In this project, we aim to develop GAN based models to predict spatio-temporal evolution using open human mobility datasets – SafeGraph (https://www.safegraph.com/).

This is an UNPAID research project, and can be done for course credit. To apply for this project, please email the project PI directly with your application materials (resume and statement of interest).

Faculty Advisor

  • Professor: Sharon Di
  • Center/Lab: CEEM
  • Location: Mudd 630
  • autonomous driving, deep learning in transportation

Project Timeline

  • Earliest starting date: 9/1/22
  • End date: 8/30/23
  • Number of hours per week of research expected during Fall 2022: ~20

Candidate requirements

  • Skill sets: M.S. are welcome to register my research credits during the semesters and summer. The student involved in this project will develop GAN based models that can predict. spatio-temporal evolution of human mobility. Students with coding skills and past experience in analyzing spatio-temporal data and training GAN models are preferred. Skill requirements are:
    1. Familiar with Python. Generating figures, graphs, tables, or statistical models to present results with python.
    2. Familiar with GAN and its variant models.
    3. Having past experience in doing research and demonstrating independent research capabilities.
  • Student eligibility: freshman, sophomore, junior, senior, master’s
  • International students on F1 or J1 visa: NOT eligible
  • Academic Credit Possible: Yes
  • Application Instructions: Please send an email to project PI Professor Di with your resume attached and a statement of interest in the body of the email.