Dr. Nongmaithem Nandini Devi

Dr. Nongmaithem Nandini Devi is a distinguished scholar holding a Ph.D. in Computer Science and Engineering from the National Institute of Technology, Meghalaya. Her pioneering research delves into the development of advanced energy trading mechanisms within smart grid systems, focusing on innovative pricing schemes, enhanced security and privacy protocols for participants, and strategic electric vehicle (EV) charging station deployment. Dr. Devi's work aims to optimize travel time and minimize user inconvenience, contributing significantly to the evolving landscape of sustainable energy management. Her interdisciplinary approach integrates multiple criteria decision-making algorithms, game-theoretical models, and blockchain architectures, ensuring robust, transparent, and efficient solutions. Dr. Devi's contributions not only advance academic discourse but also offer practical applications for the future of smart energy systems and electric mobility. 

Dr. Nongmaithem Nandini Devi has recently joined the faculty at UPES. Prior to this, she served as a Software Developer at Aricent Technology, Gurgaon, India

Dr. Nongmaithem Nandini Devi’s research focuses on the intersection of smart energy systems, computational intelligence, and secure energy trading. Her work focuses on developing advanced energy trading mechanisms within smart grids, incorporating innovative pricing schemes, robust security and privacy protocols, and strategic electric vehicle (EV) charging station deployment to optimize travel time and reduce user inconvenience. She explores the integration of blockchain architectures to enhance transparency and security in energy transactions while leveraging game-theoretical models and multi-criteria decision-making algorithms for efficient energy distribution and resource allocation. Additionally, she incorporates deep learning techniques to improve smart grid operations, utilizing neural networks for demand prediction, anomaly detection, and grid automation. Through her interdisciplinary approach, Dr. Devi aims to contribute to the advancement of sustainable energy management and intelligent mobility solutions. 

Dr. Nongmaithem Nandini Devi believes that effective teaching extends beyond the mere transmission of knowledge—it is about fostering critical thinking, creativity, and problem-solving skills that empower students to tackle real-world challenges. She emphasizes an interactive and application-driven learning environment, integrating interdisciplinary projects and practical applications to bridge the gap between theory and practice. By incorporating tools such as Python, Jupyter Notebooks, MATLAB, and real-world datasets, she ensures that students develop both a strong conceptual foundation and hands-on technical expertise relevant to industry and research. Dr. Devi views education as a transformative process, where her role as an educator is to inspire curiosity, nurture innovation, and prepare students to become ethical, competent, and forward-thinking contributors to society. 

Dr. Nongmaithem Nandini Devi teaches a variety of courses, including:

• Database Management System (DBMS): The core principles of Database Management Systems (DBMS) revolve around data organization, integrity, security, and efficiency. A DBMS ensures structured storage, retrieval, and management of data while maintaining consistency through ACID (Atomicity, Consistency, Isolation, Durability) properties. It also enforces access control, optimizes query performance, and supports concurrency to facilitate reliable and scalable data handling across various applications.
• Computer Graphics: The core principles of Computer Graphics focus on the efficient creation, manipulation, and representation of visual content. Key aspects include geometric modelling for object representation, rendering techniques for realistic image generation, and transformations to control object positioning and viewing. Additionally, principles such as lighting, shading, and animation enhance realism and interactivity in graphical applications.
• Applied Machine Learning: Foundations of supervised and unsupervised learning, neural networks, and real-world projects leveraging Python (scikit-learn, TensorFlow).
• Object Oriented Programming: The core principles of Object-Oriented Programming (OOP) in Java revolve around encapsulation, inheritance, polymorphism, and abstraction. Encapsulation ensures data security by restricting direct access to object fields, while inheritance promotes code reusability by allowing classes to derive properties from existing ones. Polymorphism enables method overriding and dynamic behaviour, whereas abstraction simplifies complex systems by exposing only essential details, making Java programs more modular, maintainable, and scalable. 

• Published impactful research in reputed journals like Energies, Journal of Parallel and Distributed Computing, Peer-to-Peer Networking and Applications, and IEEE Sensors Letters.
• Presented findings at international conferences, including the INDICON 2021. 

nongmaithem.devi@ddn.upes.ac.in