Rate My Professor Anish Jindal

Jindal's research specializations include data analytics for smart city applications in domains such as smart homes, smart grids, healthcare, and transportation; green artificial intelligence and machine learning; cyber-physical systems and Internet-of-Things; programmable and scalable networking; resource-aware computing; wireless network and security; and energy optimization. His achievements include the Outstanding Ph.D. Dissertation Award from the IEEE Technical Committee on Scalable Computing (2019), IEEE Communications Society's Outstanding Young Researcher Award for the Europe, Middle East, and Africa region (2019), IEEE Hyper-intelligence Technical Committee Award for Excellence (Early Career Researcher, 2023), Fellowship of Advance HE (FHEA, 2021), and Associate Fellowship (AFHEA, 2020). Notable publications encompass the co-authored book Big Data Analytics: Theory, Techniques, Platforms, and Applications (Springer Nature Switzerland, 2024) and influential papers such as "Decision tree and SVM-based data analytics for theft detection in smart grid" (2016), "BEST: Blockchain-based secure energy trading in SDN-enabled intelligent transportation system" (2019), "SURVIVOR: A blockchain based edge-as-a-service framework for secure energy trading in SDN-enabled vehicle-to-grid environment" (2019), "A Multi-Modal Distributed Real-Time IoT System for Urban Traffic Control" (2024), and "Automated Artificial Intelligence Framework for Anomaly Detection in Healthcare SD-IoT Networks" (IEEE GLOBECOM, 2024). With over 3,600 citations, his work advances smart grid security, blockchain-enabled energy trading, sustainable computing, and IoT systems. Jindal has presented invited talks, including on data analytics in smart grids at Durham Energy Institute seminars.