We are happy to announce a new Special Collection in “Accelerating scientific discoveries through data-driven innovations” in Patterns.
Patterns is a premium open-access journal from Cell Press, publishing ground-breaking original research across the full breadth of data science. The journal aims to share data science solutions to problems that cross domain boundaries.
Developing artificial intelligence (AI) and machine learning (ML) methods and models that can accelerate scientific discoveries and advance science has become one of the important research directions for the AI/ML research community. It has been gaining increasing attention from researchers in diverse scientific areas, including biomedical science, materials science, climate science, physics, chemistry, and many others. Data-driven AI/ML innovations to enable reliable predictions and optimal decision-making for scientific discoveries face several critical challenges, among which are high system complexity, large search space, incomplete knowledge, and small data, all of which demand novel strategies to effectively address them. Meeting these changes and thereby accelerating scientific discoveries and industrial innovations calls for research that can take full advantage of the latest advances in AI/ML to integrate data-driven techniques with scientific knowledge and principles and is able to execute them in a modern HPC environment at scale.
We invite researchers working in the forefront of accelerating scientific discoveries through innovations in machine learning (ML), AI, and data-driven modeling to submit their latest research findings to the special collection to inspire the next wave of data-driven innovations in various scientific domains.
Specific topics of interest include, but are not limited to:
- Cross-cutting research at the intersections of mathematics, ML/AI, and computing
- Scientific ML/AI integrating data-driven techniques with scientific knowledge/principles
- Uncertainty-aware techniques of learning, inference, and optimization
- Computational challenges for high-performance computing and data at extreme scales
- Data-driven discoveries/innovations in complex scientific and industrial problems
We solicit papers that can showcase the state of the art in scientific ML/AI, applied mathematics, and high-performance computing that can meet the challenges that stem from large-scale data, extreme-scale computing requirements, and the need for decision-making pertinent to complex systems in the presence of significant uncertainties, which altogether can accelerate scientific discoveries through data-driven approaches. While we look for submissions of original research articles that report the latest research findings and breakthroughs in the field, we welcome various article types considered by Patterns, which include review and perspective articles.
Manuscripts should be prepared according to the guide for authors and should be submitted online, mentioning in the cover letter that you are submitting for the “Accelerating scientific discoveries through data-driven innovations” special collection.
The article processing charge will be waived for the first five manuscripts to be accepted for publication.
For further information, visit the following link on the Patterns website:
BioMLSP Lab 