Mr. Emmanuel Ebikabowei Enemugha | AI-Based Robot Perception | Best Researcher Award

University Malaya Department of Mechanical Engineering | Nigeria

Mr. Enemugha Emmanuel Ebikabowei is a dedicated mechanical engineer and researcher, currently a Ph.d. Candidate in mechanical engineering at the University of Malaya, Malaysia, with specialization in computational fluid dynamics, gas-turbine performance, pump-impeller blade design, and energy systems optimization. He also serves as a lecturer in the department of mechanical engineering at Nigeria maritime university. His publication record on researchgate lists 5 documents with 69 reads, though his citation and h-index metrics are not publicly indicated. His scholarly work includes notable contributions such as a hybrid optimization of mixed-axial flow pump impellers using taguchi method, genetic algorithms, AI-Based Robot Perception and neural networks. additionally, He has conducted experimental analyses on firewood combustion efficiency for sustainable cooking in bayelsa state, Nigeria. His research is shaping the future of efficient pump systems and clean energy solutions for both industrial and community-scale applications.

Profile: Orcid

Featured Publications

Enemugha, E. E., Ab Karim, M. S. B., & Nik Ghazali, N. N. B. (2025). Hybrid optimisation of mixed-axial flow pump impellers parameter using Taguchi, genetic algorithms, and artificial neural networks. Next Research.

Enemugha, E. E., & Munuakuro, A. E. (2025). Experimental analysis of firewood combustion efficiency and fuel consumption patterns for sustainable cooking in Bayelsa State, Nigeria. International Journal for Research in Applied Science and Engineering Technology, 13(4).

Enemugha, E. E. (2025). The effects of impeller blade count on centrifugal pump performance and efficiency under different operating conditions: A comparison of numerical prediction. International Journal for Research in Applied Science and Engineering Technology, 13(4).

Bratua, I., Burubai, W., & Enemugha, E. E. (2025). Comparative analysis of fuelwood weight loss and energy efficiency in Bayelsa State, Nigeria. World Journal of Advanced Engineering Technology and Sciences, 14(3).

Enemugha, E. E., Ab Karim, M. S., & Nik Ghazali, N. N. (2025). Comprehensive optimization of centrifugal pump performance through the integration of the Taguchi method and polynomial regression models. Global Journal of Engineering and Technology Advances, 22(2).

Mr. Nitin Desai | Industrial Robotics | Best Researcher Award

Indian Institute of Technology Kharagpur | India

Dr. Nitin Desai is a distinguished researcher in industrial robotics and manufacturing automation, with a strong record of interdisciplinary contributions in both software and hardware domains. He is currently pursuing a Ph.d. in robotics at the Indian Institute of Technology Kharagpur, focusing on high-precision 6d pose estimation for robot manipulators using deep learning and 3d vision techniques. His expertise spans computer vision, vision-language models, large language models, reinforcement learning, Industrial Robotics and generative ai—applied to robotic motion planning, grasping, and autonomous decision-making. prior to his doctoral work, he earned his M.Tech. in cad cam and automation and robotics from veermata jijabai technological institute, mumbai, B.E. In mechanical engineering from dkte society’s textile & engineering institute, Kolhapur. Dr. Desai has served as a research scholar at the centre of excellence in advanced manufacturing technology, iit kharagpur, and as a technical consultant at scale ai, contributing to generative ai model training and data annotation for advanced automation systems. With 1 citation, 3 published documents, and an h-index of 1, his scholarly work reflects growing recognition in the academic community. his ongoing research continues to bridge artificial intelligence, robotics, and industrial automation for next-generation intelligent systems.

Profile: Scopus