PeopleofSuperintelligence

Researcher

Sancho Salcedo-Sanz

Also known as Sancho Salcedo Sanz

Sancho Salcedo-Sanz is a professor at Universidad de Alcalá whose work applies machine learning and soft computing to climate, energy and telecommunications problems. He earned a doctorate in telecommunications engineering at Universidad Carlos III de Madrid in 2002 and a second one, in physics, at Universidad Complutense de Madrid in 2019. Among his papers are a 2009 study of wind speed forecasting with neural networks and a 2023 near real-time wind speed model built on bidirectional LSTM networks. His reviews of climate extremes include an arXiv review of machine learning for atmospheric extreme events in 2022, the Reviews of Geophysics heat waves review in 2023 and a Nature Communications review of AI for extreme weather in 2025. He is a full professor in Signal Theory and Communications at Alcalá, coordinates its GHEODE research group, and is an ELLIS Fellow at the ELLIS Unit Madrid.

Now at
University of Alcalá
Works
537
Citations
14,111
h-index
61
Badges

Publication numbers from OpenAlex, as of 22 October 2026.

Timeline

  1. 2002

    Doctorate at Carlos III

    He earns a PhD in Telecommunications Engineering from Universidad Carlos III de Madrid in 2002. His thesis, on spectral techniques for improving genetic algorithms, is supervised by Carlos Bousoño Calzón.

  2. 2009

    Wind forecasts with neural networks

    In 2009, he is first author, with Ángel M. Pérez-Bellido, Emilio G. Ortiz-García, Antonio Portilla-Figueras, Luis Prieto and Daniel Paredes, of a Renewable Energy paper that hybridizes the fifth generation mesoscale model (MM5) with artificial neural networks for short-term wind speed prediction.

  3. 2019

    A second doctorate in physics

    He earns a second doctorate, in physics at Universidad Complutense de Madrid, in 2019. His thesis, on new soft-computing algorithms in atmospheric physics, is supervised by Ricardo Francisco García Herrera.

  4. June 2022

    Machine learning for extreme events

    He is first author of an arXiv review, with eleven coauthors, of machine learning methods for atmospheric extreme events, submitted in June 2022. It covers the analysis, characterization, prediction and attribution of the most important events of this kind.

  5. 2023

    BiLSTM wind speed forecasting

    In 2023, he is one of six authors of a Renewable Energy paper on a near real-time wind speed forecast model built on bidirectional LSTM networks, with Lionel P. Joseph, Ravinesh C. Deo, Ramendra Prasad, Nawin Raj and Jeffrey Soar.

  6. 2023

    Heat waves in Reviews of Geophysics

    He coauthors the Reviews of Geophysics review "Heat Waves: Physical Understanding and Scientific Challenges" in 2023 with David Barriopedro, Ricardo García-Herrera, Carlos Ordóñez and Diego G. Miralles. The review names artificial intelligence among the approaches that offer new opportunities for process-based understanding.

  7. February 2025

    AI for extreme weather review

    In February 2025, Nature Communications publishes "Artificial intelligence for modeling and understanding extreme weather and climate events", a multi-author review that includes him among its authors. It examines how AI is used to analyze floods, droughts, wildfires and heatwaves.

  8. As of October 2026

    Professor and ELLIS Fellow

    He is a full professor in Signal Theory and Communications at Universidad de Alcalá and coordinates its GHEODE research group, the Modern Heuristics and Network Design group. With a 2002 doctorate in telecommunications engineering, he applies machine learning and soft-computing techniques to atmospheric and climate problems, renewable energy and telecommunications design. He is also an ELLIS Fellow at the ELLIS Unit Madrid, listed under Machine Learning for Earth and Climate Sciences.

Career

  1. Since 2005University of AlcaláFull Professor in Signal Theory and Communications
  2. 2022–2026University of Southern Queensland
  3. 2004–2006University of Birmingham

Education

  1. 2019Complutense University of MadridDoctorate in physics
  2. 2002Universidad Carlos III de MadridPhD in Telecommunications Engineering

From the biography and OpenAlex affiliations (the years of papers that list the organization), so some years are approximate.

Most-cited works

  1. Bio-inspired computation: Where we stand and what's next2019 · Swarm and Evolutionary Computation · 594 citationsWith Carlos A. Coello Coello, Francisco Herrera, Ponnuthurai Nagaratnam Suganthan and Xin-She Yang
  2. Predicting compressive strength of lightweight foamed concrete using extreme learning machine model2017 · Advances in Engineering Software · 434 citations
  3. Heat Waves: Physical Understanding and Scientific Challenges2023 · Reviews of Geophysics · 401 citations
  4. A survey on applications of the harmony search algorithm2013 · Engineering Applications of Artificial Intelligence · 363 citations
  5. Support vector machines in engineering: an overview2014 · Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery · 300 citationsWith Gustau Camps-Valls

From OpenAlex, as of 21 October 2026.

  1. The Massachusetts Institute of Technology trained or employed 44 of the 187 AI major-prize winners, more than any other universityIncludes University of Birmingham. The Massachusetts Institute of Technology trained or employed 44 of the 187 AI major-prize winners, more than any other university. We compare doctorate and 5+ year employment links, career timing and current workplaces for 187 major-prize and 1,111 best-paper winners.
  2. The company share of AI researchers’ top papers was 31% in 2020–2024 and 8% in 1970–1974Includes University of Southern Queensland. We estimate where the people shaping AI worked when their most-cited papers appeared: the company share was 31% in 2020–2024 and 8% in 1970–1974, and Google led all organizations in 2020–2024.
  3. More people shaping AI studied at Massachusetts Institute of Technology than at any other institutionIncludes Universidad Carlos III de Madrid. We estimate where the people shaping AI studied and where their careers led. Massachusetts Institute of Technology leads with 467 former students, including 291 recorded doctorates.
  4. The median h-index is 48 at universities and 14 at frontier AI labsIncludes University of Birmingham. The median h-index is 48 at universities and 14 at frontier AI labs. We compare publishing careers, recent citations, dual appointments and job moves across 2,420 university researchers and 308 frontier-lab researchers.

Colleagues

People with dated positions at the same organization in the same years.

Sources and credits

Photo: We have no published photo of Sancho Salcedo-Sanz yet. Send us a free-licensed photo.

  1. Team - GHEODE gheode.web.uah.es. Checked 20 October 2026.
  2. Sancho Salcedo Sanz - Universidad de Alcalá portalcientifico.uah.es. Checked 20 October 2026.
  3. Hybridizing the fifth generation mesoscale model with artificial neural networks for short-term wind speed prediction ideas.repec.org. Checked 20 October 2026.
  4. Analysis, Characterization, Prediction and Attribution of Extreme Atmospheric Events with Machine Learning: a Review arxiv.org. Checked 20 October 2026.
  5. Near real-time wind speed forecast model with bidirectional LSTM networks ideas.repec.org. Checked 20 October 2026.
  6. Heat Waves: Physical Understanding and Scientific Challenges docta.ucm.es. Checked 20 October 2026.
  7. Artificial intelligence for modeling and understanding extreme weather and climate events | Nature Communications nature.com. Checked 20 October 2026.
  8. Sancho Salcedo Sanz uah.es. Checked 20 October 2026.
  9. Sancho Salcedo-Sanz | European Laboratory for Learning and Intelligent Systems ellis.eu. Checked 20 October 2026.