Marimuthu Kalimuthu

M.Sc.

Researcher
IPVS
Machine Learning for Simulation Science

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.

Trends in Integration of Vision and Language Research: A Survey of Tasks, Datasets, and Methods
Aditya MogadalaMarimuthu KalimuthuDietrich Klakow
JAIR 2021 [arXiv] [Bibtex]

Fusion Models for Improved Image Captioning
Marimuthu KalimuthuAditya MogadalaMarius MosbachDietrich Klakow
ICPR 2021 [arXiv] [Bibtex]

A Competitive Deep Neural Network Approach for the ImageCLEFmed Caption 2020 Task
Marimuthu KalimuthuFabrizio NunnariDaniel Sonntag
ImageCLEF 2020 [arXiv] [Bibtex]

Incremental Domain Adaptation for Neural Machine Translation in Low-Resource Settings
Marimuthu KalimuthuMichael BarzDaniel Sonntag
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 IntelligenceTeaching Assistant.

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