I am a PhD student at the Mathematics for Real-World Systems CDT, based in the Centre for Complexity Science. The purpose of my research is to improve the predictability of meteorological drought in Africa with a time lead of 12 months using data-driven approaches. It is supervised by Professor Colm Connaughton and Dr Francisco A. Rodrigues.
Before joining Mathsys, I had been working in the financial services industry for several years.
My research interests are Machine Learning, Deep Learning, Time Series, and Causality applied in real-world problems such as climate and finance. their applications in other scientific fields.
- Aug. 2019: Cambridge Networks Day
- Sept. 2019: Data Study Group - Project by STC -" Bandwidth allocation for mobile users: a solution for rural and urban areas" at the Alan Turing Institute, UK.
- Nov. 2019: SPAAM Seminar Series - contributed talk: "Causal Network Discovery from Climate time series".
- Mar. 2020: MISS Research Group - contributed talk: "Reinforcement Learning for FX trading".
- Sept. 2020: 10th International Conference on Climate Informatics - poster: "Discovering Causal factors of drought in Ethiopia".
- Sept. 2020: Noorbakhsh, Mohammad, Colm Connaughton, and Francisco A. Rodrigues. "Discovering causal factors of drought in Ethiopia." Proceedings of the 10th International Conference on Climate Informatics. 2020.
- MSc Mathematics for Real-World Systems – University of Warwick, UK
Thesis title: “Network analysis of African rainfall patterns”
- MSc Data Science and Analytics – Royal Holloway University of London, UK
Thesis title: “Machine Learning for Drug Discovery”
- MSc Finance and Management - Cranfield University. UK
Thesis title: “Stock returns, dividend yields, and volatility: Evidence from Hong Kong market”
- BSc Computer Engineering - Sharif University of Technology, Iran