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.
Profile: 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.