Launch week offerEnds in00h00m00s

annual Promonthly Pro

Jorge Pérez-Aracil

Assistant Professor

Universidad de Alcalá

Spain

Research Interests

ApplyKite TwinLearns as you apply

Make your next move.

Prepare your application

Review drafts before you send them.

Explore related searches

Professors in Spain

About

Jorge Pérez-Aracil is an Associate Professor at Universidad de Alcalá in Spain. His research focuses on advanced methodologies in predicting extreme weather events, including wind speed and heatwaves, leveraging techniques such as quantile regression ensembles and multi-task deep learning. Additionally, he explores applications of artificial intelligence in atmospheric forecasting and hydrological model calibration, contributing significantly to the fields of meteorology and environmental science.

Articles (33)

Year:

2026

Year:

2026

Year:

2026

Year:

2026

Year:

2026

Year:

2026

Year:

2026

Year:

2026

Year:

2025

Year:

2025

Year:

2025

Year:

2025

Year:

2025

Year:

2025

Year:

2025

Year:

2025

Year:

2025

Year:

2025

Year:

2025

Year:

2025

Year:

2025

Year:

2025

Year:

2024

Year:

2023

Year:

2023

Year:

2023

Year:

2023

Year:

2023

Year:

2023

Year:

2023

Year:

2023

Year:

2023

Year:

2023

Collaborators (32)

Andrea Castelletti

Professor

Politecnico di Milano

ITALY

Jorge Pérez-Aracil

Research Interests

Make your next move.

Explore related searches

About

Articles (33)

A probabilistic alert system for extreme wind events prediction using quantile regression ensembles

Hybrid cloudiness-irradiance modeling for enhanced 24-hour solar forecasting with multi-source data

Constructing New Fractal-like Particle Aggregates Using Seeded DLA and Concentration Gradient Diffusion Approaches

Environmental challenges of deep underwater infrastructures: elliptic curves in the evolutionary service design of submerged arch-type structures

The Maturation of AI in Drought Science: A Review of Trends, Pitfalls, and Priorities

Explainable Singular Spectrum Analysis deep learning model for half-hourly electricity price prediction

Degradation of the Intermediate Band Caused by Disorder in Quantum-Dot Intermediate-Band Solar Cells

Multi-criteria design of undersea arch-type structures using shape parameterization

Enhancing wind speed prediction in wind farms through ordinal classification

Artificial Intelligence-Based Methods and Algorithms in Fog and Atmospheric Low-Visibility Forecasting

Simultaneous multi-step wind speed prediction on multiple farms using multi-task deep learning

Accurate calibration of hydrological models with evolutionary computation multi-method ensembles

Identifying key drivers of heatwaves: A novel spatio-temporal framework for extreme event detection

Efficient design of electromagnetic field exposure maps with multi-method evolutionary ensembles

Spatio-temporal analysis of droughts in the Iberian Peninsula using complex Climate Networks over precipitation data

Go-around occurrence prediction with rule-induction, rule evolution and Machine Learning algorithms

Competencias Digitales Empresariales: Estudio Comparativo España-Europa 2021-2025

A Simple Method for Generating New Fractal-like Aggregates from Gravity-Based Simulation and Diffusion-Limited Aggregation

Inelastic period and equivalent damping in RC buildings: An energy balance approach to earthquake analysis

XAI‐GPI: An Interpretable and Adaptive Machine Learning Genesis Index for Tropical Cyclones

Enhancing the shape-optimization of submerged arches using Bézier curves

Feature selection for data-driven seasonal forecasts of European heatwaves

TensorCRO: A TensorFlow‐based implementation of a multi‐method ensemble for optimization

Machine Learning Classification–Regression Schemes for Desert Locust Presence Prediction in Western Africa

A fuzzy-based cascade ensemble model for improving extreme wind speeds prediction

Evolutionary Computation-Based Active Mass Damper Implementation for Vibration Mitigation in Slender Structures Using a Low-Cost Processor

Extreme Low-Visibility Events Prediction Based on Inductive and Evolutionary Decision Rules: An Explicability-Based Approach

Accurate long-term air temperature prediction with Machine Learning models and data reduction techniques

Cross-entropy boosted CRO-SL for optimal power flow in smart grids

Improving numerical methods for the steel yield strain calculation in reinforced concrete members with Machine Learning algorithms

New Probabilistic, Dynamic Multi-Method Ensembles for Optimization Based on the CRO-SL

The Economic Impact Associated with the Direct Connection Strength of Micropiles in Foundation Retrofit Projects

One month in advance prediction of air temperature from Reanalysis data with eXplainable Artificial Intelligence techniques

Collaborators (32)

Andrea Castelletti

Francisco Pellicer-Martínez

Víctor Manuel Vargas Yun

David Barriopedro

Elizabeth Wanner

Enrique Alexandre

Cosmin M Marina

Pedro Antonio Gutiérrez

Sancho Salcedo-Sanz

Luis Castelo Sardina

Carlos Santos-Pérez

César Hervás-Martínez

Miguel Ángel Fernández Torres

José Manuel Soria Herrera

Mihaela I. Chidean

Thong Nguyen-Huy

MARIA JULIA SANZ

J. Antonio Portilla-Figueras

Ravinesh Deo

Javier Del Ser

David Guijo-Rubio

CARLOS CRUZ

Gustau Camps-Valls

Lucas Cuadra

Alvaro Magdaleno

Emiliano Pereira

Antonio Manuel Gómez-Orellana

Konstantin Hopf

Pablo-Luis Lopez-Espi

David Casillas-Pérez

César Peláez-Rodríguez

Elena Xoplaki

Make your next move.