Jiachen Yao

About Me

Hello! I’m a Ph.D. student in Computing and Mathematical Sciences at Caltech, where I am fortunate to be advised by Professor Anima Anandkumar. My research lies at the intersection of machine learning, scientific computing, and real-world applications.

Prior to my PhD, I completed my undergraduate studies at Tsinghua University, where I had the privilege of working with Professor Jun Zhu and Professor Hang Su on physics-informed machine learning. I am also grateful for the opportunity to conduct research at Stanford University, where I worked with Professor James Landay and Professor Monica Lam on human-AI interaction.

Research Interests

My long term goal is to develop a unified framework that learns and uses efficient representations of data, domain knowledge, and available observations to model complex systems. I am particularly interested in generative approaches to achieve this objective.

Currently, I am focused on developing scalable and efficient algorithms for solving partial differential equations (PDEs) and inverse problems. My research involves developing probabilistic models in function spaces that capture the range of possible states under certain conditions, addressing not only forward and inverse problems but also incorporating more flexible constraints and uncertainty.

News

[Dec. 2024] I’ll attend NeurIPS 2024 in Vancouver. Feel free to reach out!
[Sept. 2024] Our paper, “PINNacle: A Comprehensive Benchmark of PINNs for Solving PDEs,” has been accepted to NeurIPS 2024 Datasets and Benchmarks Track!
[Jul. 2024] I graduated with honors from Tsinghua University, recognized as an Outstanding Graduate by both the Beijing Ministry of Education and Zhili College.
[Apr. 2024] I’ll be starting my Ph.D. in Computing and Mathematical Sciences in Professor Anima Anandkumar’s group at Caltech!

Publications

NeurIPS

PINNacle: A Comprehensive Benchmark of PINNs for Solving PDEs

Zhongkai Hao*, Jiachen Yao*, Chang Su*, Hang Su, Ziao Wang, Fanzhi Lu, Zeyu Xia, Yichi Zhang, Songming Liu, Lu Lu, and Jun Zhu.

Conference on Neural Information Processing Systems (NeurIPS), 2024.

PDF Code Project Page BibTex

WhisperBuds: Whispered Speech Input with Earbuds

Jackie Yang*, Jiachen Yao*, Yingtian Shi, Monica Lam, and James Landay.

In submission, 2024.

PDF Video

Preconditioning for Physics-Informed Neural Networks

Songming Liu, Chang Su*, Jiachen Yao*, Zhongkai Hao, Hang Su, Youjia Wu, and Jun Zhu.

In submission, 2024.

PDF BibTex

ICML

MultiAdam: Parameter-wise Scale-invariant Optimizer for Multiscale Training of Physics-informed Neural Network

Jiachen Yao*, Chang Su*, Zhongkai Hao, Songming Liu, Hang Su, and Jun Zhu.

International Conference on Machine Learning (ICML), 2023.

PDF Code BibTex

CHI

Selecting Real-World Objects via User-Perspective Phone Occlusion

Yue Qin, Chun Yu, Wentao Yao, Jiachen Yao, Chen Liang, Yueting Weng, Yukang Yan,and Yuanchun Shi.

Conference on Human Factors in Computing Systems (CHI), 2023.

PDF Video BibTex

* denotes equal contribution

Services

As a reviewer

Honors and Awards

Undergrad Honors

Outstanding Graduate by both the Beijing Ministry of Education and Zhili College
National Scholarship (highest undergrad honor in China, top 0.2% nationwide)
Selected to UGVR Program to conduct a summer research internship at Stanford (fully funded)
Selected to Spark Program at Tsinghua University (top 1%)
Tsinghua Scholarship for Comprehensive Excellence
Tsinghua Scholarship for Innovation
Zhili College Dean’s List (7/219)
Silver Medal in National Olympiad in Informatics (top 100 nationwide)