cv
work, education, certificates, publications, skills, languages, interests. Click on "pdf" icon for pdf version.
Basics
| Name | Emiliano Díaz Salas Porras |
| Label | Post doctoral research fellow |
| emiliano.diaz@uv.es | |
| Phone | (+34) 684-144570 |
| Url | https://emdiazsal83.github.io/ |
| Summary | Machine learning and causality researcher. |
Work
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2024.01 - Present Post-doctoral research fellow
Image & Signal Processing group, Universitat de Valencia
Research on causal discovery, causal inference and machine learning applied to Earth system sciences.
- Heatwave understanding
Education
Certificates
| Deep Learning | ||
| Institute for research, development, training and advice | July 2019 |
| Graphical Models | ||
| Bocconi University | July 2018 |
| Dynamic Econometric Models | ||
| Instituto Teconológico Autónomo de México (ITAM) | 2013/09-2014/07 |
Publications
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October 2022 Identifying the Causes of Pyrocumulonimbus (PyroCb)
NeurIPS wokshop
Causal discovery tools for finding the causes of a binary target variable with application to Pyrocumulunimbus clouds.
-
May 2022 Physics-aware nonparametric regression models for Earth data analysis
Environmental research letters
Non-parametric physics aware machine learning method.
-
March 2024 Recovering Latent Confounders from High-dimensional Proxy Variables.
Arxiv
Estimating latent confounders for causal effect estimation.
-
July 2023 Learning latent functions for causal discovery
Machine Learning, Science and Technology
Bivariate causal discovery method for non-additive data with extension to time series
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July 2023 Large language models for constrained-based causal discovery
AAAI
Using large language models to aid in causal discovery.
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January 2024 Pairwise causal discovery with support measure machines.
Applied Soft Computing
Pairwise causal dicovey using ensembles and kernel mean embeddings.
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January 2022 Pyrocast: a Machine Learning Pipeline to Forecast Pyrocumulonimbus (PyroCb) Clouds
NeurIPS wokshop
A machine learning pipeline to forecast Pyrocumulunimbus clouds.
-
January 2022 Inferring causal relations from observational long-term carbon and water fluxes records
Scientific Reports
Causal discovery method for determnistic dynamic systems with applicationto carbon and water fluxes.
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December 2023 Discovering causal relations and equations from data
Physics Reports
A technical review and survey of causal discovery and equation discovery for physics.
Skills
| Machine Learning | |
| Statistics | |
| Causal Discovery | |
| Cause-effect estimation | |
| Optimization |
Languages
| Spanish | |
| Native speaker |
| English | |
| Fluent |
| German | |
| beginner |
| French | |
| beginner |
Interests
| Machine learning | |
| Statistics | |
| Causal Discovery | |
| Cause-effect estimation | |
| Optimization |
References
| Professor Gustau Camps-Valls | |
| gustau@uv.es, [web](https://www.uv.es/gcamps/) |
| Professor Fernando David Muñoz Negrón | |
| davidm@itam.mx, [web](https://gente.itam.mx/davidm/) |
| Professor Marloes Maathuis | |
| marloesmaathuis@gmail.com, [web](https://www.linkedin.com/in/marloes-maathuis-394b45174/) |
| Manuel Sarmiento | |
| manuel.sarmiento.serrano@gmail.com , [web](http://www.financial-science.net/) |
Projects
- 2022.06 - 2022.08
FDL 2022
Frontier Development Lab - Europe - 2022. As part of the Aerosols challenge developed a machine learning pipeline an causal discovery toolbox to predict Pyrocumulunimbus clouds and understand their causes.
- Causal Discovery
- Machine Learning
- Pyrocumulunimbus
- 2024.06 - 2024.08
FDL 2024
Frontier Development Lab - Europe - 2024. Currently taking part in the 3D cLOUDS USING MULTI-SENSORS challenge.
- Machine Learning
- Clouds
- Multi-sensor
- Climate modeling