Mr. Naveen Kumar | Performance Management | Best Scholar Award

Jawaharlal Nehru university, New Delhi | India

Naveen Kumar is an experienced academician in computer engineering, currently serving as an Assistant Professor at the Panipat Institute of Engineering and Technology, Haryana, since 2014. He holds a Master of Technology in Computer Engineering from the University Institute of Engineering and Technology, Kurukshetra University, and a Bachelor of Technology in Computer Engineering from Maharishi Markandeshwar Engineering College, Mullana. His teaching career spans over fifteen years, including previous roles as Lecturer at N.C. College of Engineering and Technology, Panipat. He has qualified both the GATE (2018) and UGC-NET (July and December 2018), reflecting his strong academic foundation. His research interests include genetic algorithms, optimization techniques, digital image processing, data structures, and artificial intelligence. Naveen Kumar has published research papers in reputed journals, focusing on comparative analyses of genetic algorithm operators and their applications in solving the Traveling Salesman Problem. He has actively participated in various national workshops and faculty development programs on topics such as big data, cyber forensics, high-performance computing, and intellectual property rights. Recognized for his commitment to academic excellence, he has contributed to departmental and institutional development activities and accreditation processes. Naveen Kumar continues to inspire students and peers through his dedication to research, teaching innovation, and technical education advancement.

Profile: Google Scholar

Featured Publications

Kumar, N., & Karambir, R. (2012). A comparative analysis of PMX, CX and OX crossover operators for solving traveling salesman problem. International Journal of Latest Research in Science and Technology, 1(2), 98–101.

Kumar, N., & Chaudhary, A. (2024). Surveying cybersecurity vulnerabilities and countermeasures for enhancing UAV security. Computer Networks, 252, 110695.

Kumar, N. (2012). A genetic algorithm approach to study traveling salesman problem. Journal of Global Research in Computer Science, 3(3), 33–37.

Kumar, N., Chaudhary, V., & Dubey, S. K. (2025). Cybersecurity and emerging technologies: Challenges and opportunities. In Cybersecurity preparedness among Indian firms: Opportunities, challenges, and strategies (pp. xx–xx).

Kumar, N., Kumar, G., & Chaudhary, V. (2024). Redefining national security threats in cyberspace: A challenging problem. In Proceedings of the International Seminar on Emerging Threats to National Security: Cyber and Information Warfare (pp. xx–xx).

D. Mohatsim mahetaji | Decision-making and Problem-solving | Best Researcher Award

Parul University | India

Dr. Mohatsim A. Mahetaji is an emerging scholar in petroleum engineering and geomechanics who completed his PhD (2024) at the Department of Petroleum Engineering, School of Energy Technology, Pandit Deendayal Energy University, following an MTech in Petroleum and a BE in Mechanical Engineering. He has held roles as Teaching Assistant, Research & Teaching Assistant (2019-2023) and Research Associate (Oct–Dec 2023) before becoming an Assistant Professor in January 2025 at Parul Institute of Technology. His research spans computational analysis, artificial intelligence / machine learning, data science in drilling and well-bore stability, geomechanics and carbon capture & storage, with several peer-reviewed publications in high-impact journals. He has developed new 3D failure criteria for in-situ rock, and applied machine learning in pore-pressure prediction and wellbore mud weight optimisation. His work reflects a strong modelling and simulation orientation aimed at cost-effective, sustainable hydrocarbon exploration and production. While detailed citation counts and h-index are not publicly available, his trajectory and output indicate rising academic impact. Dr. Mahetaji continues to innovate at the intersection of AI/ML and geosciences, contributing to both theory (failure criteria) and applied drilling design, positioning him as a promising contributor in energy technology and subsurface engineering.

Featured Publications

Mahetaji, M., & Brahma, J. (2024). A critical review of rock failure criteria: A scope of machine learning approach. Engineering Failure Analysis, 159, 107998.

Mahetaji, M., Brahma, J., & Sircar, A. (2020). Pre-drill pore pressure prediction and safe well design on the top of Tulamura anticline, Tripura, India: A comparative study. Journal of Petroleum Exploration and Production Technology, 10(3), 1021–1049.

Mahetaji, M., & Brahma, J. (2024). Prediction of minimum mud weight for prevention of breakout using new 3D failure criterion to maintain wellbore stability. Rock Mechanics and Rock Engineering, 57(3), 2231–2252.

Mahetaji, M., Brahma, J., & Vij, R. K. (2023). A new extended Mohr-Coulomb criterion in the space of three-dimensional stresses on the in-situ rock. Geomechanics and Engineering, 32(1), 49–68.

Mahetaji, M., Brahma, J., & Vij, R. K. (2023). Multivariable regression 3D failure criteria for in-situ rock. Earth Sciences Research Journal, 27(3), 273–287.