empiricalresearch.ai: Accelerating Scientific Discovery with AI

empiricalresearch.ai is a pioneering interinstitutional research group dedicated to advancing artificial intelligence for science through automated empirical research. By developing cutting-edge open-source tools like AutoRA (Automated Research Assistant) and SweetBean, the group empowers scientists across neuroscience, psychology, physics, and material science to streamline model discovery, experimental design, data collection, and documentation. Their mission centers on promoting reproducibility and transparency in research, leveraging AI to enhance scientific rigor and accelerate innovation. With strong academic backing from Schmidt Science Fellows, the Rhodes Trust, and Brown University’s Carney BRAINSTORM program, and supported by major grants from the National Science Foundation and the German Research Foundation, empiricalresearch.ai stands at the forefront of AI-driven open science.

Key Features:

• AutoRA (Automated Research Assistant): An open-source tool for automating research workflows, published in the Journal of Open Source Software (JOSS) with DOI: 10.21105/joss.06839.
• SweetBean: A specialized open-source package for automated empirical research, also published in JOSS with DOI: 10.21105/joss.07703.
• Scientific Model Discovery: AI-powered methods to identify and develop scientific models from data.
• Experimental Design Automation: Tools to generate and optimize experiments using AI.
• Open Science Commitment: Emphasis on transparency, reproducibility, and open data practices.
• Interdisciplinary Collaboration: Works with researchers across neuroscience, psychology, physics, and material science.
• Open-Source Ecosystem: Maintains and shares accessible, community-driven research tools.

Pricing: empiricalresearch.ai offers its core tools and resources as free, open-source software, enabling unrestricted access for researchers and institutions worldwide.

Conclusion: empiricalresearch.ai is a transformative force in scientific research, using AI to automate and enhance empirical discovery while championing open, reproducible science—a vital asset for researchers committed to innovation and integrity.