David Bamman, Electrical Engineering and Computer Science, Representation Learning for the Discovery of Musical Influence
Professor Bamman works on applying natural language processing and machine learning to empirical questions in the humanities and social sciences. In his Hellman-funded work, he plans to develop computational methods to uncover the layers of history in songs, reasoning about their content—both their musical structure and the text of their lyrics—in order to discover patterns of influence and allusion.
Courtney Dressing, Astronomy,
Characterizing Planetary Systems Orbiting Nearby Stars
Professor Dressing is an observational astronomer focused on detecting and characterizing planetary systems orbiting nearby stars. Her Hellman-funded research will set the foundations for future detections of life as well as advance understanding of how planetary systems form and evolve over time by investigating the properties of nearby planets.