International Conference on
Applied AI and Scientific Machine Learning
December 14-18, 2024
Recent Updates
- 2024-11-20:Please note that on-campus accommodation is full. For alternative accommodation options, please refer to the Attend page.
- 2024-11-20:To confirm your attendance at the conference, please complete the registration form and payment process by clicking the “Proceed to Payment” button. Please use the same email address you used for registration to complete the payment.
- 2024-10-30: Last date for Early registration is extended until November 21st for Paper/Poster presentation participants to register after their acceptance status.
- 2024-10-23: The notification for accepted papers/posters will be sent on or before November 3rd.
- 2024-10-23:For Paper/Poster presentation participants, the link will be sent after October 31st.
- 2024-09-29: The deadline for Paper/Poster submission was October 12th. We are not accepting submissions anymore.
- 2024-09-29: The registration for the conference is open! Visit the registration page for more details.
CASML 2024
Join us at the Indian Institute of Science (IISc), Bangalore, for the inaugural Conference on Applied AI and Scientific Machine Learning (CASML) organised by AiREX Lab at IISc and supported by ARTPARK. This pioneering event, at the crossroads of AI, Machine Learning and Scientific Computing, will explore the application of AI techniques in fields like Computational Science, and Engineering.
A special session is planned for AI-driven engineering companies, organizations wanting to implement AI-driven Digital Twins, and DeepTech startups working in core science and engineering solutions. Please contact associatepartner@casml.cc.
Conference Highlights:
- Physics-Informed Neural Networks (PINNs): Delve into solving forward and inverse problems using Partial Differential Equations.
- Neural Operators: Explore Deep-O-Net and Fourier Neural Operators for complex challenges.
- Integration of NLP and CV: Focus on applications like fluid flow super-resolution.
- Digital Twins & Surrogate Modelling: Examine data-driven system replication.
- SciMLOps & High-Performance Computing: Push scientific computing boundaries with PINNs.
- Explainable & Interpretable AI: Ensure transparency in scientific AI applications.
- Pre-conference Workshop: Hands-on training on Scientific ML techniques.
Event Structure:
- Keynote Addresses & Technical Sessions: Featuring peer-reviewed presentations.
- Panel Discussions: Tackle critical industry AI challenges with Digital Twins.
- Hackathon: Bridge academic research with industrial applications.
Main Focus Areas
Physics-Informed Neural Networks
Unlock Forward and Inverse PDE Solutions with Physics-Informed Neural Networks and Variants!
Neural Operators
Harness Operator Learning with Deep-O-Net and Fourier Neural Operators to Tackle Complex Problems!
GenAI for Computational Problems
Elevate Computational Power: Use Computer Vision for Fluid Flow Super-Resolution and NLP to Solve Scientific Machine Learning Challenges!
Digital Twins & Surrogate Modelling
Create Real-Life Replicas: Digital Twins Using Data-Driven and Computational Methods!
SciMLOps
Push Scientific Boundaries: Harness High-Performance Computing and PINNs with Data-Driven Innovation!
Explainable & Interpretable AI
Drive Innovation: Use High-Performance Computing and PINNs to Redefine Scientific Computing!