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

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.

Mr. Danyang Mei | Data Analysis Techniques | Best Researcher Award

Mr. Danyang Mei | Data Analysis Techniques | Best Researcher Award

Beihua Institute of Aerospace Engineering  | China

Mr. Mei Danyang is an accomplished researcher and engineer specializing in energy equipment design, drilling technology, and deep learning applications in mechanical systems. He has led and participated in several innovation and optimization projects related to hydraulic motors, drilling tools, and equipment industrialization. His research focuses on advanced modeling and prediction techniques, particularly using deep learning for energy-efficient drilling torque prediction. Mr. Danyang has received multiple national-level awards, including top prizes in the China Postgraduate Energy Equipment Innovation Design Competition, along with several academic scholarships and honors for excellence and innovation. Professionally, he has contributed to the design and development of large-diameter raise boring machines, downhole tools, and machine tool electrical systems, demonstrating strong expertise in structural design, vibration analysis, and system integration.

Profile: Scopus 

Featured Publications

Cao, W., Mei, D., Guo, Y., & Ghorbani, H. (2025). Deep learning approach to prediction of drill-bit torque in directional drilling sliding mode: Energy saving. Measurement: Journal of the International Measurement Confederation.