The goal of this project is to develop and validate a deep neural network that predicts a child’s emotion and cognition. DSI scholars will implement 3D convolutional neural networks on brain imaging data from thousands of children to predict cognitive, emotional, and socio-developmental variables. Statistical evaluation of the model performance will be conducted. The scalable deep neural network analysis will help find brain underpinnings of cognition and emotion.

One selected candidate will receive a stipend via the DSI Scholars program. Amount is subject to available funding.

Faculty Advisor

  • Professor Jiook Cha
  • Department/School: Division of Child and Adolescent Psychiatry/College of Physicians and Surgeons
  • Location: CUMC
  • We are interested in application of big data analytics to clinical neuroscience in the field of psychiatry.

Project timeline

  • Earliest starting date: 03/01/2019
  • End date: 08/31/2019
  • Number of hours per week of research expected during Spring 2019: ~10
  • Number of hours per week of research expected during Summer 2019: ~20

Candidate requirements

  • Skill sets: deep learning packages, such as pytorch, tensorflow, keras.
  • Student eligibility (as of Spring 2019): freshman, sophomore, junior, senior, master’s
  • International students on F1 or J1 visa: eligible
  • Additional comments: Scholars require clearance to work at the new york state psychiatric institute.