Rate My Professor Sibarama Panigrahi

Dr. Panigrahi has published over 57 papers in high-impact SCI-indexed journals such as Neural Computing and Applications, Journal of Forecasting, Information Sciences, and Engineering Applications of Artificial Intelligence, with a Google Scholar h-index of 20, i10-index of 30, and more than 1,400 citations. Notable publications include 'Decomposition-based hybrid methods employing statistical, machine learning, and deep learning models for crude oil price forecasting' (Neural Computing and Applications, 2025), 'A study and development of high-order fuzzy time series forecasting methods for air quality index forecasting' (Journal of Forecasting, 2024), and 'Novel deterministic and probabilistic forecasting methods for crude oil price employing optimized deep learning, statistical and hybrid models' (Information Sciences, 2024). He has received Best Paper Awards at international conferences in 2023 and 2025, the Faculty Advisor Appreciation Award for 2024-25, and has served as Academic Editor for PLOS ONE and Editorial Board Member for Scientific Reports (Nature) since 2024. Dr. Panigrahi reviews for over 30 SCI journals and ANRF/BRNS projects, and has secured grants from SERB and ANRF, including developing electricity load forecasting software deployed by Tata Power Western Odisha Distribution Limited. He has organized multiple continuing education programs on AI, data science, and deep learning.