Education
University of California, Los Angeles (UCLA)
Master of Science in Biostatistics π
September 2023 β Present
- GPA: 4.00/4.00 | Transcript
- Advisor: Dr. Matteo Pellegrini
- Honors:
- Fielding School of Public Health Deanβs Leadership Grant (2023β2025)
- Warren Alpert Computational Biology and AI Network Fellow (2024β2025)
- Steve Wallace Policy Fellowship (2024)
- APEx Funding, UCLA Human Genetics (2024)
- Fielding School of Public Health Deanβs Leadership Grant (2023β2025)
Southwest University
Bachelor of Science in Biology π§¬
September 2018 β June 2022
- GPA: 3.84/4.00 (Rank: 2/65) | Transcript
- Outstanding Graduate
- Thesis: Analytic Hierarchy Process for Invasive Plant Management
- Honors:
- International Research Award (2021)
- Academic Excellence Scholarships (Second- and Third-Class, 2019, 2020, 2021)
- Outstanding Intern (2022)
- International Research Award (2021)
Skills
- Computational & Statistical
- Languages & Tools: R (tidyverse, ggplot2, glmnet, RShiny), Python (NumPy, Pandas, Biopython, Scikit-learn, Pybedtools, Matplotlib), MATLAB, SAS, STATA, SQL, HTML/CSS/JavaScript, LaTeX
- Platforms: Linux scripting, Git/GitHub, Hoffman2 cluster, Docker, Cloud Platforms (GCP, AWS, Azure, OCI)
- Data Analysis & Modeling: Machine learning, Bayesian inference, deep learning (Keras, TensorFlow, PyTorch), simulation, linear models, optimization, graph theory
- High-Performance Computing (HPC): Workflow orchestration, parallelized analysis, cluster-based computations
- Languages & Tools: R (tidyverse, ggplot2, glmnet, RShiny), Python (NumPy, Pandas, Biopython, Scikit-learn, Pybedtools, Matplotlib), MATLAB, SAS, STATA, SQL, HTML/CSS/JavaScript, LaTeX
- Bioinformatics
- Data Analysis: GWAS, EWAS, eQTL analysis, gene enrichment analysis, polygenic risk scores, Mendelian randomization, Gene Ontology analysis, multi-omics integration, genome annotation, single-cell data analysis (scRNA-seq, scDNA-seq)
- Tools: BLAST, InterProScan, PSIPRED, AlphaFold, ChimeraX, UCSC Genome Browser, Ensembl, Galaxy, Bioconductor, BEDTools, STAR, DESeq2, Seurat, edgeR, Enrichr
- Data Analysis: GWAS, EWAS, eQTL analysis, gene enrichment analysis, polygenic risk scores, Mendelian randomization, Gene Ontology analysis, multi-omics integration, genome annotation, single-cell data analysis (scRNA-seq, scDNA-seq)
- Mathematical
- Core Mathematics: Linear Algebra, Real Analysis, Probability and Statistics, Stochastic Process, Calculus, Partial Differential Equations, Discrete Mathematics, Infinite Theory
- Laboratory
- Molecular Biology: PCR, qPCR, DNA/RNA extraction, CRISPR/Cas9, cloning, electrophoresis, next-generation sequencing (NGS) library preparation
- Genomics: RNA-seq, ChIP-seq, single-cell RNA-seq, bisulfite sequencing
- Proteomics: Western blot, ELISA, mass spectrometry, chromatin immunoprecipitation (ChIP)
- Cell Biology: Cell culture, transfection, confocal and fluorescence microscopy, immunofluorescence, flow cytometry
- Molecular Biology: PCR, qPCR, DNA/RNA extraction, CRISPR/Cas9, cloning, electrophoresis, next-generation sequencing (NGS) library preparation
Coursework
| Course | Description | Instructor |
|---|---|---|
| STAT M254 | Statistical Methods in Computational Biology | Dr. Jingyi Jessica Li |
| BIOMATH 210 | Optimization Methods in Biology | Dr. Kenneth L Lange |
| BIOMATH M281 | Survival Analysis | Dr. Gang Li |
| BIOSTAT 202A | Mathematical Statistics | Dr. Damla Senturk |
| BIOSTAT 200A, 200B, 200C | Methods in Biostatistics | Dr. A. Klomhaus, Dr. C. M. Crespi, Dr. Jin Zhou |
| STAT 100C | Linear Models | Dr. Nicolas Christou |
| BIOSTAT 213 | Statistical Simulation | Dr. Christina Ramirez |
| MATH 115A, 33A | Linear Algebra | Dr. Pablo S. Ocal |
| MATH 131A | Real Analysis | Dr. Konstantinos Varvarezos |
| MATH 170E, 170S | Probability Theory and Statistics | Dr. Zhaoyu Zhang, Dr. Jona Lelmi |
| BIOSTAT 203A, 203B | Data Management, Statistical Computing Data Science by R |
Dr. Grace Kim, Dr. Hua Zhou |
| BIOSTAT 216 | Mathematical Methods for Biostatistics | Dr. Hua Zhou |
| BIOSTAT 231 | Statistical Power and Sample Size Methods | Dr. C. M. Crespi |
| BIOSTAT M236 | Longitudinal Data | Dr. Robert Weiss |
| Infinite Theory, Calculus, and Partial Differential Equations | ||
| Discrete Mathematics | ||
| Python and Computational Thinking | ||
| DS BMED 208 | Recent Research in Machine Learning in Medicine | Dr. Jason Ernst |
| Bioinformatics | ||
| Biochemistry, Organic Chemistry, General Chemistry | ||
| Genetics, Human Genetics, Genetic Engineering | ||
| Molecular Biology, Cell Biology, Developmental Biology | ||
| Anatomy and Physiology, Neurology | ||
| Immunology, Microbiology | ||
| Ecology, Zoology, Botany, Evolutionary Biology | ||
| PUB HLT 200A, B | Epidemiology, Public Health Policy, Community & Environmental Health Sciences |