Biography

I am a master student at the School of Computer Science of McGill University, supervised by Prof. Yue Li. I received my bachelor degree in electronic information engineering at Wuhan University, China. I am generally interested in solving healthcare-related problems, especially those associated with sound and natural languages, with machine learning methods. Currently my research topic is to apply topic models and deep learning methods on Electronic Health Records.

Before joining McGill, I was a R&D intern at the algorithm research & development department of Horizon Robotics, a leading Chinese startup with focus on embedded AI. I mainly worked on developing systems for large-scale audio data quality evaluation and selection basing on audio and textual features. Prior to that, I was a research intern at University of Toronto, working on quantitative analysis of fMRI data for clinical applications, supervised by Dr. Andrea Kassner of University of Toronto and The Hospital for Sick Children.

I also worked on signal processing tasks in a project sponsored by the Chinese Ministry of Education when I was an undergrad. In this project we developed a monitoring and analysis system for elevator’s movement using accelerometer and gyroscope attached to it. As the first author I contributed to a paper based on this project, published at ICSP 2018 (IEEE International Conference on Signal Processing) oral presentation section.

In addition, I participated in Neurips 2019 Reproducibility Challenge and investigated the performance gap betweeen deep-learning models and classical models in NLP tasks, among other projects.