Friedrich Jung | Radiology | Best Researcher Award

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Prof. Dr. Friedrich Jung | Radiology | Best Researcher Award

Brandenburg Technical University | Germany

Professor Dr. Friedrich Jung is a distinguished biomedical scientist renowned for his pioneering contributions to molecular cell biology, biomaterials, and clinical hemorheology. He has built an illustrious career across leading German research institutions, serving in key academic and leadership roles, including as Director of the Institute for Heart and Circulation Research in Dresden and Head of the Department of Biointerface Engineering at the Berlin Brandenburg Center for Regenerative Therapies. With a strong academic foundation in physical and biomedical engineering from RWTH Aachen and Saarland University, he has significantly advanced the understanding of cell–material interactions and blood–biomaterial compatibility. His research interests encompass biomaterial development, molecular mechanisms of vascular responses, regenerative medicine, and translational biotechnologies aimed at improving clinical outcomes. Highly skilled in experimental cell biology, biointerface engineering, and quality management in biomedical systems, he has authored hundreds of peer-reviewed publications, book chapters, and scientific volumes. Professor Jung’s achievements have been recognised with prestigious honours such as the Robin Fahraeus, Otfried-Müller, and Oskar Orth Awards, and he has held leadership positions in European scientific societies. A visionary scholar and mentor, he continues to inspire innovation in biomedical science, bridging engineering and medicine for the advancement of human health and regenerative therapies.

Profile: Scopus

Featured Publications

Manijeh Beigi | Medical Physics | Best Researcher Award

Published on by Cognitive Scientist Awards

Dr. Manijeh Beigi | Medical Physics | Best Researcher Award

Dr. Manijeh Beigi is an Assistant Professor in the Radiation Oncology Department at Iran University of Medical Sciences. She specializes in dosimetry, radiotherapy treatment planning, and quality audits, with a focus on using machine learning for radiomics and dosiomics analysis. Dr. Beigi earned her Ph.D. in Medical Physics from Tehran University of Medical Sciences in 2018, where she researched the application of Diffusion Tensor Imaging (DTI) in radiotherapy planning. With over a decade of experience in radiotherapy physics, she has worked in multiple hospitals, including Imam Hosein, Haft-e-Tir, and Pardis Niloo Cancer Center. She is actively involved in research on predicting radiotherapy toxicity and advanced MR imaging applications. Dr. Beigi has mentored numerous students, contributed to high-impact journals, and presented at international conferences. Her research aims to enhance radiotherapy precision and patient safety through cutting-edge imaging and AI-driven models. 🎓🔬

Profile

Education 🎓

Dr. Manijeh Beigi holds a Ph.D. in Medical Physics (2018) from Tehran University of Medical Sciences, where she developed automated clinical target volume determination for glioma treatment using multiparametric MRI. She completed her M.Sc. in Medical Physics (2010) at Tarbiat Modares University, focusing on radiotherapy dosimetry and quality audits in Varian linear accelerators. Her coursework covered key topics such as radiotherapy physics, radiobiology, MRI, CT, and PET physics, statistical methods, and treatment planning. Throughout her academic journey, she has specialized in advanced imaging techniques, radiomics, and AI-based predictive modeling for radiotherapy applications. Dr. Beigi’s education has provided her with strong expertise in medical physics, treatment planning optimization, and quality assurance, positioning her as a leader in radiation oncology research and innovation. 📚

Experience 👨‍🏫

Dr. Manijeh Beigi has been an Assistant Professor at Iran University of Medical Sciences since 2020, where she focuses on radiotherapy physics, treatment planning, and quality assurance. Previously, she worked as a Radiotherapy Physicist at Imam Hosein Hospital (2010-2016), Haft-e-Tir Hospital (2016-Present), and Pardis Niloo Cancer Center (2019-2021), specializing in 3D conformal radiotherapy, IMRT planning, machine QA, and dosimetry. She was also a Research Assistant (2012-2018) at Tehran University of Medical Sciences, collaborating on quantitative MRI and spectroscopy research. Dr. Beigi has significant experience in mentoring students, managing research projects, and implementing AI-driven radiotherapy solutions. Her work integrates imaging and machine learning to optimize treatment efficacy and minimize patient toxicity. 💼🔬

Research Interests 🔬

Dr. Manijeh Beigi’s research centers on dosimetry, radiotherapy quality audits, and the application of machine learning in radiomics and dosiomics. She explores AI-driven models to predict radiotherapy toxicity and optimize treatment planning. Her work integrates advanced MRI techniques, such as Diffusion Tensor Imaging (DTI), to enhance clinical target volume delineation for gliomas and other cancers. She investigates imaging biomarkers to assess radiation-induced damage and improve treatment precision. Additionally, Dr. Beigi is actively involved in multi-disciplinary research collaborations, utilizing deep learning for medical image analysis. Her contributions aim to advance radiation oncology by improving accuracy, reducing side effects, and personalizing treatment plans. 🧬📡

Dr. Manijeh Beigi has received several accolades for her contributions to medical physics and radiotherapy research. She has been recognized for her work in AI-driven radiomics and dosiomics at international conferences, including ESTRO and AAPM. Her research on glioma segmentation using DTI and radiotherapy toxicity prediction has been published in top-tier journals. She has also been awarded grants for her studies on advanced MRI applications in radiotherapy planning. Additionally, Dr. Beigi has played a key role in multi-institutional research collaborations, earning recognition for her leadership in medical imaging and quality assurance. 🏆🎖️

Publications 📚