Narendran Sobanapuram Muruganandam
Fellow
Narendran Sobanapuram Muruganandam completed his post-doc research in the Department of Information engineering and computer science at University of Trento, Italy. He did his PhD in Computer Science Engineering In 2023 from SASTRA University, Thanjavur, His work focuses on advanced AI‑driven forecasting of air pollution, particularly PM2.5and PM10. He co‑authored a novel SS‑LSTM deep learning model for particulate matter prediction, demonstrating superior performance over traditional approaches using data from Delhi. In 2023, he co‑developed a dynamic ensemble multivariate time‑series model for PM2.5 forecasting across multiple urban locations in Chennai. His research aims to enhance urban air quality management through scalable computational models along with Predictive Analytics and Climate change.
- AI-Driven Air Quality Forecasting created advanced machine learning and deep learning models, such as SS-LSTM, to reliably predict PM₂.₅ and PM₁₀ levels, exceeding standard statistical methods.
- Innovated Dynamic Ensemble Time-Series Modeling collaborated on a multi-location forecasting framework for Chennai, boosting predicted accuracy for urban air pollution across many monitoring stations.
- Integrated Predictive Analytics in Climate Change Research, AI approaches were used with climate data analysis to promote sustainable urban environmental management and informed policymaking.
- Scalable computational modeling developed flexible models for real-time deployment in large-scale air quality monitoring networks in smart cities.
- High-Impact Research produced and co-authored peer-reviewed articles that helped develop environmental data science, deep learning architectures, and predictive modeling for public health applications.
- Artificial Intelligence for Environmental Forecasting
- Deep Learning for Air Quality Prediction
- Time-Series Analysis and Modeling
- Predictive Analytics for Climate Change
- Computational Modeling for Smart Cities
- Data-Driven Environmental Decision Support Systems
Publications prior to joining the RIFS
- Narendran Sobanapuram Muruganandam and Umamakeswari Arumugam. 2023. Dynamic ensemble multivariate time series forecasting model for PM2.5. CSSE 44, 2 (2023), 979-989. DOI:https://doi.org/10.32604/csse.2023.024943
- Narendran Sobanapuram Muruganandam and Umamakeswari Arumugam. 2022. Seminal Stacked Long Short-Term Memory (SS-LSTM) Model for Forecasting Particulate Matter (PM2.5 and PM10). Atmosphere 13, 10 (October 2022), 1726. DOI:https://doi.org/10.3390/atmos13101726