NIAID-BRC AI Codeathon for Infectious Disease Research

When: November 12–14, 2025

Where: Argonne National Laboratory, 9700 S Cass Ave, Lemont, IL (Outside of Chicago)

Application Deadline: October 15, 2025

Apply Here

Accelerating FAIR Data and Tools with AI

The NIAID Bioinformatics Resource Centers (BRCs) invite researchers, data scientists, and developers to apply for a three-day AI Codeathon focused on improving Findability, Accessibility, Interoperability, and Reusability (FAIR-ness) of BRC data and tools using artificial intelligence (AI) and large language models (LLMs). This event will bring together participants from diverse backgrounds to build prototypes that lower the learning barrier for new users, streamline data integration, and accelerate infectious disease science.

Codeathon Goals

Apply AI and LLMs to improve accessibility and usability of BRC data and tools.
Enhance interoperability and reuse of BRC resources.
Foster collaboration between infectious disease researchers, AI developers, and bioinformaticians.
Deliver openly available prototypes that can serve as seeds for long-term community solutions.

NOTE: This is not an AI training session with tutorials for learning AI. It is a hands-on codeathon where participants are expected to work in groups to generate working prototype code and tools that employ AI technologies to advance FAIR-ness and utility of BRC tools and data.

Potential Project Topics

Participants will form teams around proposed themes below or pitch new ideas:

Virtual BRC Helpdesk. Build an AI-powered helpdesk to guide users through complex bioinformatics tasks and lower the learning barrier.
Automated Workflow Generation and Execution. Develop AI tools to generate and run workflows from user descriptions using data and tools from BRCs and external resources.
Automated Knowledge Extraction and Curation. Apply AI to extract and curate key biological insights from literature or other sources.
Assign Functions to Uncharacterized Genes. Use AI-driven approaches to predict functions for uncharacterized genes in priority and prototype pathogens.
Outbreak Monitoring and Tracking. Develop an AI system to track, collect, filter, and process outbreak data from diverse sources for near real-time monitoring and reporting.
Virtual AI Co‑scientist. Create a multi-agent AI system that generates, debates, and ranks hypotheses based on user-defined research goals.

Expected Outcomes

Team presentations to the group and invited stakeholders.
Public sharing of code and documentation via GitHub.
Prototypes for potential integration into BRC resources.

Who Should Apply?

Infectious disease researchers and domain experts
Data scientists and AI/ML researchers interested in solving biological problems
Bioinformaticians and computational biologists
Students and trainees interested in data science

Logistics

Dates: November 12–14, 2025.

Location: In-person at Argonne National Laboratory, Lemont, Illinois, USA.

Format: Working in small collaborative teams, engaging in group discussions, coding, prototyping, testing, and presentations.

Application and Registration

Participation is free but space is limited. Apply by October 15, 2025.