Chinmay Datar

Chinmay Datar is a doctoral candidate at the Technical University of Munich (TUM), affiliated with the Institute of Advanced Study (IAS) in the focus group 'Scientific Machine Learning.' He holds an M.Sc. in Computational Engineering from Friedrich-Alexander University (FAU), Erlangen, and a Bachelor's in Mechanical Engineering from the University of Pune. His research focuses on integrating classical scientific computing methods with deep learning to solve Partial Differential Equations (PDEs).

Teaching Responsibilities include:

• Summer Semester 2025: Seminar on High-Dimensional Methods for Scientific Computing and Lab Course on Machine Learning in Crowd Modeling/Simulation
• Winter Semester 2024/25: Courses on Scientific Computing & Machine Learning and a Seminar on Ethics in Science

Research Interests:

• Novel neural architectures for dynamical systems simulation
• Backpropagation-free training of neural PDE solvers
• Domain decomposition combined with neural networks for PDE solutions

Student Supervision:

• Ongoing: Eray Yildiz (Master's) and Ahmet Semiz (Master's)
• Completed: Rahma Atamert and Aditya Phopale (Master's)

Recognition: FAU Graduation Scholarship (Japan internship support).

Labs/Teams: Part of the Chair of Scientific Computing in Computer Science (SCCS), led by Prof. Hans-Joachim Bungartz.