Welcome to the Computational Scientific Machine Learning Lab (CSML) from the Department of Mechanical, Aerospace, and Nuclear Engineering at RPI.

What’s our mission?

• Our mission is to pioneer advanced modeling and simulations in Mechanical and Aerospace Engineering by harnessing the power of scientific machine learning.

What are our interests?

• Scientific machine learning for large-scale nonlinear systems
• Operator-theoretic modeling and control of fluid flows
• Generative AI for physical systems

News

• Apr 2024 Our paper on exploiting symmetry for Koopman operator is published on Nonlinear Dynamics. link

• Jan 2024 Our paper with University of Maryland on Physics-Informed Machine Learning for Plasmas is featured on Physics of Plasma link

• Apr 2024: I will join the technical committee of Fluid Dynamics in AIAA. Looking forward to talk with this exciting community.

More

- **Nov 2023:** We will see you in APS-DFD in DC. Here Nithin will present his work on differentiable programming meets high-order methods! - **Nov 2023:** Congrats to Jake Herman successfully defended his Master thesis on _Learning Linear Evolution of PDE via Koopman Operator_! - **Sep 2023:** Congrats to Nithin easily passed the qualifying exam! - **Sep 2023:** Welcome Weichao! - **Jan 2023:** Welcome Nithin and Shahriar! - **Nov 2022:** Shaowu presented PyKoopman in 75th APS-DFD in Indianapolis! - **Nov 2022:** Shaowu presented neural implicit flow in SIAM Annual Meeting TX-LA in Houston! - **Oct 2022:** Welcome Raymond from Benét Laboratories! - **Sep 2022:** Sandesh joins the lab, welcome! - **Aug 2022:** Shaowu begins the journey as Assistant Professor!