UROP Openings

Have a UROP opening you would like to submit?

Please fill out the form.

Submit your UROP opening

Expresso Depresso


Term:

Spring-Summer

Department:

MAS: Media Arts and Sciences

Faculty Supervisor:

Cynthia Breazeal

Faculty email:

cynthiab@media.mit.edu

Apply by:

March 2nd, 2020 for Spring funding.

Contact:

Felipe Moreno, pipemon@mit.edu

Project Description

Due to the widespread inaccessibility to mental health services in the world today and the stigma associated with mental illnesses, we propose a novel system to effectively detect depression markers and the severity of such with minimal intrusiveness and high reliability. The project's objective consists in creating a deep learning model to extract meaningful features associated to depression from interviews with participants, detecting the levels of depression in patients and understanding the fundamental markers in the prediction process.

Pre-requisites

- Proficiency with Python. - Machine learning familiarity at the level of 6.036/6.034. - Practical experience in machine learning or deep learning projects. - Experience in computer vision and/or signal processing is a plus. - Understanding of the Japanese language is a plus since the dataset contains interviews conducted with Japanese participants.