Building Transparent ML/AI Solutions to Advance Biological Research Codeathon

Date and Time:  February 26th to March 1st, 2024 11 AM -5 PM (EST)

Details:  Machine Learning and Artificial Intelligence continue to play pivotal roles in scientific progress, so there is a growing need for collaboration, knowledge sharing, and an exploration of the transparent deployment of ML/AI in research. To address this growing need, we are hosting a codeathon, “Building transparent ML/AI solutions to advance biological research”. 

This codeathon will be held virtually and aims to bring together developers, data scientists, and tech enthusiasts to build equitable and transparent ML/AI solutions that tackle various problems in healthcare, research, education, and more. 

After the codeathon, we will make the team products publicly available through the NCBI Codeathons GitHub Organization and may feature team projects on NCBI sites.

More information about this event is available on our NCBI Outreach Events Page.

NCBI Faculty: 

Alexa Salsbury, PhD is the lead for this codeathon. Her background is in structural biology, computational chemistry, biophysics, CADD, and data science.
Rana Morris, PhD is a NCBI Subject Matter Expert and support for this codeathon. With over 20 years of experience at NCBI, her background includes biochemistry, molecular and cellular biology, genetics, genomics, diagnostic development, and coordination of genetics/genomics components in clinical trials.
E. Sally Chang, PhD is a NCBI Subject Matter Expert and support for this codeathon. Her background is in eukaryotic genome analysis, with a focus on cnidarian genome and transcriptome sequences as models for understanding biological processes.
Brian Koser is the cloud lead for this codeathon. He is a Cloud Administrator at NCBI and has been supporting Cloud-based data sharing projects at NIH for the past thirteen years. 
 
Contact: codeathons@ncbi.nlm.nih.gov