Dr Antonios Mamalakis
I am a research scientist working with Professors Elizabeth Barnes and James Hurrell at Colorado State University (CSU).
I hold a PhD in Civil and Environmental Engineering from University of California, Irvine, advised by Professor Efi Foufoula-Georgiou.
My past work has been focused on the interaction between climate variability and change with regional hydroclimate across scales.
At CSU, I currently work on eXplainable Artificial Intelligence (XAI) and its application to climate sc
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News
New study published in AI4ES
Investigating the fidelity of explainable artificial intelligence methods for applications of convolutional neural networks in geoscience
September 2022
New study published in Env. Data Science
Neural network attribution methods for problems in geoscience: A novel synthetic benchmark dataset
June 2022
New study published in Water Resources Research
Identifying regions of high precipitation predictability at seasonal timescales from limited time series observations
May 2022
New Book chapter published
Explainable Artificial Intelligence in Meteorology and Climate Science: Model Fine-Tuning, Calibrating Trust and Learning New Science
March 2022
New study published in Geophysical Research Letters
Underestimated MJO variability in CMIP6 models
June 2021
New study published in Nature Climate Change
Zonally contrasting shifts of the tropical rain belt in response to climate change
January 2021
New study published in Journal of Climate
Graph-Guided Regularized Regression to Increase Predictive Skill of Winter Precipitation
January 2021
New study published in Journal of Climate
Rotated Spectral Principal Component Analysis (rsPCA) for Identifying Dynamical Modes of Variability in Climate Systems
January 2021
New Position!
I am very excited to join Colorado State University and work as a postdoc on knowledge-guided machine learning!
September 2020
CSU
PROJECT TEAM
PhD Graduation!
Thank you UCI for this amazing journey!
September 2020
Study included in the top 50 articles of Nature Comm:
A new interhemispheric teleconnection increases predictability of winter precipitation in southwestern US
July 2019
Highlighted Research
Attribution Benchmarks to introduce objectivity in the XAI assessment
Zonally contrasting shifts of the tropical rain belt in response to climate change
New teleconnection increases predictability of precipitation in southwestern US
Simultaneous Bias Correction and spatial Downscaling of climate model Rainfall |
