Dr. Krishnamoorthy Ramalingam is a Postdoctoral Fellow at Universiti Sains Malaysia, specializing in AI-driven biofuel optimization and nanocatalyst-enhanced biogas systems. He holds a Ph.D. in Automobile Engineering from Anna University (MIT Campus), where he was highly recommended, and an M.E. in Internal Combustion Engineering. His research combines machine learning and optimization techniques to enhance biofuel and biogas yield prediction, alongside experimental validation of ammonia/hydrogen fuel blends and advanced combustion strategies. With over 1400 citations and an h-index of 21, Dr. Ramalingam has published influential work in journals such as Fuel, Renewable Energy, Results in Engineering, and Scientific Reports. He serves as an Academic Editor for peer-reviewed journals and is an active member of SAE and IAENG. His contributions have been recognized for excellence in technical writing and interdisciplinary innovation. Currently, he is pursuing Assistant Professor roles in Mechanical Engineering, with a vision to integrate conversational AI agents into experimental workflows—enabling real-time guidance, adaptive optimization, and reproducible research in sustainable energy systems.
Dr. Krishnamoorthy Ramalingam is a Postdoctoral Fellow at Universiti Sains Malaysia, specializing in AI-driven biofuel optimization and nanocatalyst-enhanced biogas systems. He holds a Ph.D. in Automobile Engineering from Anna University (MIT Campus), where he was highly recommended, and an M.E. in Internal Combustion Engineering. His research combines machine learning and optimization techniques to enhance biofuel and biogas yield prediction, alongside experimental validation of ammonia/hydrogen fuel blends and advanced combustion strategies. With over 1400 citations and an h-index of 21, Dr. Ramalingam has published influential work in journals such as Fuel, Renewable Energy, Results in Engineering, and Scientific Reports. He serves as an Academic Editor for peer-reviewed journals and is an active member of SAE and IAENG. His contributions have been recognized for excellence in technical writing and interdisciplinary innovation. Currently, he is pursuing Assistant Professor roles in Mechanical Engineering, with a vision to integrate conversational AI agents into experimental workflows—enabling real-time guidance, adaptive optimization, and reproducible research in sustainable energy systems.