About
I work to harness machine learning and data science to drive sustainability efforts and social good. Currently, I am exploring how to use volunteer-collected data to build effective machine learning models for biodiversity monitoring.
I am an incoming PhD in EECS at MIT where I will be advised by Sara Beery and Sherrie Wang. Previously, I was at Stanford University where I received an M.S. in Computer Science, specializing in Artificial Intelligence, a B.S. with Distinction in Electrical Engineering, specializing in Information Systems & Science, and a Notation in Science Communication with Distinction.
Research
Selected Works
Affiliations
Science Communication
At Stanford, I received a Notation in Science Communication with Distinction. As a part of this notation, I built skills to effectively communicate data and scientific findings to a variety of audiences. My science communication portfolio showcases various projects from my time at Stanford and can be viewed below or by clicking here.
Presentations & Featured
DivShift
- AIhub (Blog Post) (May 2025)
- Stanford EarthML Seminar (Talk) (Apr 2025)
- Berkeley Stanford Meetup for Women in Computer Science & Electrical Engineering (Talk) (Apr 2025)
- AAAI-25 Special Track on AI for Social Impact (Oral Presentation) (Feb 2025)
- NeurIPS 2024 Workshop on Tackling Climate Change with Machine Learning (Poster & Recorded Talk) (Dec 2024)
