professional organizations and serves on UT Southwestern’s MRI Safety Committee, ensuring safe and effective use of MRI in clinical and research settings. Her work bridges the gap between engineering innovation and clinical application, making significant contributions to the field of radiation oncology and medical physics.
Dr. Brad Oborn is a Research Fellow at the School of Physics, University of Wollongong. His work focuses on advancing radiation therapy techniques, particularly in MRI-guided radiotherapy and proton therapy. He specializes in high-resolution dosimetry, magnetic field effects on radiation beams, and the integration of medical imaging with therapeutic systems. His research interests include radiation dosimetry in magnetic fields, proton beam characterization, and the development of novel detectors like the 'MagicPlates' silicon array. He collaborates on projects such as the Australian MRI-Linac Program, aiming to improve cancer treatment through real-time adaptive radiotherapy. Dr. Oborn has supervised numerous higher-degree students, focusing on topics like skin dosimetry in MRI-linacs, ion chamber response in magnetic fields, and 4D dosimetry modeling. He has secured grants from institutions like the National Health and Medical Research Council (NHMRC) and Cancer Council, supporting his work on high-resolution dosimetry and MRI-guided therapies. His publications reflect contributions to medical physics, including studies on proton dosimetry, electron streaming in MRI systems, and the clinical challenges of MRI-guided proton therapy. His work bridges fundamental physics and clinical applications, aiming to enhance precision and safety in radiation oncology.
Sara Margareta Cecilia Pilskog serves as an Associate Professor in the Department of Physics and Technology at the University of Bergen, Norway, with dual affiliation at Haukeland University Hospital's Department of Cancer Treatment and Medical Physics. Her research bridges theoretical medical physics and clinical oncology applications, focusing on precision radiotherapy techniques and biological optimization. Her primary research interests center on proton therapy innovation, where she investigates biological optimization strategies using linear energy transfer (LET) and relative biological effectiveness (RBE) modeling. She develops adaptive radiotherapy frameworks to address inter-fractional motion in pelvic cancers, particularly prostate and rectal malignancies. Her work also pioneers neutron-based in-vivo range verification systems and statistical deformation models for dose accumulation. Current projects emphasize reducing treatment margins through anatomical robustness and optimizing biological dose distributions for organ sparing. Analysis of her 15 most recent publications reveals a dominant focus on improving proton therapy precision for pelvic cancers through biological modeling and motion management. Approximately 70% of her work addresses prostate cancer applications, with significant contributions to adaptive strategies for inter-fractional changes and biological optimization techniques. Her research consistently employs Monte Carlo simulations (particularly FLUKA) and clinical data analysis to translate theoretical models into clinically viable solutions. No scientific awards were documented in the provided materials. While specific advising details remain unreported, her collaborative patterns indicate active mentorship within the University of Bergen's medical physics research ecosystem. Her publications consistently involve junior co-authors from clinical physics teams at Haukeland University Hospital, suggesting hands-on supervision of technical staff and research fellows in radiotherapy innovation projects. Grant funding appears primarily channeled through institutional hospital-university partnerships focused on clinical translation of advanced radiotherapy techniques. Dr. Pilskog operates within the University of Bergen's medical physics research cluster that maintains close operational ties to Haukeland University Hospital's radiotherapy department. This integrated academic-clinical environment enables direct implementation of her research on adaptive proton therapy and biological optimization into clinical workflows, with particular emphasis on pelvic cancer treatment protocols. The team utilizes advanced Monte Carlo simulation platforms and clinical treatment planning systems to develop and validate next-generation radiotherapy approaches.
Jing Wang, Ph.D., is a Professor of Radiation Oncology at UT Southwestern Medical Center, affiliated with the Department of Radiation Oncology’s Division of Medical Physics and Engineering. His research bridges medical imaging, machine learning, and radiation therapy optimization. B.Sc. in Material Physics, University of Science and Technology of China M.A. and Ph.D. in Physics, Stony Brook University Postdoctoral training in Radiology (Stony Brook) and Radiation Physics (Stanford) Dr. Wang’s work focuses on enhancing medical imaging quality for quantitative applications in image-guided radiation therapy (IGRT) and adaptive radiation therapy (ART) . Key areas include CT/MRI/PET reconstruction , deep learning for tumor localization , and radiomics-based survival prediction . His AIRT Lab develops AI algorithms for treatment outcome modeling and real-time imaging. Recent publications highlight advancements in transformer networks for anatomy prediction, uncertainty-aware segmentation , and delta radiomics for surgical margin analysis. Journals span Medical Physics , Physics in Medicine and Biology , and International Journal of Radiation Oncology .
Sinead O'Keeffe is a Research Fellow at the University of Limerick in the Faculty of Science and Engineering , specifically within the Department of Electronic and Computer Engineering . Her research bridges the technical domain of optical fiber sensor development with critical applications in radiation therapy and sports medicine. Primary Research Themes Medical radiation dosimetry using optical fiber sensors Brachytherapy dose monitoring systems Sports injury prevention in Gaelic football and running Mental health literacy in rural farming communities Key Technical Contributions Development of scintillation-based dosimeters Characterization of perfluorinated polymer fibers 3D printed sensor systems for clinical and rehabilitation applications Interdisciplinary Applications Prostate cancer radiotherapy dose measurement Mental health intervention programs for athletes Work-family conflict analysis in Irish farming Email: sinead.okeeffe@ul.ie
Fuad Abujarad is an Associate Professor of Emergency Medicine and Biostatistics at the Yale School of Public Health . His interdisciplinary research bridges Digital Health , Gerontechnology , and Health Informatics to address critical gaps in elder mistreatment detection and informed consent processes. PhD in Computer Science from Michigan State University (2010) MSc in Computer Science from Michigan State University (2005) His work focuses on developing Virtual cOaching in making Informed Choices on Elder Mistreatment Self-Disclosure (VOICES) – an NIH/NIA-funded digital screening tool for elder abuse – and Virtual Multimedia Interactive Informed Consent (VIC) , an AHRQ-funded mHealth solution to enhance patient comprehension. Additional projects span Personal Care Aides (PCA) workforce strengthening and Health Information Technology systems for abuse prevention. Recent publications highlight applications of his tools in dementia care , emergency departments , and primary care settings . Key trends include digital risk assessment , multimodal patient education , and fault-tolerant software design for healthcare systems. Merit of Achievements (2006) from Yale University Fulbright Fellowship (2004) Dr. Abujarad leads grants from NIA , AHRQ , CMS , RWJF , and National Institutes of Health . His lab collaborates with Michigan State University and Yale Cancer Center , emphasizing patient-centered design and real-time background check systems for long-term care worker vetting.
Professor Annette Haworth is a distinguished academic at the University of Sydney, serving as Director of the Institute of Medical Physics and Course Director for the Master of Medical Physics program. She holds conjoint roles at Westmead and Blacktown Hospitals in radiation oncology medical physics. With over 25 years of clinical experience, her work bridges medical physics, radiation oncology, and AI-driven treatment optimization. Her research focuses on biologically targeted radiation therapy, particularly prostate cancer, using advanced imaging biomarkers and AI to customize dose delivery. She leads the BiRT project ( https://birt.sydney.edu.au/ ), which develops imaging biomarkers for tumor characterization and biological treatment planning across multiple cancer sites. PhD, University of Western Australia MSc, University of Western Australia BSc(Hons), University of Leeds Her recent publications (2023-2025) explore heterogeneous dose prescriptions, radiomic stability, and AI-enhanced segmentation for radiotherapy. Key trends include integrating quantitative MRI, PET imaging, and machine learning to personalize radiation doses while minimizing healthy tissue exposure. Scientific awards: 2021 University of Sydney DVCR Cancer Gift 2015 Judith Stitt Award (American Brachytherapy Society) 2007 TROG Outstanding Achievement Award Life Member, TROG (2018) Fellow, Australasian College of Physical Scientists in Medicine Prof Haworth supervises a multidisciplinary team of physicists, computer scientists, and clinicians, with active PhD students at the University of Sydney, Auckland, and Western Australia. She has secured competitive grants, including an NHMRC project grant (2016) for BiRT development and PdCCRS funding (2010-2014) for prostate cancer bioeffect models.
