Computational Social Science, Machine Learning Analysis of Structured
and Unstructured Data, Bayesian Statistics
Professor Wallach's primary research goal is to develop new mathematical models and computational tools for analyzing vast quantities of structured and unstructured data in order to identify and answer social science questions. Specifically, she is interested in analyzing complex data regarding communication and collaboration within scientific and technological innovation communities, in order to advance the study of science and innovation policy. To this end, she works on techniques for aggregating and representing amounts of information from multiple data sources with disparate emphases, methods for analyzing relational and social network data, efficient algorithms for inference, and robust methods for reasoning under uncertain information. Professor Wallach's research contributes to machine learning, Bayesian statistics, and, in collaboration with social scientists, to the nascent fields of science and innovation policy and, more generally, computational social science.
Ph.D., Physics, University of Cambridge (2008), M.Sc., Informatics, University of Edinburgh (2002), B.A., Computer Science, University of Cambridge (2001). Professor Wallach joined the College of Information and Computer Sciences in 2007 as a Senior Postdoctoral Research Associate and became a tenure-track Assistant Professor in 2010 as part of UMass Amherst's interdisciplinary research cluster in computational social science.
In 2010, Professor Wallach (along with co-authors Ryan Prescott Adams and Zoubin Ghahramani) won the Best Paper Award at AISTATS. She is currently a co-PI on a three-year National Science Foundation grant to develop "New Methods to Enhance Our Understanding of the Diversity of Science." In addition to her research, she works to promote and support women's involvement in computing. In 2006, she co-founded an annual workshop for women in machine learning. Previously, Professor Wallach was awarded the University of Edinburgh's 2001/2002 prize for Best M.Sc. Student in Cognitive Science. While an undergrad, she won the award for the best computer science student in the 2001 U.K. Science Engineering and Technology Awards.