The lab won its first R01 from the NIH! This project is sponsored by the NIH BRAIN Initiative’s Theory, Models, and Methods (TMM) Program. We look forward to doing rockin’ science with our collaborators in the Hengen lab under this award!

The lab was selected to receive a McKnight Foundation Technological Innovations in Neuroscience Award to fund our work in neural distribution alignment!! (Article)

Aish’s paper on deep representation learning for neuroanatomy is submitted!

Check out our preprint on bioRxiv (Link) and a short version of the paper that appeared in a recent ICML Workshop on Scientific Discovery (Link)!

Congratulations to Max Dabagia for being awarded a NSF Graduate Research Fellowship! Max will be starting his PhD in the ML-CS program in Fall. Way to go Max!!

At the main meeting, John presented new results on using optimal transport for distribution alignment at NeurIPS. Check out the paper and a website where we discuss applications of the method to neural recordings.

Following the main meeting, Max presented his work on using Wasserstein barycenter regression for connectomics at the Optimal Transport for Machine Learning (OTML) Workshop. The workshop was great, we learned a lot!

NerDS lab members developed an intro to image analysis and deep learning for high school students. We taught the module to two groups of high school students that participated in the HOT Days program organized by the ECE department at Georgia Tech.

Our python notebook and instructions on how to use Colaboratory are located on the lab’s github page. (Hands on Tech Github Repo)