Hi! I’m Irena, a CS Ph.D. student at Stanford University. My research interests center on trustworthy machine learning, especially in the context of large models.

Previously, I also did my undergraduate at Stanford, where I studied Computer Science (B.S. with honors), Statistics (M.S.), and a bit of art history. Here’s a randomly sampled favorite artwork.

Many kind researchers have had an outsized impact on my career! If I can be helpful in your journey (e.g. by suggesting classes or chatting about grad school), feel free to email me at my first name [at] cs.stanford.edu.

Selected Publications

  1. OpenFlamingo: An open-source framework for training large autoregressive vision-language models
    Anas Awadalla*, Irena Gao*, Joshua Gardner, Jack Hessel, Yusuf Hanafy, Wanrong Zhu, Kalyani Marathe, Yonatan Bitton, Samir Gadre, Shiori Sagawa, Jenia Jitsev, Simon Kornblith, Pang Wei Koh, Gabriel Ilharco, Mitchell Wortsman, and Ludwig Schmidt
  2. Adaptive Testing of Computer Vision Models
    Irena Gao, Gabriel Ilharco, Scott Lundberg, and Marco Tulio Ribeiro
    In International Conference on Computer Vision 2023. (Oral Presentation)
  3. Out-of-Domain Robustness via Targeted Augmentations
    Irena Gao*, Shiori Sagawa*, Pang Wei Koh, Tatsunori Hashimoto, and Percy Liang
    In International Conference on Machine Learning 2023.
  4. Extending the WILDS benchmark for unsupervised adaptation
    Shiori Sagawa*, Pang Wei Koh*, Tony Lee*, Irena Gao*, Sang Michael Xie, Kendrick Shen, Ananya Kumar, Weihua Hu, Michihiro Yasunaga, Henrik Marklund, Sara Beery, Etienne David, Ian Stavness, Wei Guo, Jure Leskovec, Kate Saenko, Tatsunori Hashimoto, Sergey Levine, Chelsea Finn, and Percy Liang
    In International Conference on Learning Representations 2022. (Oral Presentation)

* denotes equal contribution.