
Reza Yeganegi
Research Scholar
Cooperation and Transformative Governance Research Group
Advancing Systems Analysis Program
Contact
Biography
Mohammad Reza Yeganegi joined IIASA in 2023 and is currently a research scholar in the Cooperation and Transformative Governance Research Group of the Advancing Systems Analysis Program. He has a PhD in statistics and a master’s degree in economic and social statistics from the Chamran University of Ahvaz, Iran. Prior to joining IIASA, he was affiliated with Islamic Azad University, Iran, as an assistant professor in financial statistics.Yeganegi’s research includes both the theoretical and practical sides of time series analysis, forecasting, risk analysis, predictive causality analysis, machine learning, and social network analysis. He is experienced in developing statistical tools and has a hand in online data analysis.
Last update: 06 FEB 2024
Publications
Hassani, H., Mashhad, L.M., Royer-Carenzi, M., Yeganegi, R. , & Komendantova, N. (2025). White Noise and Its Misapplications: Impacts on Time Series Model Adequacy and Forecasting. Forecasting 7 (1) p. 8. 10.3390/forecast7010008.
Komendantova, N. , Hassani, H., Yeganegi, R. , Al Salaymeh, A., & Qoaider, L. (2024). Navigating the Currents: Land Use Challenges Amidst Water and Food Security Debates and Social Media Misperceptions. Land 13 (9) e1525. 10.3390/land13091525.
Hassani, H., Royer-Carenzi, M., Mashhad, L.M., Yarmohammadi, M., & Yeganegi, R. (2024). Exploring the Depths of the Autocorrelation Function: Its Departure from Normality. Information 15 (8) e449. 10.3390/info15080449.
Hassani, H., Marvian, L., Yarmohammadi, M., & Yeganegi, R. (2024). Unraveling Time Series Dynamics: Evaluating Partial Autocorrelation Function Distribution and Its Implications. Mathematical and Computational Applications 29 (4) e58. 10.3390/mca29040058.
Hassani, H., Komendantova, N. , Rovenskaya, E. , & Yeganegi, R. (2024). Unveiling the waves of mis- and disinformation from social media. International Journal of Modeling, Simulation, and Scientific Computing 10.1142/S1793962324500338.