Mansoor Showkat | Computational Neuroscience | Best Researcher Award

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Mr. Mansoor Showkat | Computational Neuroscience | Best Researcher Award

Mr. Mansoor Showkat | SKUAT-Kashmir | India

Mansoor Showkat is a researcher in Plant Biotechnology with an M.Sc. from the University of Agricultural Sciences, Bangalore, and a B.Sc. (Hons.) in Horticulture from Sher-e-Kashmir University of Agricultural Sciences and Technology of Kashmir. His research expertise spans molecular biology, computational biology, bioinformatics, and tissue culture, with particular emphasis on antifungal compound analysis, gene transformation, and plant-pathogen interactions. Mansoor has contributed to several peer-reviewed publications and book chapters, focusing on the in-silico and in-vitro evaluation of bioactive compounds such as cordycepin, molecular mechanisms of stress responses, and secondary metabolite profiling in plants. His research projects include genetic transformation studies, metabolomics-based investigations, and the use of omics tools for crop improvement. He has actively participated in numerous international workshops, conferences, and webinars related to biotechnology, bioinformatics, and genomics. Mansoor has achieved significant academic recognition, including national rankings in competitive examinations by the Indian Council of Agricultural Research. His scientific impact is reflected by a citation count of 15, an h-index of 2, and an i10-index of 0, highlighting his growing contribution to molecular and agricultural biotechnology research.

Profiles: Google Scholar| Research Gate | Linked In

Featured Publications

  1. Showkat, M., Narayanappa, N., Umashankar, N., & Saraswathy, B. P., et al. (2024). Optimization of fermentation conditions of Cordyceps militaris and in silico analysis of antifungal property of cordycepin against plant pathogens. Journal of Basic Microbiology, 64(10), e2400409.

  2. Fatimah, N., Ashraf, S., R. U., K. N., Anju, P. B., Showkat, M., Perveen, K., Bukhari, N. A., et al. (2024). Evaluation of suitability and biodegradability of the organophosphate insecticides to mitigate insecticide pollution in onion farming. Heliyon, 10(12).

  3. Margay, K. A. A. A. R., Ashraf, S., Fatimah, N., Jabeen, S. G., & Showkat, M., et al. (2024). Plant circadian clocks: Unravelling the molecular rhythms of nature. International Journal of Plant and Soil Science, 36(8), 596–617.

  4. Margay, A. R., Ashraf, S., Fatimah, N., Jabeen, S. G., Showkat, M., R. U., K. N., Gani, A., et al. (2024). Harnessing brassinosteroids for heat resilience in wheat: A comprehensive study.

  5. Showkat, M., Nagesha, N., Ashraf, S., Nayana, K., Bashir, S., Nair, A. S., et al. (2024). Cordycepin: A molecular Trojan horse against Fusarium oxysporum f. sp. cubense—A computational perspective.

Masoud Kargar | Computational Neuroscience | Best Researcher Award

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Assist. Prof. Dr. Masoud Kargar | Computational Neuroscience | Best Researcher Award

Assist. Prof. Dr. Masoud Kargar | Islamic Azad University | Iran

Dr. Masoud Kargar is an Assistant Professor in the Department of Computer Engineering at Islamic Azad University, Tabriz Branch, specializing in artificial intelligence, machine learning, reinforcement learning, and software system engineering. He earned his bachelor’s degree in applied mathematics, master’s degree in software engineering, and Ph.D. in software engineering with a focus on modularization of multi-programming software systems. Dr. Kargar has extensive academic experience, having taught a wide range of undergraduate, master’s, and doctoral courses in advanced programming, algorithms, software engineering, data mining, big data, project management, and natural language processing across multiple universities. He also serves as the Director of Information and Communication Technology and leads the development of various software systems. Dr. Kargar is a member of the editorial board of the Iranian Journal of Computer Science (Springer) and has published 19 documents, which have been cited 89 times, giving him an h-index of 6. His research contributions have significantly advanced the fields of machine learning and software engineering, and his academic leadership continues to inspire both students and colleagues. Dr. Kargar remains committed to fostering innovation and excellence in computer engineering education and research.

Profiles: Scopus | Google Scholar | Orcid | Research Gate

Featured Publications

Karegar, M., Isazadeh, A., Fartash, F., Saderi, T., & Navin, A. H. (2008). Data-mining by probability-based patterns. Proceedings of the 30th International Conference on Information Technology Interfaces, 28.

Kargar, M., Isazadeh, A., & Izadkhah, H. (2019). Multi-programming language software systems modularization. Computers & Electrical Engineering, 80, 106500.

Kargar, M., Isazadeh, A., & Izadkhah, H. (2017). Semantic-based software clustering using hill climbing. 2017 International Symposium on Computer Science and Software Engineering.

Kargar, M., Isazadeh, A., & Izadkhah, H. (2020). Improving the modularization quality of heterogeneous multi-programming software systems by unifying structural and semantic concepts. Journal of Supercomputing, 76(1), 17.

Navin, A. H., Fesharaki, M. N., Mirnia, M., & Kargar, M. (2007). Modeling of random variable with digital probability hyper digraph: Data-oriented approach. Proceedings of World Academy of Science, Engineering and Technology, 25, 25.

Bayani, A., & Kargar, M. (2024). LDCNN: A new arrhythmia detection technique with ECG signals using a linear deep convolutional neural network. Physiological Reports, 12(17), e16182.

Karegar, M., Saderi, T., Isazadeh, A., & Fartash, F. (2008). Electronic consulting in marketing. 2008 3rd International Conference on Information and Communication Technology, 5.