Kostiantyn Kotenko | Operations Research and Statistical Optimization | Best Researcher Award

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Prof. Kostiantyn Kotenko | Operations Research and Statistical Optimization | Best Researcher Award

S.P.Timoshenko Institute of Mechanics | Ukraine

Dr. Kostyantin Kotenko is an Professor in the Department of Theoretical Mechanics at the Kyiv National University of Construction and Architecture (KNUCA), Ukraine, specialising in building structures and civil engineering systems. He holds the degree of Candidate of Technical Sciences (equivalent to PhD) and has developed extensive expertise in the dynamics of layered, or sandwich, shell structures with inhomogeneous fillers. A graduate of KNUCA, Dr. Kotenko’s academic background is rooted in the theory and design of complex structural systems, and his research focuses on the dynamic response and stability of multi-layered shells subjected to transient, impact, and nonstationary loads. Over his career, he has co-authored numerous influential papers in international journals, exploring dynamic responses of domes, cylindrical and conical shells with inhomogeneous elastic cores. His work has earned recognition for its analytical depth and contribution to advancing the field of structural dynamics. According to his Scopus profile, Dr. Kotenko has authored 10 scientific publications, received approximately 16 citations, and holds an h-index of 1, reflecting his active engagement and growing impact in the global research community. At KNUCA, he teaches theoretical mechanics and structural dynamics, supervises postgraduate research, and contributes to academic development through innovative research on layered shell mechanics. His continuing investigations into the stress–strain behaviour and stability of multi-layered systems have practical applications in modern civil and aerospace engineering. Dr. Kotenko’s scholarly contributions, combined with his dedication to education and applied mechanics, establish him as a prominent specialist in the field of dynamic analysis of layered and composite structural shells.

Featured Publications

Tushar Bhoite | Bayesian Networks and Decision Theory | Best Researcher Award

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Dr. Tushar Bhoite | Bayesian Networks and Decision Theory | Best Researcher Award

Dr. Tushar Bhoite | MES’s Wadia College of Engineering | India

Dr. Tushar Devidas Bhoite, Ph.D. in Mechanical Technology, M.E. in Machine Design, with over sixteen years of professional experience (including twelve in the automobile industry and four in academics), is a leading researcher and practitioner in integrating advanced IT technologies in auto-component manufacturing. His research interests encompass Industry 4.0, Industrial Internet of Things (IIoT), Digital Twin systems, Generative AI, predictive maintenance, neural and Bayesian networks, real-time monitoring, optimization and efficiency improvements in production environments. To date, he has authored 6 international journal papers and 3 international conference papers, co-authored 2 textbooks, and filed 2 patents, contributing to both theoretical and applied advancements. His master’s project, awarded from RGSTC Mumbai, stands as a landmark in his research portfolio, he has an h-index of 1 and over 1 citations as per his Scopus profile, reflecting strong scholarly impact. In his industrial roles, Dr. Bhoite has successfully led IOT implementations in assembly and press shops, improved Overall Equipment Effectiveness, standardized work systems, deployed TPM and Kaizen methodologies, and developed innovative solutions such as a wet-waste treatment machine. He currently serves as Assistant Professor in Automation & Robotics Engineering at MES’s Wadia College of Engineering, Pune, and continues consulting in production efficiency, resource optimization, and technology integration in manufacturing enterprises.

Profiles: Scopus | Google Scholar | Orcid

Featured Publications

Bhoite, T. D., Pawar, P. M., & Gaikwad, B. D. FEA based study of effect of radial variation of outer link in a typical roller chain link assembly. International Journal of Mechanical and Industrial Engineering, 1, 65–70.

Bhoite, T. D., & Buktar, R. B. (2025). Productivity enhancement in Indian auto component manufacturing supply chain with IoT using neural networks. Production, 35, e20240047.

Bhoite, T. D., Buktar, R. B., Mahalle, P. N., Khond, M. P., Pise, G. S., & More, Y. Y. (2025). Productivity enhancement in the Indian auto component manufacturing supply chain through IoT, digital twins with generative AI, and stacked encoder-enhanced neural networks. Operations Research Forum, 6(4), 143.

Bhoite, D. T., & Buktar, R. (2025). An investigation into revolutionizing auto component manufacturing: An IoT-based approach for improved productivity and waste elimination. Journal of Information Systems Engineering and Management, 10(9s), 409–429.

Bhoite, D. T., Buktar, R., & Kannukkadan, G. (2024). Leveraging IoT in auto component manufacturing to monitor surface roughness and tool temperature. Journal of Electrical Systems, 20(2s), 563–574.*