Artificial Intelligence tends to become a horizontal infrastructure, supporting a variety of disciplines and applications. During the last few years a number of works highlight the potential of AI utilization in natural science settings and the potential for cross-fertilization between disciplines. The workshop aims to bring together AI and:

  • Modeling and simulation of processes;
  • Big, experimental data analyses (e.g. genomic data, particle physics);
  • New materials design;
  • Optimization of technological and industrial processes;
  • Microscopy enhancement (Deep Learning Microscopy);
  • Challenges of AI in natural sciences use cases;
  • Quantum computation and AI;
  • Error correction and noise removal.

Indicative topics related to the above are:

  • Adapting AI for natural sciences
  • Mathematical modeling
  • Physics
  • Chemistry
  • Materials science and engineering
  • Biology and biomedical engineering
  • Pharmaceutical applications and bioinformatics
  • Environmental science and engineering
  • Weather and climate forecasting
  • Nanotechnology
  • Quantum computing for Natural Science
  • Quantum computing and AI
  • Big Data Analysis from Particle Physics Experiments

The need for an interdisciplinary workshop on AI and natural sciences and technology comes as a natural extension of these works, aiming to bring together practitioners from both AI and a wide range of scientific and engineering disciplines  to cross-fertilize research, algorithms, tools, and novel application areas.

Scope

The aim of the workshop is to activate and empower the – already emerging – community of natural scientists and engineers on the key role of implementing AI to a plethora of cutting-edge scientific domains and industrial processes, as well as AI researchers that understand the idiosyncrasies and challenges of applying AI methods in the area of natural sciences and engineering. To this end, we will accept submissions as:

  • Position papers, sketching promising future directions, based on recent findings on the borderline between natural sciences/novel technologies and AI.
  • Tools and demo papers, describing existing AI tools and their suggested applications on scientific and technological problems.
  • Research papers, describing new research works, highlighting the interaction between AI and natural sciences.