Tu N (Alex) Tran
Houston, TX
Graduate student in Engineering Data Science building intelligent tools for biological and multimodual data analysis.
Loki – AI-Powered Nuclei Segmentation Platform
- Engineered frontend UI for AI inference on H&E images.
- Enabled one-click model execution without requiring Python.
- Built interactive region selection directly on tissue images.
- Developed AI chatbox for real-time biological insights, identifying cell types and tissue structures.
- Significantly improved accessibility for non-technical users in research settings.
Summary
I am a Graduate student in Engineering Data Science with experience applying statistical modeling, machine learning, and data visualization to biological and engineering problems.
I am highly skilled in Python, R, SQL (in progress), and cloud-based workflows. My core expertise lies in building end-to-end pipelines, cleaning and structuring large datasets, and developing precise interactive dashboards.
Currently, I am seeking a Data Science internship to leverage my analytical skills and programming expertise for data-driven decision making.
Education
Master of Science in Engineering Data Science
University of Houston, Cullen College of Engineering
- GPA: 3.42
- Houston, TX
Bachelor of Science in Mathematics
University of Massachusetts Lowell
- Minor: Finance
- Dean’s List 2020–2021
- GPA: 3.135
- Lowell, MA
Relevant Projects
Mjolnir
Designed and deployed a visualization website using Python (Dash, Plotly) for interactive exploration of multimodal datasets. Integrated gigapixel histology images with gene expression and pathway enrichment results. Co-authored a Research Square preprint.
Visual–Omics Curation
Curated a multimodal dataset linking histology images with spatial gene expression across 32 organs. Built diagnostics to evaluate machine learning models, heavily contributing to a Nature Methods publication on foundation models.
Macrophage Analysis
Applied Leiden clustering and UMAP to single-cell data for cell-type identification. Conducted marker gene analysis to assess treatments. Automated preprocessing pipelines in Python.
COVID-19 Analysis
Analyzed RNA-seq data with TopHat, Cuffdiff, and Python. Conducted differential expression analysis and visualized results with heatmaps and volcano plots. Built a custom Gene Ontology tool.
Work Experience
Research Assistant – Cardiovascular Regeneration Program
Houston Methodist, Dr. Guangyu Wang Lab
- Built reproducible pipelines for large-scale single-cell and spatial data analysis using Python, R, and Snakemake.
- Applied clustering, trajectory inference, and statistical testing to generate insights from complex datasets.
- Created interactive dashboards (Dash/Plotly) to enable exploratory analysis by cross-functional teams.
- Delivered analyses supporting a Nature Methods publication and maintained the lab’s public-facing research website.
Marketing & Data Intern
Viet Power Solutions JSC (Vietnam)
- Monitored digital engagement metrics with Google Analytics and optimized campaigns for +39.5% performance improvement.
- Designed and launched targeted LinkedIn, Facebook, and Google Ads campaigns, raising user engagement by 50%.
- Produced clear, data-driven reports to inform leadership and refine product strategy.
Publications
Chen W., Zhang P., Tran T. N., et al. (2025). Nature Methods. doi:10.1038/s41592-025-02707-1
Zhang P., Chen W., Tran T. N., et al. (2025). Nature Communications, 16, 7178. doi:10.1038/s41467-025-62593-1
Skills
Programming
- Python (Pandas, NumPy, SciPy, scikit-learn, Plotly, Dash)
- R (tidyverse, Seurat)
- HTML/CSS
Data Science
- Data Wrangling
- Statistical Modeling & Hypothesis Testing
- Clustering & Dimensionality Reduction
- Pathway Enrichment
Machine Learning
- scikit-learn
- Trajectory Inference
- Model Diagnostics
- Evaluation Metrics
Data Engineering
- Snakemake & Git
- Linux & AWS (EC2/S3)
- Data Preprocessing & Automation
Visualization
- Dash/Plotly
- Matplotlib, Seaborn
- Interactive Dashboards
In Progress
- SQL
- A/B Testing
- Tableau / Looker