Michael Pitton | Descriptive and Inferential Statistics | Best Researcher Award

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Prof. Dr. Michael Pitton | Descriptive and Inferential Statistics | Best Researcher Award

Medical University of Mainz | Germany

Professor Dr. Michael Pitton is a distinguished German physician-scientist and expert in diagnostic and interventional radiology. A graduate of the Johannes Gutenberg University Mainz, he completed his medical studies and advanced clinical training in internal medicine, cardiology, radiology, and neuroradiology at leading German university hospitals, including the University Medical Center Mainz and the Deutsches Herzzentrum Berlin. His academic achievements include a habilitation on functional and morphological aspects of endovascular aneurysm therapy, followed by his appointment as university lecturer and senior consultant in interventional radiology. Professor Pitton has held successive leadership positions and currently serves as the Acting Director of the Department of Diagnostic and Interventional Radiology and Head of the Section of Interventional Radiology at the University Medical Center Mainz. He also holds European Board Certification in Interventional Radiology (EBIR) and the European Certification for Endovascular Specialists (CIRSE) and is a certified DEGIR instructor across all modules. Combining clinical excellence with managerial insight, he earned a Master of Health Business Administration, reflecting his engagement in healthcare management and innovation. Professor Pitton has an extensive scientific record, with approximately 127 publications, an h-index of around 33, and more than 6,771 citations, underscoring his influence in vascular and interventional radiology. His research contributions have advanced the understanding and treatment of aneurysms, transjugular intrahepatic portosystemic shunt (TIPS) interventions, and image-guided oncologic therapies. Recognized with numerous national and international awards, his work bridges academic medicine, translational research, and health leadership. Professor Pitton exemplifies excellence in clinical radiology, academic scholarship, and interdisciplinary collaboration, contributing significantly to the development of interventional radiology in Europe.

Profiles: Scopus | Orcid

Featured Publications

Graafen, D., Bart, W., Halfmann, M. C., Müller, L., Hobohm, L., Yang, Y., Neufang, A., Espinola-Klein, C., Pitton, M. B., Kloeckner, R., Varga-Szemes, A., & Emrich, T. (2022). In vitro and in vivo optimized reconstruction for low-keV virtual monoenergetic photon-counting detector CT angiography of lower legs.

Gairing, S. J., Kuchen, R., Müller, L., Cankaya, A., Weerts, J., Kapucu, A., Sachse, S., Zimpel, C., Stoehr, F., Pitton, M. B., Mittler, J., Straub, B. K., Marquardt, J. U., Schattenberg, J. M., Labenz, C., Kloeckner, R., Weinmann, A., Galle, P. R., Wörns, M. A., & Foerster, F. (2022.). 13C-Methacetin breath test predicts survival in patients with hepatocellular carcinoma undergoing transarterial chemoembolization.

Müller, L., Hahn, F., Mähringer-Kunz, A., Stoehr, F., Gairing, S. J., Foerster, F., Weinmann, A., Galle, P. R., Mittler, J., Pinto Dos Santos, D., Pitton, M. B., Düber, C., Fehrenbach, U., Auer, T. A., Gebauer, B., & Kloeckner, R. (2022). Prevalence and clinical significance of clinically evident portal hypertension in patients with hepatocellular carcinoma undergoing transarterial chemoembolization.

Oleg Selyugin | Big Data and Statistical Analytics | Big Data Analytics Award

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Dr. Oleg Selyugin | Big Data and Statistical Analytics | Big Data Analytics Award

Joint Institute for Nuclear Research | Russia

Dr. Oleg Selyugin is a Russian empirical and theoretical physicist with a distinguished career in high-energy hadron scattering and the structure of hadrons. After completing his studies at the Physics Department of Moscow State University, he joined the Joint Institute for Nuclear Research (JINR), first as a probationer and researcher at the Laboratory of Nuclear Problems, and later at the Bogoliubov Theoretical Laboratory (BTL), where he now serves as a leading scientist. At BTL, he earned his Ph.D. with the thesis “High energy elastic hadron-hadron scattering in a wide momentum transfer region,” and later obtained his Doctor of Physics and Mathematics degree with the thesis “The structure of high-energy amplitude of the elastic hadron-hadron scattering in the diffraction region.” Dr Selyugin has been recognized with multiple International Prizes of JINR for his outstanding contributions to polaron physics, hadron physics, and high-energy physics. His primary research interests include the structure of hadrons (PDFs, GPDs, form-factors), phenomenology of high-energy physics (differential cross sections, spin phenomena), models of extra dimensions (d-brane gravity), and nonlinear effects. He has been actively involved in interpreting experimental results from the CERN LHC, particularly the TOTEM and ATLAS Collaborations. His theoretical work integrates electromagnetic and gravitational form-factors derived from novel t-dependent GPDs, as well as soft and cross-even pomeron contributions, within dispersion-relation-based frameworks. With over 180 scientific papers, Dr Selyugin has made a profound and lasting impact on the understanding of elastic hadron scattering at high energies. Although specific bibliometric indicators such as 17 h-index, 78 documents, and 815 citations vary across databases, his scientific influence is widely recognized within the international physics community. He continues his pioneering research at JINR in Dubna, Russia.

Profiles: Scopus | Orcid

Featured Publications

Selyugin, O. V. (2024). Unified description of elastic hadron scattering at low and high energies. Physics of Atomic Nuclei, 87(S2), S349–S362.

Mohammad Imrul Islam | Geospatial and Spatial Statistics | Best Researcher Award

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Mr. Mohammad Imrul Islam | Geospatial and Spatial Statistics | Best Researcher Award

Bangladesh Space Research and Remote Sensing Organization (SPARRSO) | Bangladesh

Mr. Mohammad Imrul Islam is a highly dedicated Remote Sensing Researcher and Senior Scientific Officer (SSO) at the Bangladesh Space Research and Remote Sensing Organization (SPARRSO), where he has been contributing his expertise since 2015. With over a decade of professional experience in Remote Sensing (RS) and Geographic Information System (GIS), his work focuses on environmental monitoring, agriculture, forestry, and water resource management, making him one of the promising scientific minds in Bangladesh’s earth observation community. He holds a Master of Engineering in Remote Sensing and GIS from Beihang University, Beijing, China (GPA 3.76), along with both Master of Science and Bachelor of Science degrees in Geography and Environment from Jahangirnagar University, Bangladesh, with first-class distinction. At SPARRSO, he has successfully led and contributed to several national and institutional projects such as flash flood monitoring in Tanguar Haor, spatio-temporal analysis of fisheries habitats, water quality assessment for inland fisheries, and GIS-based marine fishing zone identification. His research showcases his ability to integrate satellite data with advanced geospatial analytics for sustainable environmental management and disaster resilience. His postgraduate research and pilot studies explored innovative approaches such as retrieving Leaf Area Index (LAI) and analyzing the relationship between Solar-Induced Chlorophyll Fluorescence (SIF) and Gross Primary Production (GPP), reflecting his strong foundation in combining remote sensing models with ecological parameters for vegetation monitoring. Mr. Islam has participated in numerous international training and capacity-building programs organized by ISRO, APSCO, NESAC, Hokkaido University, and the University of Twente (ITC, Netherlands), enhancing his global scientific exposure. His technical expertise covers major geospatial and analytical software including ArcGIS, QGIS, ERDAS Imagine, ENVI, SNAP, and cloud-based tools such as Google Earth Engine, complemented by programming proficiency in Python, R, and MATLAB. Fluent in both English and Bangla, and with a TOEIC score of 805, he demonstrates strong communication and collaboration skills across international platforms. Through his ongoing research on seasonality mapping of surface water and hydrometeorological flood monitoring, he continues to contribute toward global climate resilience and sustainable resource management. Actively engaged on ResearchGate, LinkedIn, and ORCID, Mohammad Imrul Islam inspires emerging geospatial researchers across South Asia. His academic rigor, technical competence, and impactful research contributions make him an exemplary candidate for the Best Researcher Award, recognizing his significant role in advancing earth observation and remote sensing research at both national and international levels.

Profiles: Google Scholar | Orcid | Linked In

Featured Publications

Islam, M. I., Rahman, M. M., & Islam, M. Z. (2025). Comparative analysis of chlorophyll-a retrieval algorithms for inland waterbodies of Bangladesh using Sentinel-2 and Landsat-8 imagery. Discover Geoscience.

Niloy, N. M., Habib, S. M. A., Islam, M. I., Haque, M. M., Shammi, M., & Tareq, S. M. (2023). Distribution, characteristics and fate of fluorescent dissolved organic matter (FDOM) in the Bay of Bengal. Marine Pollution Bulletin.

Islam, M. I., Habib, S. M. A., Haque, S. A. U., Sultana, N., Faisal, B. M. R., Rahman, H., & Sharifee, M. N. H. (2020). Applicability of OCO-2 solar induced chlorophyll fluorescence (SIF) data for the estimation of photosynthetic activity in Bangladesh. Journal of Engineering Science, 11(2), 1–9.

Faisal, B. M. R., Rahman, H., Sharifee, N. H., Sultana, N., Islam, M. I., Habib, S. M. A., & Ahammad, T. (2020). Integrated application of remote sensing and GIS in crop information system: A case study on Aman rice production forecasting using MODIS-NDVI in Bangladesh. AgriEngineering, 2(2), 243–257.

Rahman, M. M., Pramanik, M. A. T., Islam, M. I., & Razia, S. (2019). Mapping mangrove forest change in Nijhum Dwip Island. Journal of Environmental Science and Natural Resources, 11(1–2), 25–32.