CV
Curriculum vitae.
Contact Information
| Name | Yanjie Chen |
| Professional Title | Research Staff Associate |
| yc4594@columbia.edu | |
| Location | Columbia University, 1190 Amsterdam Avenue, New York, NY 10027 |
Professional Summary
I am a Research Staff Associate in the Dinh Lab at Columbia’s Irving Institute for Cancer Dynamics. My work applies statistics and machine learning to cancer genomics, with a particular focus on clustering algorithms for bulk DNA sequencing data.
Experience
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2026 - present New York, US
Research Staff Associate
Irving Institute for Cancer Dynamics, Columbia University
Advisor: Khanh N. Dinh.
- Continued DECODE development
- Large-scale validation on HPC; DECODE-copy_number_variant & DECODE2
- Other projects on cancer genomics
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2025 - present New York, US
Research Assistant
Memorial Sloan Kettering Cancer Center
Advisor: Li-Xuan Qin.
- Stabilized SyNG-BTS for tumor RNA/miRNA-seq augmentation
- Large-scale validation and supplementary analysis
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2025 - 2025 New York, US
Research Intern
Irving Institute for Cancer Dynamics, Columbia University
Advisor: Khanh N. Dinh.
- Developed DECODE to cluster mutations from bulk DNA-seq using population-genetics models
- Built the analysis pipeline for tumor clonality and subclonal inference
Education
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2024 - 2025 New York, US
Master
Columbia University
Statistics
- GPA: 3.8/4.0
- Coursework: Advanced Machine Learning, Deep Learning, Probability Theory, Computational Statistics
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2022 - 2024 Liverpool, UK
Undergraduate
University of Liverpool
Mathematics
- First Class Honours
- GPA: 3.9/4.0
- Coursework: Stochastic Modelling, Statistics and Probability
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2020 - 2022 Suzhou, China
Undergraduate
Xi'an Jiaotong-Liverpool University
Mathematics
- GPA: 3.7/4.0
- Coursework: Dynamic Modeling, Linear Algebra, Analysis
Awards
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2021 Undergraduate Academic Excellence Performance Scholarship
Xi'an Jiaotong-Liverpool University
Skills
Programming: R, Python (PyTorch), Bash/Linux, LaTeX, MATLAB
ML/Stats: Bayesian Inference, Random Forests, Time Series Analysis, NLP, Transformers
Languages
Mandarin : Native
English : Fluent
Interests
Computational Genomics: Bayesian Inference, Causal Inference, Modern ML Solutions
Projects
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2026 Joint Statistical Meetings (JSM) 2026
Speaker in a topic-contributed paper session, at the invitation of Prof. Marek Kimmel.
- Talk: “Reliable Inference of Tumor Expansion Rate and Clonality from DNA-Sequencing Data.”
- Session: “Stochastic Processes Describing Cancer-Related Biological Systems: Modeling and Inference,” Boston, US.
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2025 DitecT Lab, Columbia Engineering
Data Researcher. Advisor: Xuan Sharon Di.
- Compiling NYC TLC yellow/green taxi trips with holiday and weather data to evaluate CBD congestion pricing
- Building a lean cleaning/feature pipeline and performing time-series and causal analyses (DiD, event-study, survival) to quantify demand shifts; exploring substitution and behavioral mechanisms