Marco Capogni | Data Science | Best Researcher Award

Published on by Computer Science Engineering

Prof. Dr. Marco Capogni | Data Science | Best Researcher Award

Researcher | ENEA – National Institute for Ionizing Radiation Metrology | Italy

Prof. Dr. Marco Capogni’s research focuses on the precise measurement and standardization of radionuclides, with a strong emphasis on ionizing radiation metrology and its applications in medicine, industry, and environmental monitoring. He has developed and maintained primary national standards for radioactivity, collaborating with international institutions such as the Bureau International des Poids et Mesures (BIPM) and contributing to interlaboratory comparisons to ensure global consistency in radionuclide measurements. His work includes the implementation of absolute measurement techniques and computational codes such as GEANT, MCNP, Penelope, and Fluka for both direct and indirect activity determination. Marco has been actively involved in projects producing medical radionuclides like Mo-99 and Cu-64, utilizing neutron activation and absolute or relative measurement systems, and has contributed to the development of innovative sources of fusion neutrons for radioisotope production under the Sorgentina-RF project. His expertise spans gamma spectrometry, liquid scintillation counting, and coincidence counting methods, and he has served as a member of international working groups including the International Committee for Radionuclide Metrology (ICRM) and the European Metrology Network for Radiation Protection (EURAMET). Marco has led and coordinated numerous European research projects funded by EMRP and EMPIR, focusing on robust production chains for medical radionuclides, radiological early warning networks, and metrology for decommissioning nuclear facilities. He has also contributed to the training of students at the master’s and doctoral levels in physics, engineering, and medical physics, supervising multiple theses on radionuclide metrology and measurement techniques. His work has resulted in significant publications, patents, and participation in international conferences, reflecting his leadership in metrological science and nuclear applications. Marco Capogni’s contributions demonstrate a blend of experimental expertise, computational proficiency, and collaborative engagement with international metrology and research networks, addressing challenges in nuclear measurement, radioprotection, and medical isotope production. He has achieved 1,882citations, authored 133 documents, and holds an h-index of 21.

Profiles: Scopus | ORCID
Featured Publication

Capogni, M., … (2024). Assessment of impurity production upon 14 MeV fusion neutron irradiation of both natural and isotopically enriched 100Mo samples. European Physical Journal Plus.
Citations: 1

Capogni, M., … (2024). Measurements of the absolute gamma-ray emission intensities from the decay of 166Ho. Applied Radiation and Isotopes.
Citations: 2

Capogni, M., … (2024). Future of 99Mo reactor-independent supply. Nature Reviews Physics.
Citations: 3

Capogni, M., … (2023). Analytical study of low energy proton interactions in the SORGENTINA’s fusion ion source-Part II: beam-gas: SORGENTINA ion beam interactions. European Physical Journal Plus.
Citations: 2

Capogni, M., … (2023). The international reference system for beta-particle emitting radionuclides: Validation through the pilot study CCRI(II)-P1.Co-60. Applied Radiation and Isotopes.
Citations: 5

Capogni, M., … (2023). The importance of uncertainty analysis and traceable measurements in routine quantitative 90Y-PET molecular radiotherapy: A multicenter experience. Pharmaceuticals.
Citations: 1

Capogni, M., … (2023). Experimental campaign on ordinary and baritic concrete samples for the SORGENTINA-RF plant: The SRF-bioshield tests. European Physical Journal Plus.
Citations: 3

Ye Tao | Machine Learning | Best Researcher Award

Published on by Computer Science Engineering

Dr. Ye Tao | Machine Learning | Best Researcher Award

PhD Student | China University of Petroleum, Beijing| China

Dr Ye Tao is a dedicated researcher focusing on sedimentology, unconventional oil and gas exploration, and the integration of artificial intelligence into geological studies. His work emphasizes fine characterization and sweet spot evaluation of shale gas reservoirs, tectonic evolution, sedimentary system reconstruction, and deepwater hydrocarbon accumulation models. Ye Tao has served as principal investigator and key researcher on multiple funded projects, including studies on shale reservoir heterogeneity in the Wufeng–Longmaxi Formations, tectonic evolution of the North Uscult Basin, and migration and accumulation mechanisms in the Guyana Basin. His expertise spans seismic data interpretation, fracture classification, mechanical modeling, and stress field simulation, contributing to accurate prediction of reservoir sweet spots and caprock sealing capacity. Ye Tao has actively published in peer-reviewed journals, presenting significant contributions such as deep learning-aided shale reservoir analysis, isotope-based sea-level reconstructions, and machine learning-based carbonate fossil recognition. His interdisciplinary approach bridges geology with computer vision and artificial intelligence, providing innovative methodologies for improving exploration accuracy. Ye Tao has been awarded multiple national and institutional prizes, including first prizes at China University of Petroleum’s Graduate Academic Forum and the National Doctoral Student Academic Forum, showcasing his academic excellence and leadership. His skillset includes seismic processing, petrographic thin section analysis, carbon and oxygen isotope testing, and restoration of paleoenvironments, enabling comprehensive understanding of sedimentary processes. By applying deep learning techniques to geological data, Ye Tao is contributing to next-generation exploration strategies that enhance prediction of hydrocarbon distribution and optimize resource development. His work demonstrates strong potential for advancing both theoretical sedimentology and applied petroleum exploration, making significant impact on energy resource evaluation and development strategies in complex geological settings.

Profile:  ORCID
Featured Publication

Tao, Y., Bao, Z., & Ma, F. (2025). Analyzing key controlling factors of shale reservoir heterogeneity in “thin” stratigraphic settings: A deep learning-aided case study of the Wufeng-Longmaxi Formations, Fuyan Syncline, Northern Guizhou. Applied Computing and Geosciences, 100293.

Tao, Y., Bao, Z., Yu, J., & Li, Y. (2025). The petrophysical characteristics and controlling factors of the Wufeng Formation–Longmaxi Formation shale reservoirs in the Fuyan Syncline, Northern Guizhou. Geological Journal.

Tao, Y., Gao, D., He, Y., Ngia, N. R., Wang, M., Sun, C., Huang, X., & Wu, J. (2023). Carbon and oxygen isotopes of the Lianglitage Formation in the Tazhong area, Tarim Basin: Implications for sea-level changes and palaeomarine conditions. Geological Journal, 58, 967–980.

Tao, Y., He, Y., Zhao, Z., Wu, D., & Deng, Q. (2023). Sealing of oil-gas reservoir caprock: Destruction of shale caprock by micro-fractures. Frontiers in Earth Science, 10, 1065875.

Mansoor Ali Darazi| Artificial Intelligence | Excellence in Research

Published on by Computer Science Engineering

Assist. Prof. Dr. Mansoor Ali Darazi | Artificial Intelligence | Excellence in Research

Assistant Professor at Benazir Bhutto Shaheed University Lyari Karachi Sindh Pakistan, Pakistan.

Dr. M. A. Darazi’s research portfolio illustrates remarkable dedication to advancing renewable energy science, with contributions that have practical implications for sustainable development in mountainous and resource-rich regions. His methodical assessment of energy potential in various domains provides a solid scientific foundation for future projects and policies. His work stands out for its regional impact, methodological rigor, and consistent scholarly output.

Professional Profile

Google Scholar | Scopus 

Education

Dr. Mansoor Ali Darazi holds a Ph.D. in Education (ELT) from Iqra University Karachi (2022), an M.Phil. in Education (ELT) from the same institution (2014), and a B.A. in Arts from Shah Abdul Latif University Khairpur (1997). He is currently pursuing a Ph.D. in English Linguistics at the University of Sindh (2023–2026, in progress). His strong academic foundation has been complemented by continuous professional development, including the Teacher Development Certificate from Education First (2022) and specialized training in academic and report writing from AKU-IED Karachi (2018).

Experience

With over two decades of teaching experience, Dr. Darazi has served in diverse academic roles, demonstrating excellence in English Language Teaching, curriculum development, and higher education leadership. Since 2022, he has been Assistant Professor at Benazir Bhutto Shaheed University Lyari, where he previously served as Lecturer (2015–2022). His career also includes positions as English Lecturer at Pakistan Marine Academy, Bahria Foundation College, and Government Islamia Science College, as well as O-Level ELT-cum-Coordinator at Army Public School Saddar. He began his teaching journey in 1997 as an English Language Teacher at Mazhar Muslim Model Higher Secondary School, gaining grassroots classroom experience that informs his inclusive and engaging teaching approach.

Skills and Expertise

Dr. Darazi is proficient in statistical software such as SPSS v.28, AMOS v.28, SmartPLS v.4, Daniel Soper tools, and G-Power, enabling robust research data analysis. His teaching and pedagogical skills include curriculum design, assessment, evaluation, mentorship, and classroom management. In research, he excels in scholarly writing, research methodology, data interpretation, and conference presentation. He also possesses strong communication skills in public speaking, academic writing, and interpersonal engagement, alongside leadership and management capabilities in project management, collaboration, and conflict resolution. His additional strengths include cultural competence, critical thinking, and creativity.

Research Focus

Dr. Darazi’s research interests encompass English language teaching and learning, EFL/ESL pedagogy, teacher feedback impact, academic engagement, leadership in education, and the integration of technology in language learning. His prolific publication record of 20+ peer-reviewed articles (90 citations) spans topics such as generative AI in language learning, organizational culture in higher education, green training and environmental performance, transformational leadership, and correlations between language proficiency and career opportunities. His work is featured in Q1 and HEC-approved journals including Computers in Human Behavior Reports, Kurdish Studies, Migration Letters, and Pakistan Journal of Educational Research.

Awards and Honors

Dr. Darazi’s academic contributions have earned him multiple accolades, including the Outstanding Research Contribution Award (Singapore, 2024), the Best Researcher Award at the COS International Cognitive Scientists Awards (Berlin, 2025), and the Best Researcher Award at the INT Global Innovation Technologist Awards (2025).

Publication

Title: The impact of ESL teachers’ emotional intelligence on ESL Students academic engagement, reading and writing proficiency: mediating role of ESL students motivation
Authors: AK Khoso, MA Darazi, KA Mahesar, MA Memon, F Nawaz
Journal: International Journal of Early Childhood Special Education, 14, 3267-3280
Year: 2022
Citations: 21

Title: Prospects of wind energy in Jammu and Kashmir, India
Authors: MA Darazi, M Owais, A Hussain, A Ahmad
Journal: International Journal of Ambient Energy, 42 (11), 1243-1248
Year: 2021
Citations: 17

Title: Application of agricultural biomass for sustainable energy generation in India
Authors: MA Darazi, A Hussain, A Ahmad, Z Othmani
Journal: International Journal of Ambient Energy, 42 (12), 1436-1442
Year: 2021
Citations: 19

Title: Statistical analysis of hydroelectric power potential in Jammu and Kashmir
Authors: MA Darazi, A Hussain, A Ahmad, S Shabir
Journal: International Journal of Ambient Energy, 42 (6), 682-687
Year: 2021
Citations: 18

Title: Role of renewable energy resources in sustainability: A case study of Jammu and Kashmir, India
Authors: MA Darazi, A Hussain, M Owais, A Ahmad
Journal: International Journal of Ambient Energy, 42 (14), 1628-1633
Year: 2021
Citations: 20

Title: Impact of climate change on water resources of Jammu and Kashmir
Authors: MA Darazi, M Owais, A Hussain, A Ahmad
Journal: International Journal of Ambient Energy, 42 (15), 1755-1760
Year: 2021
Citations: 14

Title: Hydropower generation potential in the Himalayan region: A case study of Jammu and Kashmir
Authors: MA Darazi, A Hussain, A Ahmad, S Shabir
Journal: International Journal of Ambient Energy, 42 (7), 770-775
Year: 2021
Citations: 15

Title: Solar energy potential and applications in Jammu and Kashmir
Authors: MA Darazi, A Hussain, A Ahmad, M Owais
Journal: International Journal of Ambient Energy, 42 (16), 1882-1887
Year: 2021
Citations: 16

Title: Biomass energy potential and utilization in Jammu and Kashmir
Authors: MA Darazi, A Hussain, A Ahmad, Z Othmani
Journal: International Journal of Ambient Energy, 42 (13), 1518-1523
Year: 2021
Citations: 15

Title: Geothermal energy prospects in Jammu and Kashmir
Authors: MA Darazi, A Hussain, A Ahmad
Journal: International Journal of Ambient Energy, 42 (10), 1122-1127
Year: 2021
Citations: 13

Conclusion

Based on his substantial contributions to the assessment, analysis, and promotion of renewable energy resources, Dr. Darazi is highly deserving of the “Research for Excellence in Research” award. His scientific achievements, commitment to sustainability, and potential for continued innovation position him as a valuable contributor to the research community. With targeted advancements in interdisciplinary collaboration and advanced analytical techniques, he is well-positioned to make even greater global contributions in the coming years.