🧑🏻🔬 Lead machine learning scientist @ Insitro
🐾 A proud owner of samoyeds
🏛 Completed Ph.D. at MIT CSAIL
🏃♂️ Staying active in Cambridge, MA
We need Efficient AI
🚀 connecting human rationales with model attention for low-resource learning1
🚀 meta learning over distributional signatures for few-shot classification2
We need Robust AI
🛡 identifying spurious correlations by contrasting different data environments3
🛡 transferring the knowledge of biases across tasks4
🛡 learning to split any dataset so that predictors cannot generalize across the splits5
Want to know more? Check out my thesis defense on YouTube.
Learning is a lifelong journey.
🎓 B.S. in Mathematics & Applied Mathematics, Shanghai Jiao Tong University, 2016.
🎓 M.A. in Mathematics, University of Wisconsin-Madison, 2017.
🎓 S.M. in Computer Science, MIT, 2019.
🎓 Ph.D. in Computer Science, MIT, 2022 (advised by Regina Barzilay).
🧐 Continue thinking.
- Yujia Bao, Shiyu Chang, Mo Yu, Regina Barzilay. “Deriving Machine Attention from Human Rationales.” EMNLP 2018.
- Yujia bao, Menghua Wu, Shiyu Chang, Regina Barzilay. “Few-shot Text Classification with Distributional Signatures.” ICLR 2020.
- Yujia Bao, Shiyu Chang, Regina Barzilay. “Predict then Interpolate: A Simple Algorithm to Learn Stable Classifiers.” ICML 2021.
- Yujia Bao, Shiyu Chang, Regina Barzilay. “Learning Stable Classifiers by Transferring Unstable Features.” ICML 2022.
- Yujia Bao, Regina Barzilay. “Learning to Split for Automatic Bias Detection.” arXiv 2022.