Marimuthu Kalimuthu

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.