Yulia Yugay | Nanotechnology |Research Excellence Award

Dr. Yulia Yugay | Nanotechnology |Research Excellence Award

Federal Scientific Center of the East Asia Terrestrial Biodiversity, Far Eastern Branch of the Russian Academy of Sciences | Russia

Dr. Yulia A. Yugay is a plant biotechnologist and molecular biologist with a PhD in Biological Sciences, currently serving as a Senior Research Scientist at the Laboratory of Bionanotechnology and Biomedicine, Federal Scientific Center of the East Asia Terrestrial Biodiversity, Far Eastern Branch of the Russian Academy of Sciences. Her academic training is rooted in advanced biological sciences, with specialization in plant biotechnology and molecular genetics, and her professional experience spans fundamental research and applied innovation within leading national research institutes. Her research interests focus on plant cell and tissue cultures, molecular mechanisms of stress physiology, and the integration of bionanotechnology for the development of biologically active nanomaterials and functional biomolecules with applications in sustainable agriculture, biotechnology, and biomedicine. Dr. Yugay has authored 29 peer-reviewed scientific documents published in Q1–Q2 journals indexed in Web of Science and Scopus, with a strong record as first, corresponding, and co-author; her scholarly impact is reflected through an established h-index-10 and substantial citation record as indexed in Scopus and Web of Science, demonstrating consistent international visibility. In addition to research, she actively contributes to the scientific community as a peer reviewer for international journals, including MDPI titles. Her achievements highlight scientific excellence, interdisciplinary innovation, and meaningful translational potential, positioning her as a leading contributor to modern plant biotechnology and bionanotechnology research.

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Featured Publications

Mona Ali | Computer Science and Artificial Intelligence | Research Excellence Award

Prof. Mona Ali | Computer Science and Artificial Intelligence | Research Excellence Award

King Faisal University | Saudi Arabia

Dr. Mona Abdelbaset Sadek Ali is an Associate Professor of Computer Science specializing in artificial intelligence, machine learning, and image processing. She earned her PhD in Computer Science (Wireless Computer Communications) from Cardiff University, UK, after completing an MSc in Information Technology (Image Processing) and a BSc in Information Technology with honors from Cairo University. With extensive academic experience spanning the UK, Saudi Arabia, and Egypt, her research integrates deep learning, optimization techniques, computer vision, IoT, mobile security, and intelligent healthcare systems. Dr. Ali has authored over 30 peer-reviewed research articles published in high-impact Web of Science-indexed journals and conferences, achieving an h-index of approximately 17, with more than 871 citations and 29 research documents. Her work frequently appears in Q1 and Q2 journals such as Mathematics, Electronics, Sustainability, PLOS ONE, and Applied Sciences. She has led and co-led numerous funded research projects supported by national and institutional bodies and has supervised multiple postgraduate MSc and PhD researchers. Her academic excellence has been recognized through competitive research funding and research poster awards. Overall, Dr. Ali’s career reflects sustained contributions to applied artificial intelligence and data-driven solutions with strong interdisciplinary and societal impact.

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Featured Publications


Tomato leaves diseases detection approach based on support vector machines

11th International Computer Engineering Conference (ICENCO), 246–250, 2015 · Citations: 222


Identifying two of tomatoes leaf viruses using support vector machine

Information Systems Design and Intelligent Applications, 2015 · Citations: 145


Detection of breast abnormalities of thermograms based on a new segmentation method

Federated Conference on Computer Science and Information Systems, 2015 · Citations: 78


Thermogram breast cancer prediction approach based on neutrosophic sets and fuzzy c-means algorithm

IEEE Engineering in Medicine and Biology Conference, 2015 · Citations: 76


A hybrid segmentation approach based on neutrosophic sets and modified watershed: A case of abdominal CT liver parenchyma

11th International Computer Engineering Conference (ICENCO), 2015 · Citations: 70