Shah Dad Hasil | Computational Methods | Research Excellence Award

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Mr. Shah Dad Hasil | Computational Methods | Research Excellence Award

University of Electronic Science and Technology of China | China

Mr. Shah Dad Hasil is an emerging researcher in computer science currently pursuing graduate studies at the University of Electronic Science and Technology of China. His academic work lies at the intersection of artificial intelligence, bioinformatics, and computational drug discovery, where he focuses on designing intelligent computational tools to accelerate biomedical research. His work integrates machine learning algorithms, molecular docking techniques, and molecular dynamics simulations to evaluate molecular interactions and predict the biological activity of potential therapeutic compounds. A major focus of his current research is the development of AI-based predictive models targeting Trypanosoma cruzi, the parasite responsible for Chagas disease, aiming to support the discovery of new antiviral and antiparasitic drug candidates. Hasil has also demonstrated interdisciplinary research interests, contributing to studies in renewable energy technologies and computational cryptography. His research outputs have appeared in several peer-reviewed publications, including articles published in the Journal of Marine Science and Engineering. In addition to his research contributions, he has strong programming expertise in Python and C++ and practical experience working with deep learning frameworks such as TensorFlow and PyTorch. His long-term academic goal is to pursue a Ph.D. and advance AI-driven methodologies that address critical challenges in drug discovery and biomedical science.

 

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Featured Publications

Dr. Adarsh Kumar Shukla | Computational Methods | Young Scientist Award

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Dr. Adarsh Kumar Shukla | Computational Methods | Young Scientist Award

Dr. Bhimrao Ambedkar Government Medical College | India

Dr. Adarsh Kumar Shukla is a motivated and results-driven professional with expertise in Environmental Toxicology, Clinical Bioinformatics, NGS Data Analysis, Pathway Analysis, Computer-Aided Drug Design, Structural Biology, Metabolomics, Computational Biology, and Computational Chemistry. Currently serving as Scientist-B at the Multidisciplinary Research Unit, Dr. Bhimrao Ramji Ambedkar Government Medical College, Kannauj, he has prior experience as a Scientist and Research Associate in Paediatric Cardiac Research at Sri Sathya Sai Sanjeevani Research Foundation, as well as academic and project coordination roles in biotechnology and medicinal plant research. He has coordinated national-level academic events and completed FDPs focused on healthcare innovation. Dr. Shukla has contributed significantly to Health-, Plant-, and Food-Informatics research, presented papers at several conferences, and holds a granted Indian patent for the development of crab-apple-based jelly sheets. His research interests encompass structural bioinformatics, human genomics, and nutritional biotechnology, with strong proficiency in in-silico tools, laboratory instrumentation, and data analysis. Skilled in programming languages such as R, Biopython, and Bioperl, he combines computational and experimental approaches to address complex biomedical challenges.sics.

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Featured Publications

Shukla, A. K., & Kukshal, P. (2025). Computational simulations aided prioritization of genomic targets for congenital heart disease (CHD) against developmental toxicity. Reproductive Toxicology, 108, 108940.

Shukla, A. K., & Kumar, A. (2025). A chemoinformatics study to prioritization of anticancer orally active lead compounds of pearl millet against adhesion G protein-coupled receptor. Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy, 334, 125960.

Jha, R. K., Shukla, A. K., Kumari, A., & Kumar, A. (2025). Virtual screening of potential orally active anti-bacterial compounds of finger millet. Vegetos, 38(3), 1237–1248.

Jain, S., Shukla, A. K., Deepika, Panwar, S., Kumari, A., Yadav, A. K., & Kumar, A. (2024). Revolutionizing disease treatment through bioengineered probiotics and glucagon‐like peptide 1 (GLP‐1) based strategies: A path towards effective cures. Food Bioengineering, 2024, 1.

Panwar, S., Pal, S., Shukla, A. K., Kumar, A., & Sharma, P. K. (2024). Identification of micronutrient deficiency related miRNA and their targets in Triticum aestivum using bioinformatics approach. Ecological Genetics and Genomics, 31, 100236.

Prof. Dr. Petko Petkov | Matrix Analysis | Best Researcher Award

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Prof. Dr. Petko Petkov | Matrix Analysis | Best Researcher Award

Bulgarian Academy of Sciences | Bulgaria

Dr. Petko Petkov is a distinguished Professor of Control Theory at the Department of Systems and Control, Technical University of Sofia, where he has served since 1995. He earned his M.S. and Ph.D. degrees in Control Engineering from the same university in 1971 and 1979, respectively. With an impressive academic career, he has coauthored over 160 scientific papers and several influential books, including Computational Methods for Linear Control Systems (1991), Perturbation Theory for Matrix Equations (2003), Robust Control Design with MATLAB (2005, 2013), Design of Embedded Robust Control Systems using MATLAB®/Simulink® (2018), Perturbation Methods in Matrix Analysis and Control (2020), and The Numerical Jordan Form (2024). A full member of the Bulgarian Academy of Sciences and a member of the AMS, Dr. Petkov’s research focuses on matrix computations, control theory and engineering, robust and robot control, UAV control, and numerical methods and software for control systems design, particularly emphasizing computational methods and matrix analysis.

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Featured Publications

PH Petkov (2025). Probabilistic perturbation bounds of matrix decompositions. Numerical Linear Algebra with Applications 32 (1), e2582

V Angelova, M Konstantinov, P Petkov (2024). Asymptotic and Probabilistic Perturbation Analysis of Controllable Subspaces. Computation

V Angelova, P Petkov (2024). Componentwise perturbation analysis of the Singular Value Decomposition of a matrix. Applied Sciences 14 (4), 1417

PH Petkov (2022). Componentwise perturbation analysis of the QR decomposition of a matrix. Mathematics 10 (24), 4687

PH Petkov, MM Konstantinov (2022). The numerical Jordan form. Linear Algebra and its Applications 638, 1-45