Dr. Joy Dutta earned his Ph.D. in Engineering from the Department of Computer Science and Engineering at Jadavpur University, India. He holds a B.Sc. in Physics (Honours) and completed his Post-B.Sc. B.Tech and M.Tech in Computer Science and Engineering from Calcutta University, India. Currently, Dr. Dutta is a Postdoctoral Fellow in the Department of Electrical Engineering at Khalifa University, Abu Dhabi, United Arab Emirates. He is a distinguished recipient of the Government of India’s prestigious Visvesvaraya Ph.D. Fellowship, awarded by the Ministry of Electronics and Information Technology (MeitY), India, in support of his full-time doctoral research.
Dr. Dutta brings a unique blend of industry and academic experience, actively advancing research in IoT, Edge-AI, and applications for social good. His expertise spans Applied Artificial Intelligence, Machine Learning, Blockchain, Data Analytics, and Smart City solutions, addressing contemporary challenges with innovative technology-driven approaches. A Senior Member of IEEE, Dr. Dutta is highly engaged with the global research community, serving as an active reviewer for top-tier IEEE, Elsevier, and Springer journals, holding executive roles within IEEE societies, and contributing as an organizing committee member and track chair for numerous international conferences in his field.
His substantial research output includes several publications in top-tier international journals and conferences, along with multiple book chapters that reach a global research audience. Through his work, Dr. Dutta consistently contributes to advancing knowledge and developing solutions at the intersection of cutting-edge technology and societal impact.
For more details, please visit Dr. Joy's website:
Edge-Resilience: Blockchain Empowered Resilient Edge Computing in Adversarial Environments
I worked on the project entitled “Edge-Resilience: Blockchain Empowered Resilient Edge Computing in Adversarial Environments,” from July 2022 to June 2024. The research area involved incorporating AI on Edge to make the system intelligent, self-explanatory, secure, and energy efficient. This project explored how edge computing and blockchain worked together for a secure and resilient Internet of Things (IoT). I elevated the existing Proof of Authentication (PoAh) consensus mechanism for IoT-based Blockchain by incorporating AI-driven enhancements for dynamic authentications, emphasizing transparency through Explainable AI (XAI) principles. My contribution optimized efficiency and security within blockchain networks, incorporating XAI to ensure transparency while preserving privacy. This novel approach was applied to healthcare, demonstrating its real-world relevance and impact in different practical scenarios. I developed this project from the ground up using Python, showcasing my expertise in translating complex theoretical ideas into practical, demonstrable solutions. This work not only reflects my ability to innovate within the blockchain and AI domains but also underscores my dedication to contributing meaningful advancements in critical sectors.
SEEMS: Smart Efficient Energy Management System for Charging Stations Infrastructure
Currently, I am working on the project entitled "Smart Efficient Energy Management System for Charging Stations Infrastructure (SEEMS)" since July 2024. The part of the project where I am working aims to optimize the placement and utilization of Mobile Charging Stations (MCS) using advanced machine learning techniques and multi-objective optimization algorithms. My role involves developing customized supervised ML algorithms to predict EV charging demands based on historical data and understanding spatial and temporal patterns for effective MCS placement. A game theory approach, integrated with ML-based predictions, supports strategic MCS dispatch to balance conflicting objectives like minimizing power losses, distributing EV charging load, and optimizing costs. My implementation plan includes data collection and preprocessing, algorithm development, simulation, testing, and validation using cross-validation techniques and performance metrics. This work enhances the robustness, efficiency, and scalability of the UAE’s EV charging infrastructure, ultimately improving service and optimizing resource utilization. Additionally, I am also developing a blockchain-based system for dynamic, context-aware energy auctions specifically designed for Mobile EV Charging.
Achievements:
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