International Conference on

Applied AI and Scientific Machine Learning

December 14-18, 2024

Recent Updates

  • 2024-12-22Pictures taken during CASML 2024 can be accessed here.
  • 2024-12-20CASML 2024 Conference has concluded successfully! The Conference proceedings are available online.
  • 2024-12-20Prof. Ricardo Vinuesa’s talk can be accessed here.

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 DeepONet 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

PINN Icon

Physics-Informed Neural Networks

Unlock Forward and Inverse PDE Solutions with Physics-Informed Neural Networks and Variants!

Neural Operators Icon

Neural Operators

Harness Operator Learning with Deep-O-Net and Fourier Neural Operators to Tackle Complex Problems!

NLP/CV Icon

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 Icon

Digital Twins & Surrogate Modelling

Create Real-Life Replicas: Digital Twins Using Data-Driven and Computational Methods!

MLOps Icon

SciMLOps

Push Scientific Boundaries: Harness High-Performance Computing and PINNs with Data-Driven Innovation!

Explainable AI Icon

Explainable & Interpretable AI

Drive Innovation: Use High-Performance Computing and PINNs to Redefine Scientific Computing!

Speakers

Prof. Dr. George E. Karniadakis

Prof. Dr. George E. Karniadakis

Brown University

Research Interests: Physics-informed Neural Networks, Probabilistic Scientific Computing, Stochastic Multiscale Modelling

Prof. Anima Anandkumar

Prof. Anima Anandkumar

California Institute of Technology and NVIDIA

Research Interests: Machine learning, Artificial Intelligence

Prof. Ricardo Vinuesa

Prof. Ricardo Vinuesa

KTH Royal Institute of Technology

Research Interests: AI/ML/RL for CFD, Flow control, Turbulent Flows, Sustainability

Dr. Pradeep Ramachandran

Dr. Pradeep Ramachandran

Advanced Computing labs, KLA

Research Interests: HPC, Image processing, AI

Prof. Dr. Siddhartha Mishra

Prof. Dr. Siddhartha Mishra

ETH, Zurich

Research Interests: Scientific computing, nonlinear PDEs, machine learning, computational fluid dynamics

Suchismita Sanyal

Suchismita Sanyal

ExxonMobil

Research Interests: Computational sciences

Dr. Arjun Jain

Dr. Arjun Jain

FastCode AI

Research Interests: Computer Graphics, Vision, Machine Learning

Jigar Halani

Jigar Halani

NVIDIA

Research Interests: High Performance computing, Big Data, AI Metaverse, Virtualization

Prof. Bharadwaj Amrutur

Prof. Bharadwaj Amrutur

IISc Bangalore

Research Interests: Robotics, AI-enabled Autonomous systems

Dr. Suranjan Sarkar

Dr. Suranjan Sarkar

Shell Technology Centre

Research Interests: Computational fluid dynamics, Systems Modeling, Digital Twins and Surrogate Modeling, SciML

Dr. Prakash Raghavendra

Dr. Prakash Raghavendra

AMD

Research Interests: GPU Computing, HSA Compilers

Dr. Alexander Heinlein

Dr. Alexander Heinlein

TU Delft

Research Interests: Numerical Analysis, High Performance Computing, Scientific Machine Learning

Dr. Prasanna Balaprakash

Dr. Prasanna Balaprakash

Oak Ridge National Laboratory

Research Interests: AI for Science, High Performance Computing, Scientific Machine Learning

Prof. Gianluigi Rozza

Prof. Gianluigi Rozza

SISSA, Int. School for Adv. Studies, Italy

Research Interests: Numerical Analysis, Numerical Simulation, Optimization Control, Computational Fluid Dynamics

Dr. Priyanka Sharma

Dr. Priyanka Sharma

Fujitsu Research of India (FRIPL)

Research Interests: HPC, AI, Deep Learning, NLP, Computer Vision

Registration

Students

Including post docs and RA research staff
Regular Registration
2,000
Late Registration
3,000

Faculty

For academicians
Regular Registration
4,000
Late Registration
6,000

Industry

For industry professionals
Regular Registration
8,000
Late Registration
12,000