People
- Associate Professor of Aerospace
Adrián Lozano-Durán
The overarching theme of my research is fluid dynamics, with an emphasis on turbulence through theory, numerical simulation, and experiments. My work includes causal inference, reduced-order modeling, and the control of turbulence using information theory. I am also interested in machine-learning closure models for computational fluid dynamics, specifically oriented towards aerospace applications ranging from low-speed aerodynamics to supersonic and hypersonic flows.
- Joining January 2025
Angkur Shaikeea
We aim to unite designers, material scientists, and mechanicians to foster innovation in the creation of new materials. Our goal is to develop cutting-edge experimental tools, particularly using X-rays, to understand material behavior in 3D and apply this knowledge to design new materials and products. We are in pursuit of building a unique laboratory that integrates tomography, ptychography, EDXRD, and 3DXRD for in-situ measurements under mechanical loading, for metals to biological samples. By extracting detailed 3D stress and strain data, we are in pursuit of building the largest database for data-driven mechanics, enabling machine learning and AI analysis. With a strong foundation in solid mechanics, our research tackles complex challenges across disciplines while also prioritizing sustainable innovations.