URAP

Alan Jian

Quantifying Goal Congruence using Natural Language Processing

The goal of my work is to identify issues amongst both industry and student teams and recommend solutions that can help teams navigate interpersonal dynamics. So far, I’ve focused my efforts on assessing a team’s goal alignment by studying each member’s responses to the questions: Did your team have a shared goal for your work together? If so, what was it? By using word embeddings and similarity algorithms, we hope to create a program that, given a class or company’s responses to this question, automatically pinpoints teams that are struggling to find common ground, and suggests solutions accordingly.

Message to Sponsor

Thanks again for supporting me during these trying times. I've learned some really meaningful lessons from the research I've conducted this summer, and we're excited to be pursuing a start-up based in our research in the near future. These advancements would not have been possible without your help.
  • Major: Data Science
  • Mentor: Sara Beckman, Haas School of Business