Emily Jin

Hi — I'm Emily! I'm an incoming Ph.D. student in Computer Science at Stanford University. I'll be supported by the NDSEG Fellowship and was also honored to receive the NSF GRFP.

Previously, I earned my B.S. in Mathematics and M.S. in Computer Science at Stanford. During this time, I had the privilege of working with Prof. Jiajun Wu, Prof. Tobias Gerstenberg, and Prof. Li Fei-Fei on projects exploring visual reasoning and its intersection with cognitive science.

Email / Scholar / Github / LinkedIn

Research

My research interests lie in machine learning and computer vision, with a focus on developing machines that leverage a structured understanding of the visual world to reason with human-like flexibility. Drawing inspiration from human cognition, I aim to explore how machines can (1) learn structured visual representations at the "right" level of abstraction, and (2) perform complex, real-world reasoning grounded in these representations.

	Predicate Hierarchies Improve Few-Shot State Classification Emily Jin, Joy Hsu, Jiajun Wu ICLR, 2025 project page / paper / code
	MARPLE: A Benchmark for Long-Horizon Inference Emily Jin, Zhuoyi Huang, Jan-Philipp Fränken, Weiyu Liu, Hannah Cha, Erik Brockbank, Sarah A. Wu, Ruohan Zhang, Jiajun Wu, Tobias Gerstenberg NeurIPS Datasets and Benchmarks Track, 2024 project page / paper / code
	Whodunnit? Inferring What Happened From Multimodal Evidence Sarah A. Wu, Erik Brockbank, Hannah Cha, Jan-Philipp Fränken, Emily Jin, Zhuoyi Huang, Weiyu Liu, Ruohan Zhang, Jiajun Wu, Tobias Gerstenberg CogSci, 2024 preprint / pdf / poster / code
	Mini-BEHAVIOR: A Procedurally Generated Benchmark for Long-horizon Decision-Making in Embodied AI Emily Jin, Jiaheng Hu, Zhuoyi Huang, Ruohan Zhang, Jiajun Wu, Li Fei-Fei, Roberto Martín-Martín NeurIPS GenPlan Workshop & NeurIPS ALOE Workshop, 2023 paper / poster / code
	Modeling Dynamic Environments with Scene Graph Memory Andrey Kurenkov, Michael Lingelbach, Tanmay Agarwal, Emily Jin, Chengshu Li, Ruohan Zhang, Li Fei-Fei, Jiajun Wu, Silvio Savarese Roberto Martín-Martín ICML*, 2023 project page / paper / code
	MOMA-LRG: Language-Refined Graphs for Multi-Object Multi-Actor Activity Parsing Zelun Luo, Zane Durante, Linden Li, Wanze Xie, Ruochen Liu, Emily Jin, Zhuoyi Huang, Lun Yu Li, Ruohan Zhang, Jiajun Wu, Juan Carlos Niebles, Ehsan Adeli, Li Fei-Fei NeurIPS Datasets and Benchmarks Track, 2022 project page / paper / code

Teaching & Outreach

Over the years, I've been incredibly lucky to find support from inspiring mentors and inclusive communities. These experiences have motivated me to give back through teaching and outreach:

Stanford AI4ALL.
Program Manager, 2020-2025.

Stanford CS 231N. Deep Learning for Computer Vision.
Course Assistant, Spring 2025.

Stanford CS 157. Introduction to Logic.
Course Assistant, Fall 2024.

Stanford TreeHacks
Organizer, 2021.

AIHacks. Southern California's first all-female high school hackathon.
Founder and Executive Director, 2019-2020
Media: Spectrum News / Los Angeles Daily News

Website source from Jon Barron.