معرفی
Ruth Fong is a Teaching Professor at the Department of Computer Science, Princeton University, where she teaches foundational and advanced AI/ML courses (COS324, COS126) while leading the Looking Glass Lab in explainable AI research. She collaborates closely with the Visual AI Lab and Professor Olga Russakovsky.
- Education:
- PhD in Visual Geometry Group, University of Oxford (advised by Andrea Vedaldi, funded by Rhodes Trust and Open Philanthropy)
- MSc in Neuroscience, University of Oxford (with Rafal Bogacz, Ben Willmore, and Nicol Harper)
- AB in Computer Science, Harvard University (with David Cox and Walter Scheirer)
Research Focus: Pioneering Explainable AI and ML Fairness, with emphasis on post-hoc model understanding, interpretable-by-design architectures, and human-AI interaction frameworks. Her work spans computer vision, self-supervised learning, and neuroscience-inspired methodologies.
Publication Trends: Recent papers (2023-2025) analyze interactive explanations, concept salience, and gender artifacts in vision datasets. Earlier work (2017-2020) established foundational techniques in extremal perturbations, backpropagation saliency, and neural network interpretability.
- Scientific Awards:
- Princeton Engineering Council Teaching Award (2025)
- Keller Center Summer Course Development Grant (2025)
- CHI Honorable Mention Paper Award (2023)
- Open Philanthropy AI Fellowship (2018)
- Rhodes Scholarship (2015)
Advising: Directly mentored 10 Princeton undergraduates on IW/senior theses projects spanning generative AI, medical imaging fairness, and interactive visualization tools. Grants include Princeton SEAS and Open Philanthropy funding for the Looking Glass Lab.
Lab & Team: Leads the Looking Glass Lab with 6 graduate/postgraduate members including Rawand Aziz, Matthew Barrett, and Ben Wachspress. Collaborates with faculty across Princeton and Oxford.
