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Stefan Michalik is a Beamline Scientist at Diamond Light Source, UK, working on the I12 beamline since 2018. He joined Diamond in 2015 as a Postdoctoral Research Associate after research roles at the Institute of Physics ASCR in Prague (2013-2015) and Pavol Jozef Šafárik University in Košice (2012). He earned his PhD in Condensed Matter Physics from Pavol Jozef Šafárik University in Košice in 2011. His research centers on structural studies of disordered systems, particularly metallic glasses, using synchrotron and neutron scattering combined with Reverse Monte Carlo simulations. Expertise includes X-ray pair distribution functions, in situ devitrification studies, powder diffraction, and computational modeling of atomic structures. Recent publications demonstrate interdisciplinary work in metallurgy, glass science, and environmental applications, employing advanced X-ray techniques to analyze microstructure evolution and develop novel materials for industrial and ecological uses. As part of the I12 beamline (JEEP) team at Diamond, he supports high-energy X-ray imaging and microtomography for engineering, environmental, and materials science research.

• Condensed Matter Physics
• Materials Science
• Glass Science
• +3 more

Nicolás Vila Blanco is an Associate Professor at the University of Santiago de Compostela (USC), Spain, conducting research through CiTIUS (Centro de Investigación en Tecnoloxías da Información e as Comunicacións). His academic journey includes a PhD in Information Technology from USC and the University of Coruña (2022), an M.Sc. in Data Science and Computer Engineering from the University of Granada, and a B.Sc. in Computer Science from the University of Vigo. Dr. Vila Blanco's research focuses on medical image processing using Deep Learning techniques, with particular expertise in dental panoramic radiograph analysis, age and sex estimation, oral microbiome research, and medical imaging applications for conditions like COVID-19. His work bridges computer science and clinical dentistry/medicine, developing practical tools that address real clinical challenges. His publication record demonstrates consistent output in high-impact journals and conferences, with numerous Q1 publications across medical imaging, dentistry, and bioinformatics fields. His research shows a clear trajectory from theoretical AI development to practical clinical implementation, with emphasis on tools that can be readily adopted in medical practice. Dr. Vila Blanco has developed several important research tools including DenTiUS Deep Plaque software for automated dental plaque quantification, IDALib for efficient image data augmentation, and has contributed to PrimerEvalPy for microbiome primer evaluation. His clinical research has produced evidence on antimicrobial efficacy, dental plaque analysis methods, and diagnostic systems with real-world applicability. His collaborative approach is evident in his numerous co-authored publications spanning dentistry, microbiology, cardiology, and computer science departments. This interdisciplinary work positions him as a bridge between technical AI development and clinical healthcare applications.

• Medical image processing
• Deep Learning
• Computer Vision
• +5 more

Raphaël Mercier serves as Research Professor and head of the Department of Chromosome Biology at the Max Planck Institute for Plant Breeding Research (MPIPZ) in Cologne, Germany. His department investigates fundamental mechanisms of genetic transmission and modification across generations, with primary focus on meiosis and meiotic recombination in plants. His research spans: Molecular control of meiotic crossover formation and interference Synthetic apomixis engineering for clonal seed propagation Conservation of chromosome dynamics from plants to humans Chiasma distribution and heterochiasmy regulation Integration of chromosome biology with agricultural applications Analysis of his 2009-2023 publications reveals consistent innovation in manipulating plant reproductive systems, highlighted by breakthroughs in synthetic apomixis (Nature 2019, Nature Communications 2022) that enable clonal propagation of hybrid crops. His work bridges fundamental chromosome mechanics with practical breeding solutions, predominantly using Arabidopsis and rice models. As department head at MPIPZ, he leverages institute-wide resources including the Plant Metabolism and Metabolomics Facility and Imaging Platform. His publication record in premier journals (Science, Nature, PNAS) demonstrates sustained leadership in plant chromosome biology, though specific awards and grant details are not provided in source materials.

• Plant Genetics
• Meiosis
• Meiotic Recombination
• +4 more

Tareq Alodat is a Lecturer in Statistics and Data Science at the Mathematics & Statistics school of La Trobe University in Melbourne, Australia. He simultaneously holds a Postdoctoral Research Fellow position at UNSW Australia's School of Mathematics and Statistics in Sydney. His academic background includes: PhD from La Trobe University, Melbourne, Australia (2016-2019) Dr. Alodat's research expertise spans theoretical and applied statistics with significant contributions to long-range dependent processes, stochastic modeling, and nonparametric methods. His work bridges probability theory with practical applications in ecology, medical research, and spatial statistics. He has developed novel statistical approaches for complex data structures and contributed to distribution theory, particularly with generalized skew-normal distributions. Analysis of his publication trajectory reveals increasing specialization in fractional stochastic differential equations applied to spherical geometry, alongside continued work in ecological statistics. His research demonstrates consistent theoretical development paired with practical applications across diverse domains, with recent publications showing sophisticated mathematical techniques applied to real-world problems. Dr. Alodat serves as a reviewer for several prominent journals including Communications in Statistics-Simulation and Computation, Symmetry-Basel, and Entropy, reflecting his standing in the statistical community.

• Applied Statistics
• Biostatistics
• Data Communications
• +5 more

Johan Peter Bøtker serves as an Associate Professor in the Department of Pharmacy at the University of Copenhagen's Faculty of Health and Medical Sciences, specializing in advanced pharmaceutical technology and solid-state analysis. His research program emphasizes: Solid-state characterization using thermal analysis, Raman spectroscopy, and synchrotron diffraction techniques Development of dissolution testing methodologies with 3D-printed custom apparatus Computer vision applications for pharmaceutical quality control systems Advanced processing techniques including milling, hot-melt extrusion, and additive manufacturing Acoustic data treatment for inhaled drug delivery optimization Analysis of his publication record reveals consistent expertise in solid-state transformations, dissolution mechanisms, and amorphous material stability, with increasing integration of computational modeling and synchrotron-based analytical approaches. His work bridges pharmaceutical sciences with materials engineering and analytical chemistry. While specific awards were not documented, Dr. Bøtker maintains extensive collaborative networks across international research institutions as evidenced by his co-authorship patterns and country-level research mapping.

• Pharmaceutical Technology
• Solid-State Characterization
• Drug Delivery Systems
• +3 more