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Teddy Weaver graduated from Vanderbilt University in 2013 and spent over half a decade working in project management before realizing he needed a career change. Recognizing that pursuing a post-graduate degree would lead to a more fulfilling path, he set his sights on data science. Pursuing Data Science… Read More

The National Consortium for Data Science is a collaboration of leaders in academia, industry, and government formed to address the data challenges and opportunities of the 21st century. They are hosting their first springtime iteration of the Data Matters short-course series, virtually from March 13 –… Read More

Mortar sample taken at Caesarea’s Cruzader cathedral: (upper left) Eastern façade of the Cathedral; (lower left) mortar sample location marked with a flag; (lower right) close-up photo of the mortar sample location before taking the sample. Mortar is an essential part of construction, and has been used by builders for… Read More

We’re pleased to be able to introduce Zhaoqian (Joshua) Su as a new DSI Postdoctoral Fellow! Joshua comes to us from the Einstein College of Medicine where as a Postdoctoral Fellow he applied deep learning to problems related to the formation protein structures such as peptide… Read More

Interested in biomedicine, protein folding, protein dynamics, biological function, or spectroscopy? Want to learn more about the intersection of these topics with artificial intelligence (AI), deep learning (DL), computation, and data science? This may be the opportunity for you! The Mchaourab Lab investigates mechanisms of protein folding, and currently… Read More

About Dr. Phil Lieberman, Jewish Studies Research Context 1 The Torah was originally transcribed in Medieval times, where medieval scholars transcribed the consonants. This could produce ambiguity; consider the New York Times – if you read the words “sh rd ths”… Read More

About Clinical notes and other free-text documents provide a breadth of clinical information that is not often available within structured data. Transformer-based natural language processing (NLP) models, such as BERT, have demonstrated great promise to improve clinical text processing. However, these models are commonly trained on generic corpora,… Read More

About The goal of this project is to employ deep learning on paired EEG-MRI data in order to make MRI predictions based on EEG alone. The project currently has ~40 subjects with paired MRI-EEG data (collected separately but with the same task design), which will grow… Read More

About The Education and Brain Science Research Lab is beginning the Student Teacher Interaction Analytic (STiA) project to determine the relationship between executive function language used by teachers during reading instruction and reading outcomes. Executive function (EF) is a set of cognitive controls that support us in planning,… Read More

Looking to work with training transformers for revolutionizing learning engagement in the humanities? Read on to learn more about a novel application by Dr. Ole Molvig – assistant professor of History and founder of the Emergent Technology Lab at the Wond’ry! About Another project by Dr. Molvig for increasing… Read More