Chaitanya Kumar Mankala | Machine Learning | Best Computer Engineering Award Published on 24/10/2025 by Engineering Scientist Dr. Chaitanya Kumar Mankala | Machine Learning | Best Computer Engineering Award Villanova University | United States Dr. Chaitanya Kumar Mankala’s research focuses on advancing sustainable, scalable, and intelligent computing through the convergence of artificial intelligence, serverless architectures, and neuroidal network models. His work in real-time natural language processing emphasizes the development of energy-efficient and low-latency AI systems using cloud-native parallel processing on platforms such as AWS, enabling large-scale language models to operate dynamically with minimal environmental impact and operational cost. His contributions to evolutionary artificial neuroidal networks propose next-generation neural architectures capable of adaptively restructuring themselves through evolutionary algorithms to enhance learning efficiency, fault tolerance, and inference accuracy across diverse data environments. By integrating distributed serverless infrastructure with neuromorphic design principles, his research addresses limitations in current AI scalability, offering frameworks that support autonomous decision-making and real-time processing for healthcare, cybersecurity, and industrial automation. His conference work on the Next Generation Artificial Neural Network further explores biologically inspired computational models that bridge cognitive mechanisms with advanced deep learning, paving the way for highly interpretable, resilient, and self-evolving AI systems. Collectively, his research advances the paradigm of intelligent computing by integrating sustainability, scalability, and adaptive learning, contributing to the future of autonomous AI systems deployed on edge and cloud environments for mission-critical applications. Profile: Orcid | Google Scholar Featured Publications Mankala, C. K., & Silva, R. J. (2025). Sustainable real-time NLP with serverless parallel processing on AWS. Information, 16(10). https://doi.org/10.3390/info16100903 Mankala, C. K. (2025). Evolutionary artificial neuroidal network using serverless architecture [Doctoral dissertation]. Mankala, C. K., & Silva, R. (2023, November 16). Next generation artificial neural network. In Proceedings of the ICEHTMC Conference.
Dr. Chaitanya Kumar Mankala’s research focuses on advancing sustainable, scalable, and intelligent computing through the convergence of artificial intelligence, serverless architectures, and neuroidal network models. His work in real-time natural language processing emphasizes the development of energy-efficient and low-latency AI systems using cloud-native parallel processing on platforms such as AWS, enabling large-scale language models to operate dynamically with minimal environmental impact and operational cost. His contributions to evolutionary artificial neuroidal networks propose next-generation neural architectures capable of adaptively restructuring themselves through evolutionary algorithms to enhance learning efficiency, fault tolerance, and inference accuracy across diverse data environments. By integrating distributed serverless infrastructure with neuromorphic design principles, his research addresses limitations in current AI scalability, offering frameworks that support autonomous decision-making and real-time processing for healthcare, cybersecurity, and industrial automation. His conference work on the Next Generation Artificial Neural Network further explores biologically inspired computational models that bridge cognitive mechanisms with advanced deep learning, paving the way for highly interpretable, resilient, and self-evolving AI systems. Collectively, his research advances the paradigm of intelligent computing by integrating sustainability, scalability, and adaptive learning, contributing to the future of autonomous AI systems deployed on edge and cloud environments for mission-critical applications.
Dr. Chaitanya Kumar Mankala’s research focuses on advancing sustainable, scalable, and intelligent computing through the convergence of artificial intelligence, serverless architectures, and neuroidal network models. His work in real-time natural language processing emphasizes the development of energy-efficient and low-latency AI systems using cloud-native parallel processing on platforms such as AWS, enabling large-scale language models to operate dynamically with minimal environmental impact and operational cost. His contributions to evolutionary artificial neuroidal networks propose next-generation neural architectures capable of adaptively restructuring themselves through evolutionary algorithms to enhance learning efficiency, fault tolerance, and inference accuracy across diverse data environments. By integrating distributed serverless infrastructure with neuromorphic design principles, his research addresses limitations in current AI scalability, offering frameworks that support autonomous decision-making and real-time processing for healthcare, cybersecurity, and industrial automation. His conference work on the Next Generation Artificial Neural Network further explores biologically inspired computational models that bridge cognitive mechanisms with advanced deep learning, paving the way for highly interpretable, resilient, and self-evolving AI systems. Collectively, his research advances the paradigm of intelligent computing by integrating sustainability, scalability, and adaptive learning, contributing to the future of autonomous AI systems deployed on edge and cloud environments for mission-critical applications.
Dr. Chaitanya Kumar Mankala’s research focuses on advancing sustainable, scalable, and intelligent computing through the convergence of artificial intelligence, serverless architectures, and neuroidal network models. His work in real-time natural language processing emphasizes the development of energy-efficient and low-latency AI systems using cloud-native parallel processing on platforms such as AWS, enabling large-scale language models to operate dynamically with minimal environmental impact and operational cost. His contributions to evolutionary artificial neuroidal networks propose next-generation neural architectures capable of adaptively restructuring themselves through evolutionary algorithms to enhance learning efficiency, fault tolerance, and inference accuracy across diverse data environments. By integrating distributed serverless infrastructure with neuromorphic design principles, his research addresses limitations in current AI scalability, offering frameworks that support autonomous decision-making and real-time processing for healthcare, cybersecurity, and industrial automation. His conference work on the Next Generation Artificial Neural Network further explores biologically inspired computational models that bridge cognitive mechanisms with advanced deep learning, paving the way for highly interpretable, resilient, and self-evolving AI systems. Collectively, his research advances the paradigm of intelligent computing by integrating sustainability, scalability, and adaptive learning, contributing to the future of autonomous AI systems deployed on edge and cloud environments for mission-critical applications.
Dr. Chaitanya Kumar Mankala’s research focuses on advancing sustainable, scalable, and intelligent computing through the convergence of artificial intelligence, serverless architectures, and neuroidal network models. His work in real-time natural language processing emphasizes the development of energy-efficient and low-latency AI systems using cloud-native parallel processing on platforms such as AWS, enabling large-scale language models to operate dynamically with minimal environmental impact and operational cost. His contributions to evolutionary artificial neuroidal networks propose next-generation neural architectures capable of adaptively restructuring themselves through evolutionary algorithms to enhance learning efficiency, fault tolerance, and inference accuracy across diverse data environments. By integrating distributed serverless infrastructure with neuromorphic design principles, his research addresses limitations in current AI scalability, offering frameworks that support autonomous decision-making and real-time processing for healthcare, cybersecurity, and industrial automation. His conference work on the Next Generation Artificial Neural Network further explores biologically inspired computational models that bridge cognitive mechanisms with advanced deep learning, paving the way for highly interpretable, resilient, and self-evolving AI systems. Collectively, his research advances the paradigm of intelligent computing by integrating sustainability, scalability, and adaptive learning, contributing to the future of autonomous AI systems deployed on edge and cloud environments for mission-critical applications.
Dr. Chaitanya Kumar Mankala’s research focuses on advancing sustainable, scalable, and intelligent computing through the convergence of artificial intelligence, serverless architectures, and neuroidal network models. His work in real-time natural language processing emphasizes the development of energy-efficient and low-latency AI systems using cloud-native parallel processing on platforms such as AWS, enabling large-scale language models to operate dynamically with minimal environmental impact and operational cost. His contributions to evolutionary artificial neuroidal networks propose next-generation neural architectures capable of adaptively restructuring themselves through evolutionary algorithms to enhance learning efficiency, fault tolerance, and inference accuracy across diverse data environments. By integrating distributed serverless infrastructure with neuromorphic design principles, his research addresses limitations in current AI scalability, offering frameworks that support autonomous decision-making and real-time processing for healthcare, cybersecurity, and industrial automation. His conference work on the Next Generation Artificial Neural Network further explores biologically inspired computational models that bridge cognitive mechanisms with advanced deep learning, paving the way for highly interpretable, resilient, and self-evolving AI systems. Collectively, his research advances the paradigm of intelligent computing by integrating sustainability, scalability, and adaptive learning, contributing to the future of autonomous AI systems deployed on edge and cloud environments for mission-critical applications.
Mankala, C. K., & Silva, R. J. (2025). Sustainable real-time NLP with serverless parallel processing on AWS. Information, 16(10). https://doi.org/10.3390/info16100903 Mankala, C. K. (2025). Evolutionary artificial neuroidal network using serverless architecture [Doctoral dissertation]. Mankala, C. K., & Silva, R. (2023, November 16). Next generation artificial neural network. In Proceedings of the ICEHTMC Conference.