CV
You can access the PDF version here. (Last update: 2023.2)
Education
- B.S. in Statistics, University of Science and Technology of China, 2016.9-2020.6
- Ph.D in Data Science, City University of Hong Kong, 2020.9-2024.6 (expected)
Research experience
- Fall 2018: Research Assistant
- Department of Statistics & Finance, University of Science and Technology of China
- A Bayesian Method for Systemic Risk Assessment in Financial Networks:
- Collected data from different banks’ yearbooks to build a complete Chinese banks liability database.
- Applied a Bayesian methodology and constructed a Gibbs sampler to generate samples for individual liabilities in Chinese interbank networks.
- Derived default probabilities of individual banks and compared the performance with other reconstruction models.
- Research Output: One article published in Physica A: Statistical Mechanics and its Applications: Solvency contagion risk in the Chinese commercial banks’ network
- Supervisor: Prof. Yu Chen
- Summer 2019: Research Assistant
- Department of Mathematics, Arizona State University
- A Competitive Model for Drug-Resistant Evolution of E. coli cells:
- Developed a biological reasonable ODE model to mathematically demonstrate the drug-resistant evolution of E. coli.
- Validated our model using real biological experimental data and the numerical simulation fit the data perfectly.
- Used this model to further inspire new explanation of biological mechanisms about drug- resistant evolution.
- Mathematical System of Nutrient Allocation Strategy in E. coli cells
- Built and modified an equation system to depict the dynamic behavior of GFP/OD and greatly fitted the experiments.
- Used MATLAB to search for the optimized parameters and adjusted parameters in various conditions.
- Generalized the system into other complicated situations and the proved to be satisfactory and robust.
- Research Output: One paper published in SIAM Undergraduate Research Online: Clinical data validated mathematical model for intermittent abiraterone response in castration-resistant prostate cancer patients
- Supervisor: Prof. Yang Kuang
- Fall 2019: Research Assistant
- School of CIDSE, Arizona State University
- Multimodal Machine Learning for Alzheimer Disease Diagnosis:
- Using neuroimaging data from ADNI database to explore multimodal learning in Alzheimer disease diagnosis.
- Develop EM algorithm to deal with missing modalities problem in multimodal learning of Alzheimer disease diagnosis
- Construct convolutional neural networks using magnetic resonance imaging to classify patients with Alzheimer disease and normal control people.
- Supervisor: Prof. Jing Li
Programming Languages
C, MATLAB, R, Python