I am a Ph.D. student in the Department of Computer Science at Princeton University, where I work with Prof. Jia Deng in the Princeton Vision & Learning Lab. I am interested in computer vision and artificial intelligence in general. My current research focuses on how machine learning techniques can be applied to solve theorem proving — a long-standing research area that was dominated by formal methods. Prior to that, I worked on human pose estimation, action detection, and visual relationship understanding.
I received my master’s degree from the University of Michigan and my bachelor’s degree from Tsinghua University.
[杨凯峪] [Email: firstname.lastname@example.org] [CV]
7/2017 Our model scored second (localization) and third (classification) in the Charades Activity Challenge at CVPR 2017.
4/2016 We released the code for stacked hourglass networks – a state-of-the-art model for human pose estimation.
- Kaiyu Yang and Jia Deng. “Learning to Prove Theorems via Interacting with Proof Assistants.” In review.
- Kaiyu Yang, Olga Russakovsky, and Jia Deng. “SpatialSense: An Adversarially Crowdsourced Benchmark for Spatial Relation Recognition.” In review.
- Alejandro Newell, Kaiyu Yang, and Jia Deng. “Stacked Hourglass Networks for Human Pose Estimation.” European Conference on Computer Vision (ECCV). 2016.
- During my undergraduate years, I served as a TA for Data Structures and Algorithms at Tsinghua University, which was offered to both students on-campus and the general public as a massive open online course (MOOC). I received the Outstanding Teaching Assistant Award twice (in 2015 and 2016). Besides regular TA responsibilities such as grading and office hours, I also deal with the online infrastructure for MOOC.