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.

Mr. Ashuvendra Singh | Structural Damage Detection | Best Researcher Award

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Mr. Ashuvendra Singh | Structural Damage Detection | Best Researcher Award

National Institute of Technology | India

Mr. Ashuvendra Singh is a dedicated academic and research professional currently serving as Assistant Professor and Head of the Department of Civil Engineering at Dev Bhoomi Uttarakhand University, Dehradun. He also leads the Internal Quality Assurance Cell (IQAC) and manages the Dev Bhoomi Incubation & Innovation Foundation, where he actively promotes innovation, research, and entrepreneurship through startup mentoring, hackathons, and industry collaborations. His research focuses on structural health monitoring, vibration-based damage detection, and the application of machine learning techniques such as GNN, SVM, and DANN for predictive modeling and data analysis. He has published numerous research papers in reputed national and international journals and has collaborated with external research institutions on advanced structural studies. In addition to his academic and research contributions, he plays a key role in institutional quality enhancement, faculty development, and policy implementation, while fostering a culture of innovation and excellence in higher education.

Profiles: Scopus | Orcid | Google Scholar 

Featured Publications

AK Bhatt, H., Raj, H., Sharma, V. B., Biswas, S., Singh, A., Silori, R., & Pandey, M. (2025). Advancements in pothole detection techniques: A comprehensive review and comparative analysis. Discover Artificial Intelligence, 5(1), 1–27.

Singh, A., & Kaloni, S. (2025). Leveraging vibration sensor data and machine learning for effective structural health monitoring of the KW51 bridge. Innovative Infrastructure Solutions, 10(12), 1–18.

Christy, H. J., Pati, P., Malathi, H., Singh, A., Kalele, G., & Piakaray, D. (2025). Application of Island Biogeography Theory in designing urban biodiversity reserves. Natural and Engineering Sciences, 10(2), 469–481.

Dolma, N., Tiyasha, T., & Singh, A. (2025). A case study on land subsidence occurrence in Joshimath, Uttarakhand. Discover Geoscience, 3(1), 1–20.

Singh, A., Kumar, S., & Ranger, A. (2024). Enhancing manufacturing strength through fly ash-based processes using genetic-chimp optimized adaptable gradient boosting. Proceedings on Engineering, 6(1), 397–406.

Prof. Xiangchao Shi | Computational Methods | Best Researcher Award

Published on by Global Energy Awards

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.