We will further develop a large scale dataset that evaluates gender biases in sentence-level NLP systems. We will then develop training techniques to encourage models to overcome and mitigate gender-based biases.

This project is eligible for a matching fund stipend from the Data Science Institute. This is not a guarantee of payment, and the total amount is subject to available funding.

Faculty Advisor

  • Professor: Adam Poliak
  • Department/School: Computer Science/Barnard
  • We study the reasoning capabilities and biases in natural language processing models. We also apply natural language processing to other fields to glean insights from large amounts of text.

Project Timeline

  • Earliest starting date: 3/1/2021
  • End date: 9/1/2021
  • Number of hours per week of research expected during Spring 2021: ~8
  • Number of hours per week of research expected during Summer 2021: ~35

Candidate requirements

  • Skill sets: Python, Machine Learning, bash/unix
  • Student eligibility: freshman, sophomore, junior, senior, master’s
  • International students on F1 or J1 visa: eligible
  • Academic Credit Possible: Yes