About Me
I am a postdoctoral scholar from Department of Statistics, Stanford University, advised by Prof. Wing Hung Wong (NAS member). Prior to that, I was a PhD student from Department of Automation, Tsinghua University, where I spent two years in Stanford University, jointly advised by Prof. Wing Hung Wong. My research area mainly covers statistical learning and machine learning algorithms. My current interests aim at solving several problems in statistics, such as density estimation and Bayesian inference with deep generative models. I'm also interested in applying machine learning algorithms to various problems in biomedical informatics and computational biology, which involves pharmacology data, biomedical data and next-generation sequencing (NGS) data analysis.
Recent News
- 2022.08 - I will give a invited talk at Washington, DC for Joint Statistical Meetings 2022.
- 2021.12 - We won the first place in NeurIPS 2021 Multimodal Single-Cell Data Integration competition two Joint Embedding tasks.
- 2021.09 - Our study on neural network boosting was accepted to NeurIPS 2021.
- 2021.03 - Our study on neural density estimation was accepted to PNAS.
- 2021.02 - Our study on single cell analysis with deep generative models was accepted to Nature Machine Intelligence.
More
- 2020.09 - Our study on molecule optimization with reinforcement learning was accepted to NeurIPS 2020.
- 2020.06 - Our study on drug sensitivity prediction with graph neural network was accepted to ECCB 2020.
- 2020.06 - Our study on gene mutation prediction using histopathological images was accepted to MICCAI 2020.
- 2019.09 - I will visit the Department of Statistics, Stanford University as a joint Ph.D. student advised by Wing Hung Wong.
- 2019.07 - I will give a invited talk at Basel, Switzerland for ISMB 2019.
- 2019.05 - I win the travel fellowship provided by International Society of Computational Biology (ISCB).
Employment
June. 2021 - Present
Department of Statistics, Stanford University, CA, USA
Postdoctoral Scholar
Education
Sep. 2019 - June. 2021
Department of Statistics, Stanford University, CA, USA
Joint Ph.D. student
Aug. 2016 - June. 2021
Department of Automation, Tsinghua University, Beijing, China
Doctor of Philosophy
Aug. 2015 - Jan. 2016
Department of Computer Science, Lund University, Sweden
Exchange Student
Aug. 2012 - Jul. 2016
ShenYuan Honors College, Beihang University, Beijing, China
Bachelor of Engineering
Internships
Jul. 2019 - Sep. 2019
AI+Healthcare, SenseTime Inc
Research Intern
Selected Publications
 | Desity Estimation with Deep Generative Neural Networks |
 | Simultaneous Deep Generative Modeling and Clustering of Single-cell Genomic Data |
 | Boost Neural Networks by Checkpoints |
 | Reinforced Molecular Optimization with Neighborhood-Controlled Grammars |
 | Feature-Enhanced Graph Networks for Genetic Mutational Prediction Using Histopathological Images in Colon Cancer |
 | Incorporating Gene Expression in Genome-wide Prediction of Chromatin Accessibility via Deep Learning |
 | Cancer Drug Response Prediction via a Hybrid Graph Convolutional Network |
 | hicGAN Infers Super Resolution Hi-C Data with Generative Adversarial Networks |
 | Quantifying Functional Impact of Non-coding Variants With Multi-task Bayesian Neural Network |
 | Chromatin Accessibility Prediction via a Hybrid Deep Convolutional Neural Network |