Emily Mower Provost, Ph.D.

Professor of Electrical Engineering and Computer Science
Associate Chair, Division of Computer Science and Engineering
Department of Electrical Engineering and Computer Science
College of Engineering
Professor of Psychiatry

“Computational measures of mood and emotion have the potential to change how we think about the distribution of treatment. I am thrilled to collaborate with researchers at the Prechter Program to investigate next generation methods for assessing mood and understanding the course of bipolar disorder.”

- Emily Mower Provost, Ph.D.


Dr. Mower Provost received her B.S. in Electrical Engineering (summa cum laude and with thesis honors) from Tufts University and her M.S. and Ph.D. in Electrical Engineering from the University of Southern California (USC).

Dr. Mower Provost is an Associate Professor in the Computer Science and Engineering (CSE) Department. She is a member of Tau-Beta-Pi, Eta-Kappa-Nu, and a member of IEEE and ISCA. She has been awarded a National Science Foundation CAREER Award (2017), a National Science Foundation Graduate Research Fellowship (2004-2007), the Herbert Kunzel Engineering Fellowship from USC (2007-2008, 2010-2011), the Intel Research Fellowship (2008-2010), the Achievement Rewards for College Scientists (ARCS) Award (2009 – 2010), and the Oscar Stern Award for Depression Research (2015). She is a co-author on the paper, “Say Cheese vs. Smile: Reducing Speech-Related Variability for Facial Emotion Recognition,” winner of Best Student Paper at ACM Multimedia (2014), a co-author of the winner of the Classifier Sub-Challenge event at the Interspeech 2009 Emotion Challenge, and a co-author
of an honorable mention paper at ICMI 2016.

Her research interests are in human-centered speech and video processing and multimodal interface design. The goals of her research are motivated by the complexities of human emotion generation and perception.

As a member of the Prechter bipolar research team, Dr. Mower Provost leads the development of computational methods of predicting mood swings in bipolar disorder. Her work focuses on understanding the specific patterns that accompany transitions from healthy euthymic states to either mania or depression. She has worked to develop methodology to collect unstructured speech continuously and unobtrusively via the recording of day-to-day cellular phone conversations. Her investigations suggest that manic and depressive mood states can be recognized from these speech data, providing new insight into the feasibility of unobtrusive, unstructured, and continuous speech-based wellness monitoring for individuals with bipolar disorder.

Dr. Mower Provost’s work also focuses on understanding the human emotion perception process. This research is motivated by the critical need for novel methods that forward the assessment and treatment of mood disorders. Her work focuses on the link between changes in how people perceive emotion and changes in mood. This has important implications for developing therapies and characterizing the severity of mood disorders.