Curriculum Vitae
My research combines climate dynamics, numerical modelling, data science, and artificial intelligence to better understand climate variability, extreme events, and their impacts on society.
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Academic Profile
Current position
Postdoctoral Researcher
Department of Earth Sciences
Uppsala University
Sweden
Research Interests
- Climate variability
- Compound climate extremes
- Climate impacts
- Artificial Intelligence for Climate Science
- Earth system modelling
Expertise
- Climate modelling
- Statistical analysis of large climate datasets
- Programming in Python & R
- High-performance computing
- Machine Learning
- Natural Language Processing
Education
Ph.D. – Sciences
UCLouvain, Earth and Life Institute, Earth and Climate Research Center
M.Sc. – Physics of Earth, Planets and Climate
Career Timeline
| Year | Position |
|---|---|
| 2023–present | Postdoctoral Researcher, Uppsala University |
| 2016-2023 | Teaching Assistant in Physics, and Ph.D. candidate, UCLouvain |
| 2012-2016 | M.Sc. Physics |
Professional Affiliations
My research is conducted within an international network of collaborations focused on climate variability, climate extremes, and their societal impacts. I am actively involved in the following scientific initiatives:
Regional Working Group on African Monsoons (WG-AFM)
Member of the international working group under the Monsoon Panel, contributing to research on African monsoon dynamics, predictability, and climate variability.
Website: https://impo.tropmet.res.in/mpwg-afm-members.htmlCentre for Impacts of Climate Extremes (CLIMES)
Affiliated researcher with the Swedish Centre for Impacts of Climate Extremes, an interdisciplinary research centre investigating the impacts of climate extremes and supporting climate adaptation and resilience.
Website: https://www.climes.se/about/
Highlights
Scientific Service
Conference convener
2026
- Co-convener of the European Geoscience Union General Assembly session, CL4.7, on Climate and Life in Africa, from Past to Future.
Technical Skills
Python
R
GIS
Machine Learning
Climate models
Languages
French
English
Swedish (basic)