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

Assoc. Prof. Dr. Adnan Ozsoy | Computational Methods | Best Researcher Award

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Assoc. Prof. Dr. Adnan Ozsoy | Computational Methods | Best Researcher Award

Hacettepe University | Turkey

Dr. Adnan Ozsoy is a computer engineering academic specializing in blockchain, cryptocurrencies, distributed systems, parallel computing, HPC, GPGPU technologies, and big data problems. He has led and contributed to multiple prestigious funded research projects covering efficient parallelization on GPUs, lattice-based cryptographic protocols, and NTRU-based cryptosystems. His current research focuses on blockchain applications across sectors such as health, land registry, digital identity, secure distributed storage, scalable microservices, high-rate message handling, voltage scaling on GPUs, data compression, SDR-based real-time signal detection, and sequence alignment. He has supervised numerous Ph.D. and M.S. theses in blockchain technologies, parallel and embedded systems, cryptography, and secure distributed computing. At Hacettepe University, he teaches core and advanced subjects including data structures, algorithms, parallel programming, and blockchain, and has pioneered Turkey’s first undergraduate and graduate blockchain course. His professional engagements include consultancy at NETGSM on big data architecture, cloud and container technologies, microservices, scalability challenges, and academic R&D outcomes. His career is further supported by several major international and national awards, invitations for seminars and trainings, and industry collaborations in GPU computing and blockchain technologies.

Erdogan, H. T., & Ozsoy, A. (2025). CUDA-supported 5G multi-access edge computing modifications on 5G-air-simulator. EURASIP Journal on Wireless Communications and Networking, 2025(1), 29.

Ozsoy, A., Nazli, M., Cankur, O., & Sahin, C. (2025). CUSMART: Effective parallelization of string matching algorithms using GPGPU accelerators. Frontiers of Information Technology & Electronic Engineering, 26(6), 877–895.

Cihan, S., Yılmaz, N., Ozsoy, A., & Beyan, O. D. (2025). A systematic review of the blockchain application in healthcare research domain: Toward a unified conceptual model. Medical & Biological Engineering & Computing, 63(5), 1319–1342.

Zorlu, O., & Ozsoy, A. (2024). A blockchain-based secure framework for data management. IET Communications, 18(10), 628–653.

Fisne, A., Kalay, A., Yavuz, F., Cetintepe, C., & Ozsoy, A. (2023). Energy-efficient computing for machine learning based target detection. Concurrency and Computation: Practice and Experience, 35(24), e7582.

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. Xiangchao Shi | Computational Methods | Best Researcher Award

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Prof. Xiangchao Shi | Computational Methods | Best Researcher Award

Southwest Petroleum University  | China

Professor Shi Xiangchao, Assistant Dean at the School of Petroleum and Natural Gas Engineering, Southwest Petroleum University, specializes in drilling acceleration, intelligent drilling systems, and rock mechanics. His pioneering work integrates finite element analysis and rock mechanics to enhance the coupling performance of PDC bits and positive displacement motors (PDMs), improving drilling efficiency and stability in complex formations. He has contributed significantly to deep and ultra-deep shale gas drilling technologies through collaborations with CNPC, Sinopec, and international universities. His research establishes strong theoretical and computational foundations for intelligent, efficient, and safe petroleum drilling operations.

Profile: Scopus | Orcid | Google Scholar  

Featured Publications

Liu, J., Xue, F., Dai, J., Yang, J., Wang, L., Shi, X., Dai, S., Hu, J., & Liu, C. (2025). Waveform features and automatic discrimination of deep and shallow microearthquakes in the Changning shale gas field, Southern Sichuan Basin, China. Journal of Applied Geophysics, 105850.

Dai, J., Liu, J., Yang, J., Xue, F., Wang, L., Shi, X., Dai, S., Hu, J., & Liu, C. (2025). Seismicity associated with hydraulic fracturing in Changning shale gas field, China: Constraints from source mechanisms, stress field and fluid overpressure thresholds. Journal of Rock Mechanics and Geotechnical Engineering.

Wang, Z., Shi, X., Jiao, Y., Chen, S., Wang, R., & Lv, Z. (2025). Integrated selection and design method for PDC bits and positive displacement motor. Petroleum.

Fan, C., Nie, S., Li, H., Pan, Q., Shi, X., Qin, S., Zhang, M., & Yang, Z. (2024). Geological characteristics and major factors controlling the high yield of tight oil in the Da’anzhai member of the western Gongshanmiao in the central Sichuan basin, China. Geomechanics and Geophysics for Geo-Energy and Geo-Resources, 10(1), 67.

Wang, Z., Shi, X., Chen, S., Jiao, Y., Wang, R., & Lv, Z. (2024). Enhancement on PDC bit based on Archimedean spiral control method. Petroleum Science Bulletin.