Rui (Rachel) Yan

Ph.D. Candidate

Institute for Computational and Mathematical Engineering

Stanford University
ruiyan [at] stanford [dot] edu
 LinkedIn /  GitHub /  Google Scholar

Hello! I am a third-year Ph.D. student in Computational and Mathematical Engineering (ICME) at Stanford University, advised by Prof. Lei Xing.

My research interests focus on the intersection of artificial intelligence (AI) and healthcare. Specifically, I am interested in representation learning and machine learning, and developing computational tools that can effectively learn representations from biomedical data. My work is particularly focused on addressing the unique challenges presented by high-dimensional, multi-modal, and decentralized data.

Prior to starting my Ph.D., I received my B.S. in Applied Math and Statistics from UCLA and my M.S. from Stanford University, where I worked with Prof. Serena Yeung and Prof. Jure Leskovec on medical image analysis and commonsense reasoning. Beyond academia, I have also worked at Facebook, Uber AI, and Microsoft Research.


Selected Publications

Label-Efficient Self-Supervised Federated Learning for Tackling Data Heterogeneity in Medical Imaging
Rui Yan, Liangqiong Qu, Qingyue Wei, Mars Huang, Liyue Shen, Daniel Rubin, Lei Xing, Yuyin Zhou
IEEE Transactions on Medical Imaging (2023) [Paper] [arXiv] [Code]

Correlative Image Learning of Chemo-mechanics in Phase-transforming Solids
Haitao Deng, Hongbo Zhao,..., Rui Yan, ..., Andrew M. Minor, William C. Chueh
Nature Materials (2022) [Paper] [Code]

Stochastic Models Accounting for Hidden Cell-drug Interactions
Song Yi Bae, Ning Guan, Rui Yan, Katrina Warner, Scott D. Taylor, Aaron S. Meyer
Cell Death & Disease (2020) [Paper] [Code]

Course Projects

Evaluation Metrics for Split and Rephrase
Stanford CS224n Natural Language Processing with Deep Learning
[Report] [GitHub]

Prediction of Gene Expression from Histopathology Images via Deep Learning in Gastric Cancer
Stanford CS271 Artificial Intelligence in Healthcare
[Report]

CNN Image Recognition Architecture Simplification
Stanford CS229 Machine Learning
[Poster] [Report] [GitHub]

Microscopy Cell Classification with Image Processing and SVM classifier
UCLA NSF-REU project advised by Prof. Marcus Roper
[Report]

Investment Portfolio Analysis -- Statistical Models in Finance
STATSC283 project: analyzed porfolio of 30 stocks from 5 industries
[Report]

Experience

 Internships
  • Research Intern @ Microsoft Research, Redmond, WA Summer 2022
  • Research Engineer Intern @ Uber AI, San Francisco, CA Summer 2021
  • Data Scientist Intern, Infra @ Facebook (now Meta), Menlo Park, CA Summer 2020

 Teaching Assistant
  • ICME Data Science Summer Workshop @ Stanford Summer 2021 & 2022
  • CS224N: Natural Language Processing with Deep Learning @ Stanford Winter 2021
  • EE364A: Convex Optimization @ Stanford Summer 2020
  • PIC20A: Java Programming @ UCLA Winter & Spring 2019
  • PIC16: Python Programming @ UCLA Fall 2018

Awards
Misc.
  • In my free time, I enjoy reading and hiking.