Scientific machine learning

Physics-, chemistry-, and biology-informed learning

Causality, mechanistic models, symbolic AI & neuro-symbolic reasoning

Uncertainty quantification, calibration, robust & trustworthy AI

Explainability, interpretability, and scientific hypothesis generation

Surrogate modeling for simulators

Differentiable programming & PDE solvers

Foundation models for scientific data (text, code, graphs, time series, multimodal)

Data management & curation

Lab automation; autonomous agents for experiments

HPC, distributed training, accelerators, and efficient AI at scale

Benchmarking, evaluation protocols, and open-source toolchains

Scientific visualization, human-in-the-loop systems, and interactive assistants

Physics, astronomy, cosmology, HEP/NP, plasma & fusion, materials science

Inverse problems, instrument control, detector/beamline optimization

Quantum science & technology

Quantum-inspired ML

Generative design and retrosynthesis

Molecular property prediction

Reaction networks, catalysis, battery & energy materials discovery

Multiscale modeling, electronic structure, and spectroscopy analysis

Genomics, proteomics, structural biology, and systems biology

Bioinformatics, single-cell & spatial omics

Drug discovery and design

Neuroscience & cognitive science

Biomedical imaging and digital twins

Climate modeling, weather prediction, hydrology, and oceanography

Remote sensing, GIS, geophysics, ecology, and biodiversity monitoring

Disaster response, sustainability, and environmental policy support

Control, robotics & autonomous systems

CPS and digital twins

Fluid dynamics, aero/thermo/structural analysis, and manufacturing

Communications & networks, smart infrastructure, and energy systems

Automated theorem proving, program synthesis for scientific computing

Scientific workflows, MLOps, and experiment tracking in computational labs

Computational economics, epidemiology, demography, and policy modeling

Science of science, research knowledge graphs, meta-research

Ethics, safety, governance, and equitable access to scientific AI

Reproducibility, data sharing, licensing, and artifact evaluation