The institute has launched the Polish Research Infrastructure Network for Artificial Intelligence-Assisted Science project

The Institute has started implementing the project: the Polish Research Infrastructure Network for Science Assisted by Artificial Intelligence. The project is being implemented under Measure 2.4 of the FENG program No. FENG.02.04-IP.04-0019/24

The aim of the project “Polish Research Infrastructure Network for Artificial Intelligence-Assisted Science (PLAI4SCIENCE)” is to create a unique research infrastructure to support the development of science, especially physics and chemistry, using artificial intelligence (AI) and machine learning (ML). The main application of this infrastructure is to create a computational platform and measurement stations for the scientific community and business entities, providing tools for:

1. ML-assisted material simulations: study of the properties of molecules and nanostructures; study of the properties of low-dimensional optoelectronic systems; development and use of AI/ML-assisted quantum-chemical and simulation methods to reduce the cost of theoretical calculations and enable simulation of large systems that are difficult to process with currently available quantum-chemical methods. Commercial applications: predicting the properties of multi-electron systems, computational chemistry, spectroscopic calculations, materials engineering, molecular dynamics, drug design, material identification for the photovoltaic, spintronics and organic electronics industries.

2. Molecular spectroscopy and photonic metrology: use of optical resonant cavities, ultraprecision spectroscopy, optical frequency combs to measure material properties and ultrafast processes and validate spectroscopic models calculated using AI methods and ML models, “smart” light sources. Commercial applications: characterization of materials for the semiconductor and optoelectronics sectors, generation of reference data for atmospheric monitoring and trace detection systems, process monitoring, biomedical diagnostics, precision characterization of laser systems.

3. Measurements using spatial-spectral imaging: hyperspectral imaging with ML models for detection, segmentation and classification of spectra, and dedicated computer vision models. Commercial applications: environmental and phenomenon monitoring, quality control (e.g., food), non-contact substance detection and identification, medical diagnostics.

4. Uses of explainable AI and ML methods in the sciences: specialized algorithms and models, both classical and deep neural network architectures, e.g. graph networks and language models, as well as tools for model learning and reinforcement learning. The infrastructure component is an advanced computing environment with high-powered clusters and appropriate software.

The results of the project are aimed at scientists conducting research in physics, chemistry and other fields requiring analysis and processing of large data sets.

IITIS PAN is the coordinator of the project, which also involves Nicolaus Copernicus University in Torun, Wroclaw University of Technology and the Institute of Bioorganic Chemistry of the Polish Academy of Sciences, Poznan Supercomputing and Networking Center.

The total cost of the Project is PLN 92,635,716.67, with funding of PLN 69,709,425.54.

#EuropeanFunds #EUFunds

  

 

Author: Krzysztof Grochla 02.01.2025

Historia zmian

Data aktualizacji: 08/01/2025 - 08:35; autor zmian: mgr inż. Ewelina Szweda (eszweda@iitis.pl)

The Institute has started implementing the project: the Polish Research Infrastructure Network for Science Assisted by Artificial Intelligence. The project is being implemented under Measure 2.4 of the FENG program No. FENG.02.04-IP.04-0019/24

The aim of the project “Polish Research Infrastructure Network for Artificial Intelligence-Assisted Science (PLAI4SCIENCE)” is to create a unique research infrastructure to support the development of science, especially physics and chemistry, using artificial intelligence (AI) and machine learning (ML). The main application of this infrastructure is to create a computational platform and measurement stations for the scientific community and business entities, providing tools for:

1. ML-assisted material simulations: study of the properties of molecules and nanostructures; study of the properties of low-dimensional optoelectronic systems; development and use of AI/ML-assisted quantum-chemical and simulation methods to reduce the cost of theoretical calculations and enable simulation of large systems that are difficult to process with currently available quantum-chemical methods. Commercial applications: predicting the properties of multi-electron systems, computational chemistry, spectroscopic calculations, materials engineering, molecular dynamics, drug design, material identification for the photovoltaic, spintronics and organic electronics industries.

2. Molecular spectroscopy and photonic metrology: use of optical resonant cavities, ultraprecision spectroscopy, optical frequency combs to measure material properties and ultrafast processes and validate spectroscopic models calculated using AI methods and ML models, “smart” light sources. Commercial applications: characterization of materials for the semiconductor and optoelectronics sectors, generation of reference data for atmospheric monitoring and trace detection systems, process monitoring, biomedical diagnostics, precision characterization of laser systems.

3. Measurements using spatial-spectral imaging: hyperspectral imaging with ML models for detection, segmentation and classification of spectra, and dedicated computer vision models. Commercial applications: environmental and phenomenon monitoring, quality control (e.g., food), non-contact substance detection and identification, medical diagnostics.

4. Uses of explainable AI and ML methods in the sciences: specialized algorithms and models, both classical and deep neural network architectures, e.g. graph networks and language models, as well as tools for model learning and reinforcement learning. The infrastructure component is an advanced computing environment with high-powered clusters and appropriate software.

The results of the project are aimed at scientists conducting research in physics, chemistry and other fields requiring analysis and processing of large data sets.

IITIS PAN is the coordinator of the project, which also involves Nicolaus Copernicus University in Torun, Wroclaw University of Technology and the Institute of Bioorganic Chemistry of the Polish Academy of Sciences, Poznan Supercomputing and Networking Center.

The total cost of the Project is PLN 92,635,716.67, with funding of PLN 69,709,425.54.

#EuropeanFunds #EUFunds