Prof. Jin-Song von Storch | Computational Materials Science | Research Excellence Award

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Prof. Jin-Song von Storch | Computational Materials Science | Research Excellence Award

Max-Planck Institute for Meteorology | Germany

Prof. Jin-Song von Storch is a distinguished scientist in computational materials science whose interdisciplinary expertise bridges advanced numerical modeling, statistical physics, and large-scale system simulation. She is widely recognized for her leadership in developing high-resolution computational frameworks that reveal complex interactions between structure, dynamics, and emergent properties in material and physical systems. As a senior researcher and academic leader, she has made foundational contributions to multiscale modeling, stochastic processes, and data-driven approaches that enhance predictive accuracy in complex systems. Her work is characterized by methodological rigor, conceptual clarity, and a strong emphasis on translating theoretical insight into robust computational tools. Prof. von Storch has played a central role in collaborative international research initiatives, where her ability to integrate mathematics, physics, and computation has driven innovation across disciplinary boundaries. In addition to her research excellence, she is deeply committed to academic mentorship, guiding doctoral and postdoctoral researchers while fostering inclusive and intellectually vibrant research environments. She has held key editorial, advisory, and governance roles within major scientific programs, reflecting the high level of trust placed in her expertise and judgment by the global research community. Her scholarly output includes influential journal articles, book contributions, and invited works that continue to shape contemporary thinking in computational and theoretical science. Through sustained scientific leadership, original research vision, and dedication to knowledge advancement, Prof. Jin-Song von Storch exemplifies the qualities recognized by the Research Excellence Award and stands as a leading figure in computational science and interdisciplinary innovation.

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Featured Publications


Principles of Equilibrium Fluctuations

– Physica A: Statistical Mechanics and Its Applications, 2026 (Open Access)

Randomness and Integral Forcing

– Tellus Series A: Dynamic Meteorology and Oceanography, 2024 (Open Access)

Mr. Zhaoli Su | Computational Materials Science | Best Researcher Award

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Mr. Zhaoli Su | Computational Materials Science | Best Researcher Award

Mr. Zhaoli Su is a Ph.D. candidate at the Beijing Institute of Technology, specializing in Optoelectronic Information Engineering with a focused application in medical multimodal artificial intelligence. His research bridges deep learning, radiology, and clinical decision support systems to develop intelligent diagnostic tools. With active involvement in medical image-text fusion and language model applications, Mr. Su’s academic pathway reflects innovation in healthcare AI. His early career shows promise in aligning technological advancement with medical utility.

Mr. Zhaoli Su | Beijing Institute of Technology | China

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Education

Mr. Su is currently pursuing a Ph.D. in Optoelectronic Information Engineering. His academic training covers medical imaging, machine learning, and natural language processing, forming a robust foundation for intelligent healthcare systems development. Throughout his doctoral program, he has engaged in cutting-edge research that integrates clinical data with AI algorithms to solve diagnostic challenges in radiology.

Experience

His research experience includes developing advanced diagnostic systems by integrating medical image processing and large language models. He has contributed to projects involving radiology report generation and modeling disease progression using longitudinal imaging data. Through interdisciplinary collaboration, he applies deep learning techniques to improve the accuracy and efficiency of clinical decision-making. His work reflects a strong commitment to advancing intelligent healthcare technologies through AI innovation and applied research in medical informatics.

Contributions

Mr. Zhaoli Su’s research focuses on the advancement of intelligent systems for medical imaging analysis, with particular emphasis on multimodal data fusion, disease diagnosis, and radiology report generation. Utilizing large-scale clinical datasets and cutting-edge artificial intelligence models, he has developed automated tools that improve diagnostic precision and clinical workflow efficiency. His work is characterized by a strong interdisciplinary approach that combines optoelectronic engineering and healthcare technology. By addressing real-world clinical challenges through innovative AI applications, his contributions pave the way for more accurate, accessible, and scalable diagnostic support systems in modern medicine.

Research Focus

Mr. Su’s primary research areas include Medical Multimodal AI, Radiology Report Generation, and Clinical Decision Support Systems. He works on integrating textual and imaging data using deep learning to improve interpretability and accuracy in clinical diagnostics. His emphasis on modeling disease progression and developing tools for real-time clinical use makes his work valuable in advancing AI-powered healthcare solutions.

Publications

MedKit: Multi-level Feature Distillation with Knowledge Injection for Radiology Report Generation
Authors: Zhaoli Su, Hong Song, Yucong Lin, You Wu, Xutao Weng, Zhongxuan Mao, Bowen Liu, Hongxia Yin, Jian Yang
Journal: Expert Systems with Applications

PRTA: Joint Extraction of Medical Nested Entities and Overlapping Relation via Parameter Sharing Progressive Recognition and Targeted Assignment Decoding Scheme
Authors: Bowen Liu, Hong Song, Yucong Lin, Xutao Weng, Zhaoli Su, Xinyan Zhao, Jian Yang
Journal: Computers in Biology and Medicine

Conclusion

Mr. Zhaoli Su demonstrates strong research potential in the intersection of artificial intelligence and medical imaging. His early contributions to radiology report generation and clinical AI systems are promising and well-aligned with healthcare innovation. He is a fitting candidate for emerging research recognition, particularly the Best Research Scholar Award, and with continued scholarly growth, will be well-positioned for future recognition as a leading researcher in the field.

Mr. Dae Hyeob Yoon | Materials Science | Best Researcher Award

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Mr. Dae Hyeob Yoon | Materials Science | Best Researcher Award

Mr. Dae Hyeob Yoon is currently an undergraduate researcher in Mechanical Engineering at Chungbuk National University (CBNU), South Korea. His research interests lie in micro/nanotechnology, sensors, and MEMS. Despite being at an early stage in his academic career, he has already contributed to a peer-reviewed publication in Applied Sciences and participated in nationally recognized research programs. His early engagement in advanced materials research and active academic presentation record demonstrate a deep commitment to scientific inquiry.

Mr. Dae Hyeob Yoon | Chungbuk National University (CBNU) | South Korea

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Mr. Yoon is pursuing a Bachelor of Science in Mechanical Engineering at CBNU. Alongside his coursework, he has been actively involved in undergraduate research initiatives, including the Undergraduate Research Opportunities Program (UROP). His academic training has allowed him to integrate theoretical knowledge with experimental design and fabrication techniques related to flexible electronics and nanomaterials.

Research Experience 

As an undergraduate, Mr. Yoon has contributed to one completed research project involving the development of a flexible and conductive heating membrane. He has presented his work at the Korean Society of Mechanical Engineers (KSME) and will present at the EKC conference in Austria. His publication demonstrates competency in research design, experimental methodology, and technical writing, marking significant early-career achievements.

Contributions

Mr. Dae Hyeob Yoon’s research is focused on developing flexible heating technologies for use in wearable electronics and smart textiles. His current work involves creating a scalable, low-voltage, and mechanically stable heating platform using advanced materials and fabrication techniques. This research addresses major limitations in existing flexible heaters, such as fragility and high energy demands. The technology he is advancing has significant potential for integration into next-generation wearable devices, enabling personalized and adaptive applications in health, fitness, and smart clothing systems. His innovative approach contributes meaningfully to the field of flexible, functional electronics.

Research Focus 

Mr. Yoon’s primary research focus is on the application of micro and nanotechnology to develop scalable and efficient platforms for wearable and flexible electronics. His current work addresses key challenges in mechanical stability and power efficiency, contributing to emerging markets in personalized technology and smart textiles. His interdisciplinary interest bridges mechanical engineering with material science and electronics.

Publication

Development of a Flexible and Conductive Heating Membrane via BSA-Assisted Electroless Plating on Electrospun PVDF-HFP Nanofibers

Author: Dae Hyeob Yoon

Conclusion

Mr. Dae Hyeob Yoon is a motivated and talented early-stage researcher whose contribution to nanofiber-based heating technologies is noteworthy. His research potential is clear, and with continued academic development and broader engagement in scientific activities, he has the capacity to evolve into a strong candidate for high-level research awards. At this time, he would be better suited for young researcher or emerging researcher recognition, while continuing to build toward Best Researcher status in the future.

Dr Maryam Mirfatah | Computational Materials Science | Best Researcher Award

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Dr Maryam Mirfatah | Computational Materials Science | Best Researcher Award

Dr. Maryam Mirfatah 🎓 is a macroeconomist with expertise in monetary policy, exchange rate regimes, and DSGE modeling. She earned her Ph.D. in Economics from Yazd University and has held research positions at leading institutions like the London School of Economics, King’s College London, and currently, Banco de Portugal 🇵🇹. Her work blends empirical policy analysis 📊 with applied macroeconomics, publishing in top journals like Economic Modelling. A UK HEA Fellow 👩‍🏫, she actively contributes to global economic dialogues 🌍 through collaborations and international conferences. Dr. Mirfatah’s research supports sustainable, evidence-based policymaking across diverse economies. 📈📚💡

Dr Maryam Mirfatah, King’s College London, United Kingdom

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🎓 Education

Dr. Maryam Mirfatah holds a Ph.D. in Economics (2019) from Yazd University, Iran, with a thesis focused on “Money Growth Rules in Emerging Economies” 📈🌍. She earned her M.Sc. in Economics (2011) from Azad University of Isfahan and a B.Sc. in Statistics (2006) from Isfahan University of Technology 📊📘. Committed to teaching excellence, she completed a Graduate Certificate in Learning and Teaching (2020) at the University of Surrey, earning Fellowship of the Higher Education Academy (FHEA) 👩‍🏫🌟. Additionally, she participated in the prestigious GTA Workshop at the London School of Economics in 2024 🎓🇬🇧.

🏛️ Experience

Dr. Maryam Mirfatah is a highly accomplished economist with over 15 years of professional experience in academic, policy, and industry roles 🌍📊. She currently serves as a Research Fellow at Banco de Portugal 🏛️ and a Visiting Fellow at King’s Business School, London, focusing on macroeconomic policy and global financial spillovers. Her academic roles span King’s College London, LSE, and City University of London, where she teaches macroeconomics, econometrics, DSGE modeling, and policy design 🎓📈. She also has corporate experience in financial risk analysis and feasibility studies in Iran’s steel and mining sectors 🏗️💼, blending technical expertise with real-world economic application.

🌍 Presentation

Dr. Maryam Mirfatah has actively contributed to prestigious international economic conferences 🌍📈. From 2019 to 2025, she presented at events such as the CEBRA Annual Meeting 🇩🇪, Southern Economic Association® Meetings 🇺🇸, Money Macro and Finance Society Conferences 🇬🇧, and Computing in Economics and Finance Conferences 🇫🇷🇨🇦. Her insights have been showcased at T2M at CREST, France (2025) and India’s ISI Growth Conference (2021) 🇮🇳. Dr. Mirfatah’s work bridges macroeconomics, finance, and computational modeling, earning global recognition and fostering interdisciplinary academic dialogue 📊💡🤝. Her frequent invitations reflect her influence in modern economic theory and policy research.

🔍 Research Focus

Dr. Maryam Mirfatah’s research bridges monetary economics and international macroeconomics with a forward-looking lens on climate change and energy transition 🌱⚡. Her interests span monetary and fiscal policy, open economy macroeconomics, and macro-financial stability 💼🏦. She delves into the interplay between macroprudential frameworks and global economic shocks, analyzing how policies can foster resilience in volatile financial systems 📉🛡️. Her work is crucial in shaping economic strategies that align sustainability with stability, offering insights into managing cross-border financial risks and driving green economic transformation for a more balanced and future-ready world 🌐🌿.

📚 Publications

LAMP, Informality and Monetary Growth Rules in an Emerging Economy
Authors: M. Mirfatah, V.J. Gabriel, P. Levine
Journal: Economic Modelling (2025)
Explores macroeconomic policy and informal sector dynamics in emerging markets.

Optimal Liquidity Provision and Interest Rate Rules: A Tale of Two Frictions
Authors: P. Levine, M. Mirfatah, J. Pearlman, S. Tsiaras
Journal: School of Economics Discussion Papers (2023)
Investigates interest rate policy under market frictions in a DSGE framework.

Monetary Growth Rules in an Emerging Open Economy
Authors: M. Mirfatah, V.J. Gabriel, P. Levine
Journal: School of Economics Discussion Papers (2020)
Focuses on monetary rule design in economies with exchange rate volatility.

Imperfect Exchange Rate Pass-through: Empirical Evidence and Monetary Policy Implications
Authors: V. Gabriel, P. Levine, M. Mirfatah, J. Swarbrick
Year: 2019
Empirical study analyzing how exchange rate fluctuations impact domestic prices.

Analysis of the Impact of Good Governance on the Non-Oil Export of Oil Exporting Countries
Authors: H. Sharifi-Renani, H. Mollaesmaeili-Dehshiri, M. Mirfatah
Journal: Journal of Economic Policy and Research 8(1), 1–10 (2013)
Early work examining governance and diversification in oil-dependent economies.

Mr Sina Soltani | Computational Materials Science | Best Researcher Award

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Mr Sina Soltani | Computational Materials Science | Best Researcher Award

Sina Soltani is a skilled Instrumentation Engineer at Honeywell UOP, Rosemont, IL, USA, with a strong academic foundation in electrical and control engineering 🎓⚙️. He earned his B.S. and M.S. degrees from Shiraz University, Iran, in 2011 and 2013, respectively. His expertise spans estimation theory, nonlinear systems, adaptive control, signal processing, and intelligent data mining techniques 🧠📊🔧. With a deep interest in innovative industrial automation and smart system integration, he combines practical engineering with advanced control strategies to enhance system reliability and efficiency 🛠️💡📈. He continues to contribute to next-generation engineering solutions globally 🌍🔬.

Mr Sina Soltani, Honeywell UOP, United States

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🎓 Education

 Sina Soltani earned his M.Sc. in Control and Power Engineering from Shiraz University in 2014 🎓⚡ and a B.Sc. in Electrical and Computer Engineering from Shiraz University of Technology in 2012 💡🔌. He also holds a High School Diploma from Naserian High School, completed in 2005 🏫📘. His academic path is further strengthened by a range of professional certifications in PLC programming (TIA Portal, S7-400H), industrial networks (Profibus, Modbus, Ethernet), and electrical safety (ATEX, ISO 9001) 🧠📈⚙️. This blend of formal education and applied training equips him with strong expertise in automation and instrumentation engineering 🔍🔧.

📏 Experience 

Sina Soltani has over a decade of experience in instrumentation, automation, and control engineering ⚙️🔧. At Honeywell UOP 🇺🇸, he leads instrumentation system design and integration for industrial applications. Previously, he served as a senior engineer at Neyriz Ghadir Steel Complex 🇮🇷, focusing on fire & gas systems, PLC/DCS programming, and calibration 🎛️💡. At Piramoon Pardazesh Qeshm, he specialized in radioactive measurement systems and technical documentation 📊📐. He also held roles as a chief electrical engineer at PetroAzma and as a university lecturer 📚🧠. His expertise spans sensors, analyzers, motors, safety systems, and advanced process control 🌍🔍.

🛠️ Technical Skills 

Sina Soltani possesses a robust technical skill set in Instrumentation Engineering, Control Systems, Automation, and Calibration 🧪⚙️📏. He is proficient in configuring and maintaining advanced industrial instruments, including flowmeters, analyzers, and control valves 🔄🔍. With deep knowledge of PLC/DCS systems, loop tuning, and process optimization, he excels at designing and integrating control strategies for complex operations 💻🔧. His expertise includes working with safety standards (NEC, IEC) and executing diagnostics and root-cause analysis for system failures 🚨🛠️. These capabilities make him a valuable asset in driving innovation and operational excellence across modern industrial environments 🌐🏭.

🏆 Achievement 

On May 22, 2024, Sina Soltani was honored with the Top Researcher Award at Neyriz Ghadir Steel Complex, Shiraz, Iran, for his exceptional contributions to Instrumentation and Automation Engineering 🛠️📡. His innovative work in process control systems, real-time signal integration, calibration technologies, and automation reliability set a benchmark in industrial engineering ⚙️📊. This distinction reflects his impact on system accuracy, safety enhancements, and advanced control methodologies 📈🔍. Recognized for combining deep technical expertise with practical problem-solving, he continues to lead advancements in instrumentation for critical infrastructure and manufacturing environments 🌍🔬.

🔬 Research Focus 

Sina Soltani’s research is centered on advanced control systems, signal processing, and intelligent estimation methods for industrial applications 🧠📉⚙️. His recent work includes the application of autoregressive Kalman filters for gamma level measurement and well-log data estimation 🔬📡, as well as the development of fuzzy logic and iterative learning-based control algorithms for instrument air units and harmonic mitigation ⚡🔁. He also explores high-efficiency modeling of electrical machines using subdomain techniques and smart controllers for distributed energy systems ⚙️🔋🌍. His interdisciplinary focus bridges control theory, automation, and real-time optimization in complex engineering systems 🛠️📊🤖.

📚 Publications

Advances in Gamma Level Measurement by Optimal Autoregressive Kalman Filter

Author: S. Soltani
Conference: 2024 20th CSI International Symposium on Artificial Intelligence and Signal Processing

Designing and Implementing an Algorithm Based on an Autoregressive Kalman Filter to Estimate Well-Log Data

Author: S. Soltani
Conference: 2023 9th International Conference on Control, Instrumentation and Automation (ICCIA)

Introducing an Improved Control Method for Instrument Air Unit Based on Fuzzy and Iterative Learning Control

Author: S. Soltani
Journal: ISA Transactions (2025)

An Analytic 2D Subdomain Model for Slotless Electrical Machines with Internal Arc/Cubic Shape Permanent Magnets

Authors: M. Pourahmadi-Nakhli, M.J.K. SeyedHassanDaryanavard, S. Soltani
Journal: Intelligence 1(1), 13–23 (2025)

Fast Subdomain Approximation of Brushless Electrical Machines with Spoke-Hub Permanent Magnets

Authors: M. Pourahmadi-Nakhli, S.H. Daryanavard, M. Jokar-Kohanjani, S. Soltani
Conference: 2024 32nd International Conference on Electrical Engineering (ICEE)

A Novel Fuzzy Type-2 PI Repetitive Control Methodology for Harmonic Elimination in Distributed Generation Sources

Authors: S. Soltani, M. Rayat
Conference: 2024 9th International Conference on Technology and Energy Management (ICTEM)

Mrs Charoula Iliaskou | Materials Science | Best Researcher Award

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Mrs Charoula Iliaskou | Materials Science | Best Researcher Award

Mrs. Charoula Iliaskou is a medical physicist and researcher at the University Medical Center Freiburg 🇩🇪, specializing in intraoperative electron beam radiation therapy (IOERT) ⚡🏥. She holds an MSc in Medical Physics from the National and Kapodistrian University of Athens 🇬🇷, graduating top of her class 🎓. Her research explores targeted dosimetry, radiation planning, and magnetic nanoparticles for hyperthermia therapy 🧲🧪. Skilled in Monte Carlo simulations, clinical software, and nanomaterials analysis, she integrates theory with real-world clinical application 🔬💻. Charoula’s work contributes to more precise, effective cancer therapies and positions her as a promising figure in radiation oncology research 🌍📈.

Mrs Charoula Iliaskou, University Medical Center Freiburg, Germany

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Education 🎓

Mrs. Charoula Iliaskou holds an MSc in Medical Physics – Radiation Physics from the National and Kapodistrian University of Athens (2020), where she graduated top of her class (Rank 1/19, Grade 9.14/10) 🎓🏅. She earned her BSc in Physics from Aristotle University of Thessaloniki in 2018 (Rank 2/23, Grade 8.18/10) 📘🔬. In 2017, she participated in the Erasmus+ program at the University of Duisburg-Essen, Germany, gaining international academic experience 🌍📖. Her academic journey began with an excellent high school diploma from Xanthi, Greece (Grade 18.9/20) 🏫📐, demonstrating consistent excellence in science and education.

Experience 👩‍🔬

Mrs. Charoula Iliaskou is currently a Physicist in the Division of Medical Physics at the University Medical Center Freiburg 🇩🇪, where she develops image-guided planning and verification workflows for IOERT (Intraoperative Electron Beam Radiation Therapy) 🏥⚡. Her MSc research focused on in vivo dosimetry for breast cancer using EBT3 Gafchromic films 🎯🧪. She has hands-on training in radiation treatment planning and quality assurance from AHEPA Hospital and early research experience in nanoparticle hyperthermia and magnetometry 🧲🔬. Her work combines clinical physics with nanoscale science, showing deep engagement from student researcher to applied medical physicist 👩‍🔬📈.

Honors and Awards 🏅

Mrs. Charoula Iliaskou was honored with the “Best Undergraduate Student Internship of the Physics Department for the year 2017–2018” 🏅 by the Aristotle University of Thessaloniki, Greece 🇬🇷. This award recognized her outstanding performance, commitment, and research initiative during her clinical internship in radiation oncology and medical physics 🏥🔬. It reflects her early dedication to academic and professional excellence, as well as her ability to integrate theoretical knowledge into practical medical applications 🎓⚙️. This recognition served as a launching point for her future achievements in medical physics, marking her as an emerging talent in the field 🌟.

Skills

Mrs. Charoula Iliaskou brings a powerful set of scientific and technical skills to her research in medical physics 🧪. Her expertise includes radiation dosimetry, magnetic nanoparticle characterization (VSM, SQUID), X-ray diffraction, SEM-TEM imaging, and Monte Carlo simulations 🔬📊. She is proficient in tools such as MATLAB, SPSS, EGSnrc, ImageJ, and clinical planning systems like ECLIPSE and RADIANCE 💻🧠. Charoula is multilingual—fluent in Greek, English, Spanish, and German 🗣️—and excels in teamwork, leadership, communication, and project management 🤝📅. Her skillset bridges computational analysis, clinical application, and experimental research, making her a highly versatile scientist.

Research Focus 🔬

Mrs. Charoula Iliaskou focuses her research on medical and radiation physics, particularly on intraoperative electron beam radiation therapy (IOERT) and targeted dosimetry techniques for cancer treatment ⚛️🏥. Her interests span the development of image-guided planning workflows, Monte Carlo simulations, and nanoparticle-based hyperthermia therapies 🧲🔬. She combines advanced analytical tools like radiation dosimetry, X-ray diffraction, and SEM-TEM imaging with clinical software such as ECLIPSE and RADIANCE 💻📊. With interdisciplinary expertise bridging nanotechnology, oncology, and statistical modeling, her research aims to improve precision and outcomes in radiation oncology and cancer therapy 🌍📈.

Publications 📚

Minimum and optimal requirements for a safe clinical implementation of ultra-high dose rate radiotherapy: A focus on patient’s safety and radiation protection
✍️ Authors: C. Garibaldi, S. Beddar, N. Bizzocchi, T.T. Böhlen, C. Iliaskou, R. Moeckli, …
📚 Journal: Radiotherapy and Oncology, Vol. 196, 110291 (2024)
🛡️ Theme: Radiation safety, FLASH radiotherapy, clinical implementation

 Ex-vivo evaluation of magnetite magnetic nanoparticles as magnetic hyperthermia carriers
✍️ Authors: N. Maniotis, E. Myrovali, Z. Kalpaxidou, C. Iliaskou, M. Angelakeris, …
📚 Conference: 2018 EMF-Med 1st World Conference on Biomedical Applications of Electromagnetic Fields
🧲 Theme: Magnetic nanoparticles, hyperthermia therapy, biomedical applications

Evaluation of RADIANCE Monte Carlo algorithm for treatment planning in electron based Intraoperative Radiotherapy (IOERT)
✍️ Authors: C. Iliaskou, G. Rossi, I. Sachpazidis, V. Boronikolas, M. Gainey, D. Baltas
📚 Journal: Zeitschrift für Medizinische Physik, 2024
🧮 Theme: Monte Carlo simulation, IOERT, treatment planning systems

Development of a TLD-100 based setup for in vivo dosimetry in Intraoperative Electron Beam Radiation Therapy (IOERT): An experimental and clinical evaluation
✍️ Authors: C. Iliaskou, M. Gainey, B. Thomann, M. Kollefrath, R. Saum, E. Gkika, …
📚 Journal: Zeitschrift für Medizinische Physik, 2025
📏 Theme: In vivo dosimetry, TLD-100, intraoperative radiation

PS02.29 Clinical Evaluation of a TLD-Based In-Vivo Dosimetry Workflow in Pancreatic Intraoperative Electron Beam Radiation Therapy (IOERT): One Case Report Study
✍️ Authors: C. Iliaskou, M. Gainey, M. Kollefrath, E. Gkika, U. Wittel, D. Ruess, A.L. Grosu, …
📚 Conference/Journal: Case study presentation, clinical physics context
🩺 Theme: Clinical evaluation, pancreatic cancer, IOERT workflow