Johns Hopkins UniversityEst. 1876

America’s First Research University

Call for Proposals: Foundations of Data Science and AI

Award Amount: Up to $60,000 (one award available) 

Performance Period: Awarded Spring 2026; funds must be expended by the end of fiscal year 2027. 

As AI and data science continue to rapidly evolve, maintaining a pipeline of fundamental, theory driven, and basic research is critical to driving the next generation of breakthroughs. 

This mechanism is designed to seed highly innovative, high-risk/high-reward basic research in data science and artificial intelligence. The Data Science and AI Institute (DSAI) is seeking proposals that explore novel theoretical frameworks, algorithmic innovations, or consider foundational questions regarding AI or the augmentation of human intelligence by AI. 

Proposals must focus on basic research and fundamental advances of DSAI. While not an exhaustive list, competitive proposals might address one or more of the following foundational challenges: 

  • Next-Generation Computational Frameworks: Developing novel neural architectures beyond current transformer paradigms, including state-space models, energy-based models, or neuro-symbolic systems that integrate learning with logical reasoning. The strongest proposals will focus on justifications and analysis that go beyond empirical demonstration.  
  • Theoretical Foundations of AI: Advancing the mathematical understanding of modern machine learning frameworks, including the analysis of optimization problems, generalization bounds, expressivity, sampling and modern generative models, and the theoretical limits of representation learning. 
  • Causality and Robustness: Foundational approaches to causal discovery, causal inference, and out-of-distribution generalization, enabling models that inform on the underlying data-generating mechanisms rather than mere correlations. Of particular interest is the study of causality in very large models.  
  • Intelligence Augmentation: Basic research into systems designed to augment human intelligence. This includes the fundamental science of human-AI teamwork, value alignment, and models natively designed to reason alongside human experts. 
  • Efficiency and Scalability: Foundational algorithms that drastically reduce the computational complexity, memory requirements, or data requirements of training and deploying large-scale AI models. 
  • Other foundational areas of DSAI.  

(Note: Proposals focused on applying existing DSAI methods to domain-specific problems, such as clinical prediction or materials discovery, are explicitly outside the scope of this call.) 

Eligibility

  • The Principal Investigator (PI) must be a DSAI faculty member.
  • Co-investigators may be from any Johns Hopkins division and may include non-faculty members with relevant expertise.
  • MS/PhD students, undergraduates, and teaching faculty are not eligible to serve as a project’s PI and proposals submitted solely by such individuals will be considered non-responsive.
  • A Principal Investigator may submit no more than one proposal as lead PI.
  • Awardees will be asked to serve as reviewers in the subsequent funding cycle.

Deadlines 

  • Submission deadline: April 13, 2026
  • Awards announced: June 1, 2026
  • Award start date: June 15, 2026
  • Funds must be spent by: May 15, 2027
  • Final report due: June 15, 2027

Learn more and submit a proposal (JHU affiliate access only)

The deadline for proposal submissions is Monday, April 13.  

Contact 

For any questions about the Foundations of Data Science and AI call for proposals, please email dsai-academics@jhu.edu.