Contact
Universitätsstraße 32
70569 Stuttgart
Germany
Room: 2.316
Office Hours
Just drop by my office. Or feel free to send me an email to express your interest, or for scheduling an appointment.
Subject
Current Topics of Interest:
- Deep Neural Networks for Solving Partial Differential Equations (PDEs)
- Efficient Representation Learning for Modeling Dynamical Systems (e.g., PDEs)
- Physics-Informed Machine Learning (Neural Operators, PINNs, Graph Networks, etc)
- Deep Learning for Spatio-Temporal Modeling (e.g., S4)
- Transformer Models for Vision and Time-Series Data
- Neural Fields for Learning Physics (e.g., CROM)
- Generative Models for Computer Vision (Vision Transformers -- Swin, ViT-like)
- Graph Neural Networks for Simulations (MPNN, MeshGraphNets, etc)
- Transfer Learning for Fluid Mechanics
- Hybrid Models for Accelerated Simulations
- Neural Operators for Simulations (e.g., FNO, CFNO, AFNO)
- Symbolic Regression (utilizing for e.g., PySINDy, PySR)
If you're interested in any of the above listed topics for your Bachelor's/Master's Thesis, or Research Project, please feel free to send me an email, attaching your current CV, up-to-date Transcript of Records, and a brief one paragraph motivation.
Aditya Mogadala, Marimuthu Kalimuthu, Dietrich Klakow
JAIR 2021 [arXiv] [Bibtex]
ICPR 2021 [arXiv] [Bibtex]
ImageCLEF 2020 [arXiv] [Bibtex]
ACL 2019 [Bibtex]
WS-2023/24
Seminar: Machine Learning in the Sciences. Co-organizer along with Mathias Niepert.
SS-2023
Seminar: Deep Learning for the Sciences. Co-organizer along with Mathias Niepert.
WS-2022/23
Seminar: Machine Learning in the Sciences. Co-organizer along with Mathias Niepert.
Course : Introduction to Artificial Intelligence. Teaching Assistant.