Dr. Dhruv Sharma | Deep Learning | Best Researcher Award

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Dr. Dhruv Sharma | Deep Learning | Best Researcher Award

Amity University | India

Dr. Dhruv Sharma is an assistant professor at the Amity Centre for artificial intelligence, Amity university, noida, uttar pradesh, india. He earned his Ph.d. in electronics and communication engineering from Delhi technological university (dtu), specializing in machine learning, computer vision, and multimodal ai. his academic and research journey reflects a deep commitment to advancing artificial intelligence through innovative methodologies in signal processing, natural language processing, and deep-learning architectures. With a total of 7 publications in reputed sci and scopus-indexed journals, dr. sharma has made impactful contributions to the fields of intelligent perception and vision-language fusion. his research on multimodal radiology report generation, conducted in collaboration with the rajiv gandhi cancer institute and research centre, exemplifies his interdisciplinary approach to real-world problem-solving, Deep Learning . his scholarly influence is evidenced by 109 citations, an h-index of 6, and an i10-index of 3, demonstrating consistent research quality and impact. He has also published one patent and actively serves as a reviewer for leading ieee, elsevier, and springer journals. Dr. Sharma has been honored with the commendable research award and the premier research award from dtu, recognizing his excellence in artificial intelligence research and innovation.

Profiles: Orcid | Google Scholar

Featured Publications

Sharma, D., Dhiman, C., & Kumar, D. (2025, October). UnMA-CapSumT: Unified and multi-head attention-driven caption summarization transformer. Journal of Visual Communication and Image Representation.

Sharma, D., Dhiman, C., & Kumar, D. (2024, July). FDT−Dr2T: A unified Dense Radiology Report Generation Transformer framework for X-ray images. Machine Vision and Applications.

Sharma, D., Dhiman, C., & Kumar, D. (2024, May 30). Control with style: Style embedding-based variational autoencoder for controlled stylized caption generation framework. IEEE Transactions on Cognitive and Developmental Systems.

Rautela, K., Sharma, D., Kumar, V., & Kumar, D. (2024, January). Obscenity detection transformer for detecting inappropriate contents from videos. Multimedia Tools and Applications.

Sharma, D., Dhiman, C., & Kumar, D. (2024, January). XGL-T transformer model for intelligent image captioning. Multimedia Tools and Applications.

Dr. Sharon Kiprotich | Material Science | Best Researcher Award

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Dr. Sharon Kiprotich | Material Science | Best Researcher Award

Murang'a University of Technology | Kenya

Dr. Sharon Kiprotich is a kenyan physicist and senior lecturer at murang’a university of technology, where she also serves as the chairman of the department of physical and biological sciences. she holds a Ph.d. in physics, an M.Sc. in physics with cum laude, and a B.Sc. hons in physics from the university of the free state, south Africa, as well as a bachelor’s degree in education (physics/mathematics) from kenyatta university, Kenya. With over a decade of experience in teaching, research, and academic leadership, she has served as a lecturer, research assistant, and secondary school teacher, contributing significantly to both academic and institutional development. Her administrative roles include membership in the promotion and appraisal committee, postgraduate coordination, and academic advising for graduate and undergraduate students. Dr. Kiprotich’s research has garnered notable recognition in Material Science with 70 citations from 57 documents, 17 publications, and an h-index of 6, reflecting her growing influence in the field of physics. her academic and professional journey exemplifies dedication to scientific advancement, mentorship, and the empowerment of young scholars in Kenya and beyond, marking her as a distinguished contributor to physics education and research in Africa.

Profiles: Scopus | Orcid

Featured Publications

Kiprotich, B., Waithaka, P., Opiyo, S., & Kiprotich, S. (2025, October 9). Green synthesis of Ga-doped SnO₂ nanoparticles: Effects of Ga doping concentrations on the structural and optical properties. Journal of Photonic Materials and Technology.

Gakuru, S. W., Kiprotich, S., Waithaka, P., & Dejene, F. B. (2025, October 8). Synergetic effects of Zn:Fe-codoped TiO₂ nanoparticles on the structural, optical, and morphological properties. Physica Status Solidi (a).

Kiprotich, N., Waithaka, P., Kiprotich, S., & Njagi, J. (2025, June 30). Effects of tin doping concentration on the structural and optical properties of cadmium oxide nanoparticles. Advances in Materials.

Jepngetich, J., Njoroge, P. W., Opiyo, S., & Kiprotich, S. (2025, May 1). Synthesis and characterization of Ag–ZnO using citrus reticulata peel extract. Materials Research Express.

Waithira, S. N., Wako, A. H., Nyamato, S., & Kiprotich, S. (2024, December). Effects of synthesis temperature on the structural and optical properties of CaAl₂O₄: Eu²⁺, Dy³⁺ nanoparticles. Scientific African.

Dr. Ibrahim Ahmad | Sustainable Livestock Production | Best Researcher Award

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Dr. Ibrahim Ahmad | Sustainable Livestock Production | Best Researcher Award

University of Tasmania | Australia

Dr. Ibrahim Ahmad is a distinguished veterinary scientist and doctoral researcher at the university of Tasmania, Australia, specializing in sustainable livestock production under the tasmanian institute of agriculture. He holds a doctor of veterinary medicine from Usmanu Danfodiyo university sokoto, a master’s degree in veterinary medicine from ahmadu bello university zaria, and is currently pursuing a Ph.d. in agriculture alongside a graduate certificate in research. his research focuses on developing novel anti-methanogenic feed additives from asparagopsis armata to mitigate enteric methane emissions from ruminant livestock, thereby promoting climate-resilient animal agriculture. With over a decade of professional experience as a senior veterinary officer in nigeria, dr. ahmad has contributed extensively to animal health, welfare, biosecurity, Sustainable Livestock Production and sustainable livestock management. he has received multiple international awards and scholarships, including the tasmania graduate research scholarship and the aw howard memorial trust scholarship. his scholarly output includes 14 research documents, 73 citations, and an h-index of 6, reflecting his growing influence in animal science and environmental sustainability. As an active member of several international professional societies, dr. ahmad continues to advance global research in livestock production, veterinary medicine, and sustainable agriculture.

Profiles: Scopus | Orcid

Featured Publications

Ahmad, I., Rawnsley, R. P., Bowman, J. P., & Omede, A. A. (2025). Rumen microbiome response to methane inhibition. Microbiology Australia.

Ahmad, I., Rawnsley, R. P., Bowman, J. P., & Omede, A. A. (2025, October). Graduate student literature review: Limitations in feeding red seaweed Asparagopsis species for enteric methane mitigation in ruminants. Journal of Dairy Science.

Ahmad, I., Bowman, J., Rawnsley, R., & Omede, A. (2025, June 26). Feed-grade biochar supplementation for enteric methane emissions reduction: Potential anti-methanogenic myths and emerging facts.

Omede, A., Raedts, P., Ahmad, I., Talbot, J., Dolbey, B., & Rawnsley, R. (2024, July 8). Effect of transition feeding of Asparagopsis-oil (Asp-oil) on sheep performance. In Proceedings of the 35th Biennial Conference of the Australian Association of Animal Sciences (ISSN 0728-5965).

Ahmad, I., Omede, A., & Rawnsley, R. (2024, July 8). Harnessing a long transition period in feeding Asparagopsis for enteric methane mitigation in ruminants. In Proceedings of the 35th Biennial Conference of the Australian Association of Animal Sciences (ISSN 0728-5965).

Dr. Emily Bagarukayo | Autonomous Robot Navigation | Best Researcher Award

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Dr. Emily Bagarukayo | Autonomous Robot Navigation | Best Researcher Award

Makerere University | Uganda

Dr. Emily Bagarukayo is a distinguished academic, researcher, and consultant in computing and Ict, currently serving at the school of computing and informatics technology, college of computing and information sciences, Makerere university. She holds a Ph.d in information science from Radboud university Nijmegen, Netherlands, a postgraduate diploma in educational technologies from the university of cape town, a master’s in computer science from makerere university, and a bachelor’s degree in computer science (hons) from mbarara university of science and technology. She is also a research associate at the international center of it and development, southern university, USA. Her doctoral research focused on e-learning, emphasizing the role of digital learning environments and Autonomous Robot Navigation multimedia in enhancing learning outcomes through the “learning by construction approach.” her current research interests include personalized learning, instructional content development, and ict4d, with a growing focus on the impact of social software on education. she has published 11 documents, received 14 citations from 14 documents, and holds an h-index of 2. As a passionate educator, she has mentored numerous undergraduate and postgraduate students while contributing to over 36 peer-reviewed journals, conferences, and book chapters.

Profile: Scopus

Featured Publication

Bagarukayo, E. Framework for enhancing tutor–student interaction in blended courses: A case of Bachelor of Youth in Development Work at Makerere University.

 

Mr. Salman khan | Environmental sciences | Best Researcher Award

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Mr. Salman khan | Environmental sciences | Best Researcher Award

Abdul Wali Khan University Mardan | Pakistan

Mr. Salman Khan is a dedicated researcher and educator in the field of chemistry from Abdul Wali Khan University, Mardan, Pakistan. He has a strong academic background focused on applied and environmental chemistry, particularly in the development of sustainable energy and water purification systems. His thesis explored strategies to enhance bio-oil and bio-gas through catalytic co-pyrolysis of calotropis with waste plastic and spent engine oil, reflecting his deep interest in renewable energy and chemical transformation. His research interests include wastewater treatment, hydrogen production, mxenes, batteries, catalytic pyrolysis, Environmental sciences and biomass conversion. Salman has contributed to national and international research projects on nanocomposites for water treatment and microbial desalination systems for efficient water purification. as an education professional, he has developed engaging course materials, guided students, and fostered innovative learning environments. He is also proficient in english, holding certification from the international english language testing system. His scholarly profile demonstrates measurable academic impact, with 45 citations, an h-index of 3, and an i10-index of 2. Salman aims to continue expanding his research horizons, collaborate globally, and make impactful advancements in environmental chemistry and sustainable technologies.

Profile: Google Scholar

Featured Publications

Hussain, S. A., Hu, J., Liu, H., Aslam, F., Khan, S., Khan, L., & Jiao, F. (2024). Preparation of C-doped g-C₃N₄ by co-polycondensation of melamine and sucrose for improved photocatalytic H₂ evolution. International Journal of Hydrogen Energy, 87, 705–712.

Jamal, M., Nabi, G. A. K., Sun, H., Ullah, K., Khattak, O. A., Kashif, M., Khan, S., et al. (2024). Preparation of manganese-doped bismuth oxide for the photocatalytic degradation of methylene blue. Archives of Advanced Engineering Science, 1–7.

Bibi, A., Ghazal, S., Shah, A., Khan, S., Nawaz, I., Israr, M., Rani, S., Ullah, K., et al. (2024). Comparative study of antibacterial and antifungal activities of silver nanoparticles and Capsicum annum leaves extracts. Journal of Animal and Plant Research, 1(2), 19–25.

Khan, S., Kalsoom, U., Kashif, M., Hussain, S. A., Gul, M., Azizi, S., & Maaza, M. (2025). Smart and sustainable microplastic removal: Hybrid systems, bio-inspired technologies, real-time sensing, and policy integration. Water, Air, & Soil Pollution, 236(14), 1–34.

Kalsoom, U., Khan, S., Kashif, M., Yaseen, H. S., Hussain, S. A., Azizi, S., & Maaza, M. (2025). MXene-based hybrid composites for lithium-ion batteries: Advances in synthesis strategies and electrochemical performance. Ionics, 1–21.

Hussain, S. A., Hu, J., Aslam, F., Hu, C., Liu, H., Ullah, A., Khan, S., & Jiao, F. (2025). Bandgap modulation via Al photodeposition on C-doped g-C₃N₄ for enhanced photocatalytic hydrogen production. Industrial & Engineering Chemistry Research.

Dr. Paolo Ingallinella | Diagnostics | Best Researcher Award

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Dr. Paolo Ingallinella | Diagnostics | Best Researcher Award

Diasorin | Italy

Dr. Paolo Nunzio Ingallinella is a distinguished biotech director at Diasorin Italia Spa, with over many years of expertise in peptide and protein chemistry for therapeutic and diagnostic applications. he holds a master’s degree in chemistry from the university of naples and began his career at irbm, where he contributed to groundbreaking antiviral research, developing potent hcv peptide inhibitors and an hiv fusion inhibitor that advanced antiviral drug design. He has been leading innovative diagnostic projects at diasorin, including the development of the first automated immunoassays for hdv and hev antibodies and Diagnostics broad-spectrum legionella antigen detection systems. his extensive research portfolio includes 25 completed or ongoing projects, 23 journal publications indexed, and 20 patents published or under process. According to scopus metrics, Dr. Ingallinella has an h-index of 19 with a total of 1,616 citations, reflecting his strong influence in the biotechnology and immunodiagnostics fields. his work focuses on recombinant protein and monoclonal antibody development, biomarker discovery, and molecular biology applications in diagnostics and therapeutic peptide chemistry. A member of the Italian peptide society, Dr. Ingallinella continues to shape the landscape of modern biotechnology through innovation and scientific leadership.

Profile: Scopus

Featured Publications

Ingallinella, P. N., et al. (2025). The LIAISON® Legionella Urinary Ag assay: A novel high-throughput, fully automated dual-antigen detection method with improved sensitivity and expanded Legionella species and serogroup coverage. Respiratory Investigation.

Ingallinella, P. N., et al. (2014). Development of a neuromedin U–human serum albumin conjugate as a long-acting candidate for the treatment of obesity and diabetes: Comparison with the PEGylated peptide. Journal of Peptide Science.

Ingallinella, P. N., et al. (2013). A PEGylated analog of the gut hormone oxyntomodulin with long-lasting antihyperglycemic, insulinotropic, and anorexigenic activity. Bioorganic & Medicinal Chemistry.

Ms. Tamanna | Neural Networks for Robot Control | Best Researcher Award

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Ms. Tamanna | Neural Networks for Robot Control | Best Researcher Award

Goethe University, Frankfurt | Germany

Tamanna is a Ph.d. researcher at Goethe University, Frankfurt, Germany, specializing in geochemistry with a focus on integrating data science and machine learning into geo-scientific research. Her work aims to bridge the gap between traditional geoscience and modern computational methodologies by leveraging data-driven approaches to analyze complex geochemical systems. She holds a bs-ms degree in earth and environmental sciences from the Indian institute of science education and research, Bhopal. her expertise spans elemental and isotopic geochemistry, geospatial analysis, statistical modeling, and predictive analytics for geochemical processes. She is proficient in programming and data visualization using python, Neural Networks for Robot Control, matlab, qgis, and arcgis. Tamanna has authored two research documents with approximately one citation and an h-index of 1 for those publications; overall, her author-level record includes 99 citations and an h-index of 6, according to google scholar. Beyond her technical skills, she is actively involved in interdisciplinary research that combines quantitative methods, laboratory work, and field investigations to enhance the understanding of earth’s chemical evolution. fluent in english and hindi, with working knowledge of german, she represents the next generation of data-driven geoscientists.

Profile: Orcid

Featured Publications

Tamanna, Hezel, D. C., & Marschall, H. R. (2025, October). MRMinerals and MineralTD: Machine‐Readable Mineral Formula and Compositions Data Set for Data‐Driven Research. Geoscience Data Journal.

Tamanna, Hezel, D. C., Srivastava, N., & Faber, J. (2025, August 13). Using machine learning for automatic rock classification. American Mineralogist.

Dr. Dmitri Lapotko | Automated Cancer Diagnostics | Best Researcher Award

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Dr. Dmitri Lapotko | Automated Cancer Diagnostics | Best Researcher Award

Scorpido Photonics Inc | United States

Dr. Dmitri Lapotko is the pi, cto, and ceo at scorpidophotonics inc., and a pioneering researcher in the field of plasmonic nanobubbles. He invented laser-generated nano-explosions capable of detecting and treating lethal diseases such as cancers and malaria at the cellular level in real time, automating processes to minimize dependence on human expertise and reduce errors. His groundbreaking technology enables the instant detection of single cancer cells in vivo and selectively destroys them on-demand, achieving performance previously unattainable with conventional methods, Automated cancer diagnostics. Dr. lapotko has led numerous research initiatives, including the nih u01 project “harnessing cancer aggressiveness to overcome cancer resistance” and the nsf project “instant diagnosis of cancers with plasmonic nanobubbles,”. he has authored multiple scholarly documents in high-impact journals, with a total of 357 citations, an h-index of 8, i10-index of 7, and 349 citations, reflecting the influence and reach of his work in biomedical optics and nanomedicine. His contributions also extend to consultancy and industry projects focused on instant, automated, and minimally invasive detection of microscopic cancers in patients. With a consistent record of innovation, dr. lapotko continues to advance the frontiers of real-time cellular diagnostics and targeted therapy, merging cutting-edge photonics with life-saving medical applications.

Profiles: Orcid | Google Scholar

Featured Publication

Lapotko, D. (2009). Optical excitation and detection of vapor bubbles around plasmonic nanoparticles. Optics Express, 17(4), 2538–2556.

Lapotko, D. O., Lukianova, E., & Oraevsky, A. A. (2006). Selective laser nano‐thermolysis of human leukemia cells with microbubbles generated around clusters of gold nanoparticles. Lasers in Surgery and Medicine.

Lukianova-Hleb, E. Y., Ren, X., Sawant, R. R., Wu, X., Torchilin, V. P., & Lapotko, D. O. (2014). On-demand intracellular amplification of chemoradiation with cancer-specific plasmonic nanobubbles. Nature Medicine, 20(7), 778–784.

Lapotko, D. O., & Hleb, K. (2019). Diagnosis, removal, or mechanical damaging of tumor using plasmonic nanobubbles. U.S. Patent No. 10,471,159.

Lapotko, D. (2008). Plasmonic nanoparticle-generated photothermal bubbles and their biomedical applications. Nanomedicine, 4(7), 813–845.

Assoc. Prof. Dr. Gokhan Guven | Robotics | Best Researcher Award

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Assoc. Prof. Dr. Gokhan Guven | Robotics | Best Researcher Award

Mugla Sitki Kocman University | Turkey

Dr. Gokhan Guven is a Ph.D. Candidate in the department of curriculum and instruction at Mugla Sitki Kocman University, turkey, specializing in science education under the supervision of dr. yusuf sulun. he earned his bachelor’s degree in elementary science education from pamukkale university and completed his master’s in science education at mugla sitki kocman university, where his thesis focused on preservice elementary teachers’ reflection journal writing and epistemological beliefs in science and technology laboratory applications. Currently pursuing his doctoral studies in science education, dr. guven’s research interests include energy education, science teacher education, and science laboratory applications. throughout his academic career, he has served as a teaching assistant in various laboratory-based courses, including general biology, general physics, Robotics and general chemistry, contributing significantly to hands-on science instruction and pedagogy. his scholarly contributions have garnered 179 citations across 12 documents, with an h-index of 7, reflecting the impact and recognition of his research within the scientific and educational community. fluent in both english and turkish, Dr. guven continues to advance his research and academic pursuits, focusing on enhancing the quality and effectiveness of science education at both theoretical and practical levels.

Profiles: Scopus | Orcid

Featured Publications

Güven, G., Orhan Özen, S., & Şarlakkaya, K. (2025). Virtual reality applications integrated into the 5E learning model in environmental topics in science education. Research in Science & Technological Education. Advance online publication.

Kozcu Cakir, N., & Guven, G. (2025). Enhancing engineering design, scientific creativity, and decision-making skills in prospective science teachers through engineering design-based robotics coding applications. Research in Science & Technological Education. Advance online publication.

Güven, G., & ÖzüneL, Y. (2023). Arduino destekli robotik kodlama etkinlikleri ile ilkokul 2. sınıf doğal afetler konusunun öğretimi. Ege Bilimsel Araştırmalar Dergisi.

Güven, G., & Göçen Kabaran, G. (2023). Yenilenebilir enerji eğitimine yönelik bir öğretim tasarımı geliştirme ve değerlendirme. Eğitim Teknolojisi Kuram ve Uygulama.

Guven, G., Kozcu Cakir, N., Sulun, Y., Cetin, G., & Guven, E. (2022). Arduino-assisted robotics coding applications integrated into the 5E learning model in science teaching. Journal of Research on Technology in Education, 54(1), 1–20.

Ms. Siona Prasad | Automated Early VTE Detection | Best Researcher Award

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Ms. Siona Prasad | Automated Early VTE Detection | Best Researcher Award

Harvard Medical School | United States

Ms. Siona Prasad is a dedicated medical researcher and md candidate at harvard medical school, boston, massachusetts, pursuing her degree through the pathways program with an expected graduation. She graduated summa cum laude from harvard university with an a.b. in computer science and global health & health policy. Her academic and research journey reflects a strong interdisciplinary blend of medicine, data science, and global health innovation. with a research portfolio spanning prestigious institutions such as brigham and women’s hospital, mass general brigham, and boston children’s hospital, dr. prasad has contributed to advancements in cardiovascular risk prediction, ai-driven diagnostics, and digital health innovation. Her notable projects include developing machine learning algorithms for early disease detection and ai-powered diagnostic tools, Automated early VTE detection highlighting her expertise at the intersection of healthcare and technology. her scholarly work has been cited 9 times across 6 published documents, demonstrating growing recognition within the academic community, and she holds an h-index of 3, reflecting the impact and relevance of her contributions to biomedical research. driven by a vision to integrate artificial intelligence into clinical decision-making, dr. siona prasad continues to shape the future of computational medicine and global health equity.

Profiles: Scopus | Orcid

Featured Publications

Prasad, S., Dykes, P. C., Schreiber, R., Hijjawi, S., Nawab, K., Kim, A., Lipsitz, S., Syrowatka, A., Samal, L., Bates, D. W., et al. (2025). Development of an algorithm for estimating the likelihood of venous thromboembolism in primary care using structured and unstructured electronic health record data. American Journal of Hematology. Advance online publication.

Rao, A. S., Prasad, S., Lee, R. S., Farrell, S., McKinley, S., & Succi, M. D. (2025). Development and evaluation of an artificial intelligence–powered surgical oral examination simulator: A pilot study. Mayo Clinic Proceedings: Digital Health. Advance online publication.

Alayande, B. T., Pai, M., Prasad, S., Abimpaye, M., Bakorimana, L., Niyigena, A., Nkurunziza, J., Cubaka, V. K., Kateera, F., Fletcher, R., et al. (2023). Image-based surgical site infection algorithms to support home-based post-cesarean monitoring: Lessons from Rwanda. PLOS Global Public Health, 3(2), e0001584.

Prasad, S. (2022, May). Robustness of a visible image machine learning surgical site infection diagnostic algorithm when image quality is degraded. Presented at the Rwanda Health Research and Policy Symposium.

Prasad, S. (2022, April 8). Urban inversions of air pollution sources/sinks and uncertainty quantification to pinpoint determinants of poor air quality. Presented at the Joint Mathematics Meeting.