Hello! I am a first-year PhD student at Stanford, where I am grateful to be advised by Percy Liang and Greg Valiant. My research is in natural language processing, machine learning, and theory. In the past, I've worked on syntactic parsing, grammar induction, and multilingual modeling.
If you're an undergrad and you have questions about research or grad school, feel free to email me!
Low Complexity Probing via Finding Subnetworks Steven Cao, Victor Sanh, Alexander M. Rush NAACL, 2021
Asymmetric Susceptibility Tensor Imaging Steven Cao, Hongjiang Wei, Jingjia Chen, Chunlei Liu Magnetic Resonance in Medicine, 2021
Unsupervised Parsing via Constituency Tests Steven Cao, Nikita Kitaev, Dan Klein EMNLP, 2020
CoVer: Collaborative Light-Node-Only Verification and Data Availability for Blockchains Steven Cao, Swanand Kadhe, Kannan Ramchandran IEEE Blockchain, 2020
Multilingual Alignment of Contextual Word Representations Steven Cao, Nikita Kitaev, Dan Klein ICLR, 2020
Multilingual Constituency Parsing with Self-Attention and Pre-Training Nikita Kitaev, Steven Cao, Dan Klein ACL, 2019
Learning-based Single-step Quantitative Susceptibility Mapping Reconstruction Without Brain Extraction Hongjiang Wei, Steven Cao, Yuyao Zhang, Xiaojun Guan, Fuhua Yan, Kristen Yeom, Chunlei Liu Neuroimage, 2019
Imaging Diamagnetic Susceptibility of Collagen in Hepatic Fibrosis Using Susceptibility Tensor Imaging Hongjiang Wei, Kyle Decker, Hien Nguyen, Steven Cao, Tsung‐Yuan Tsai, Cynthia Dianne Guy, Mustafa Bashir, Chunlei Liu Magnetic Resonance in Medicine, 2019
Quantitative Susceptibility Mapping of Articular Cartilage in Patients with Osteoarthritis at 3 Tesla Hongjiang Wei, Huimin Lin, Le Qin, Steven Cao, Yuyao Zhang, Naying He, Weibo Chen, Fuhua Yan, Chunlei Liu Journal of Magnetic Resonance Imaging, 2019
EECS 126: Probability and Random Processes (Spring 2020) - Teaching Assistant
EECS 16A: Linear Algebra and Circuits (Spring 2019) - Teaching Assistant