440 Huntington Avenue
350 West Village H
Boston, MA 02115
ATTN: Andrea Danyluk, 202WVH
360 Huntington Avenue
Boston, MA 02115-5000
- BA in Mathematics/Computer Science, Vassar College
- PhD in Computer Science, Columbia University
Andrea Danyluk is the Global Director of the Align Master’s Program and Visiting Professor at Northeastern University. She comes to Northeastern from Williams College, where she is the Mary A. and William Wirt Warren Professor of Computer Science. At Williams she has served as Chair of the Computer Science Department, of the Cognitive Science Program, and as Acting Dean of the Faculty. Prior to joining the faculty at Williams, she was a researcher at NYNEX (now Verizon).
Danyluk’s research interests are in machine learning, where her work has been motivated by a variety of applications, from telecommunications to computational music. Within that application context, she has worked on problems such as data error, cost sensitivity, and feature selection. She has served as both Program co-Chair and General Chair of ICML.
Danyluk is also active in Computer Science education. She is a co-author of a textbook – Java: An Eventful Approach –with Kim Bruce and Tom Murtagh, and was a member of the ACM/IEEE-CS Task Force on CS Curricula 2013. She is currently a member of the ACM Education Council, as well as co-Chair of the ACM Data Science Task Force.
Danyluk has been a member of CRA-W, the Computing Research Association’s Committee on the Status of Women in Computing Research, since 2008, where her projects focus primarily on undergraduate research mentoring.
She received her BA from Vassar College and her PhD from Columbia University.
What is your field of research/teaching?
My fields of research include Machine Learning and Computer Science Education.
What are the specifics of your educational background?
I received a PhD in Computer Science at Columbia University and a BA in Mathematics/Computer Science at Vassar College.
What is your research focus in a bit more detail? Is your current research path what you always had in mind for yourself, or has it evolved somewhat? If so, how/why?
My CS disciplinary research lies squarely in Machine Learning. I have always been motivated by real applications, as they help bring to light interesting research questions. Over the past decade or so, I have become increasingly involved in Computer Science Education research. As a professor who is passionate about teaching, I am especially interested in developing curricula and pedagogy that make students excited about computer science and that allow them to thrive.