About us

ModelFLOWs is a research group led by Full Professor Soledad Le Clainche. The group is based in the Department of Applied Mathematics at the School of Aerospace Engineering, Universidad Politécnica de Madrid (UPM). Our team employs diverse data-driven methods—such as modal decompositions, machine learning architectures, and data assimilation tools—to generate hybrid reduced order models grounded in physics. These models are designed to study the physics of complex dynamical systems, reconstruct and repair databases, and perform temporal forecasting. Because these models are physics-informed, they are highly robust and exhibit strong generalization capabilities. They have been successfully applied to a variety of complex flows (turbulent, reactive, etc.) and other non-linear dynamical systems. Additionally, the ModelFLOWs group has extensive expertise in computational fluid dynamics (CFD), flow control, and the development of novel tools and methodologies for data analysis.

Group Leader

Soledad Le Clainche

Full Professor

Group Members

Andrés Bell

Assistant Professor

Xiangrui Zou

MSCA Postdoctoral Researcher

Francisco Giral

PhD Candidate

Arindam Sengupta

PhD Candidate

Guillermo Barragán

PhD Candidate

Paul Jeanney

PhD Candidate

Alvaro Manzano

PhD Candidate

Christian Amor

PhD Candidate

Zhuoqun Zhao

PhD Candidate

Isacco Faglioni

PhD Candidate

Han Chen

PhD Candidate

Jiannan Li

PhD Candidate

Miguel Ríos

PhD Candidate

Wentai Deng

PhD Candidate

Álvaro Río

PhD Candidate

Alberto Rodríguez

PhD Candidate

Iñaki Gutierrez

PhD Candidate

Pablo López Salazar

MSc Student

Ángel Alonso Escalante

MSc Student

Mikel Navarro

MSc student

Ander Sánchez

MSc student

Carlos Sainz

MSc student

Alumni