CASML – Conference

Conference on Applied AI and Scientific Machine Learning (CASML) – 2024

December 14 to 18 – 2024

Department of Computational and Data Sciences, Indian Institute of Science Bangalore

About the Conference

The inaugural Conference on Applied AI and Scientific Machine Learning will be a pioneering event at the intersection of machine learning and scientific computing. The conference will be hosted at the Indian Institute of Science, Bangalore. This conference aims to address the growing need for a dedicated forum to explore the application of machine learning techniques in scientific domains such as physics, chemistry, biology, and engineering. The three-day conference will comprise keynote addresses, technical sessions featuring peer-reviewed presentations and panel discussions on critical issues in the field. A notable component of the conference is a hackathon, designed to bridge the gap between academic research and industrial applications. This event will bring together industry professionals and academics to formulate and solve real-world challenges in scientific machine learning and applied AI/ML. The conference will be preceded by 2 days of workshops (14, 15 Dec-2024) to train participants in the state of the art of scientific machine learning.

Core topics for the conference

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Physics-Informed Neural Networks

Using Physics Informed Neural Networks and its variants to solve Forward and Inverse problems with Partial Differential equations (PDE).

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Digital Twins & Surrogate Modelling

Digital twin of applications that replicate real life systems using data-driven or computational methods.

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Applied AI

Applied AI techniques are driving innovation across various scientific disciplines, enabling faster predictions, enhanced data analysis, and the exploration of complex problems. We invite insights into Applied AI-driven scientific workflows and their potential to accelerate scientific computing.

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Neural Operators

Use of operator learning such as Deep-O-Net, Fourier Neural operator or any advancement in the architecture to solve problems.

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MLOps

Leveraging high-performance computing and Physics-Informed Neural Networks (PINNs) to push the boundaries of scientific computing with data-driven methodologies.

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NLP/CV for Computational Problems

Uses of Computer Vision for Computational Problems such as Super-Resolution of Fluid Flows, and Applications of NLP in Aiding or Solving Scientific Machine Learning Problems

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Explainable & Interpretable AI

Leveraging high-performance computing and Physics-Informed Neural Networks (PINNs) to push the boundaries of scientific computing with data-driven methodologies.

Important Dates

Description Date
Abstract Submission Start Date02-Sep-2024
Abstract Submission End Date30-Sep-2024
Start of Registration01-Oct-2024
Notification of Acceptance15-Oct-2024
Last Date for Early Registration30-Oct-2024
Last Date for Late Registration15-Nov-2024

Invited Speakers (Tentative)

– TBD –

Paper Submission Instructions

Submission Format:

  • Papers will be accepted based on extended abstracts.
  • The extended abstracts should be 4 to 5 pages in length.

Abstract Availability:

  • Accepted extended abstracts will be published on the conference website.

Template:

  • A LaTeX template for preparing the extended abstracts will be made available soon.