We are looking for talented data scientists to support the data processing and learning in the Startup Cartography Project and its follow-on project, the Artificial Intelligence in Entrepreneurship Lab.
Project: analyze behavior of Siamese fighting fish (Betta splendens) as part of a collaboration between the Bendesky and Cunningham labs of the Zuckerman Institute (NeuroTheory Center)
The Milky Way swarms with orbiting satellite dwarf galaxies of astounding diversity. Some galaxies continue to form stars while others stop and dim in brightness. In computer simulations, the evolutionary history of each dwarf galaxy that leads to these differences is known. Galaxies can lose gas and stop forming stars due to early exposure to stellar radiation (reionization), interaction with the hot gas of the host (ram-pressure stripping), or gravitational interactions with the host/dwarf galaxies (tidal effects).
A central issue facing systems neuroscience is defining the rich naturalistic behavioral repertoire that mice engage in under psychiatrically relevant situations. Recent advances in deep learning (e.g., DeepLabCut) have made frame by frame detailed pose estimation possible. However, this dense behavioral data requires new techniques for defining the ethogram (full description of behavior). To date, researchers have used frequency based time series approaches to tackle this problem, with significant limitations. An alternative approach would be to take advantage of new topology methods (persistent homology and directed algebraic topology) to characterize the shapes formed by mouse limb trajectories. Such an approach would have broad application in systems neuroscience. For this project, the student will use machine learning to label animal body parts, then topology to characterize the ethogram and compare the results to existing approaches.
Call for Faculty Participation. December 2019.
The Data Science Institute is pleased to call for Faculty Participation in the Spring and/or Summer 2020 sessions of the 3rd cohort of Data Science Institute (DSI) Scholars Program. The goal of the DSI Scholars Program is to engage undergraduate and master students to work with Columbia faculty, through a data science research internship. Last year, we worked with 47 projects and received more than 400 unique applications from Columbia Students. The program’s unique enrichment activities will foster a learning and collaborative community in data science at Columbia.