Matthew Martin | Portfolio
Computer scientist & biologist. Portfolio showcasing projects, research, and skills.
Matthew Martin
Computer Scientist & Biologist
My foundation in Biology from James Madison University gives me the domain expertise to understand complex life science challenges, while my Computer Science degree from the University of Colorado Boulder provides the technical skills to build robust, data-driven solutions. I build projects at the intersection of software, machine learning, and health sciences.
As a Software Engineer Intern at AstraZeneca, I designed and developed a C#/.NET application to automate the ingestion and normalization of experimental data into SQL Server, directly supporting downstream machine learning workflows. I am passionate about leveraging AI to create scalable and maintainable tools that advance healthcare.
Career Goals
I aim to pursue a career building AI and data-driven tools that improve healthcare outcomes. My long-term goal is to develop innovative software and machine learning solutions for biotech, health tech, or pharmaceutical organizations, while continuing to grow as a researcher and engineer.
| View Projects | Download Resume |
Education
B.S. Computer Science — University of Colorado Boulder, GPA 4.0, Dec 2025
Awards: Dean’s List Student, CSPB Orientation Leader
B.S. Biology — James Madison University, Jul 2021
Awards: Dean’s List Student
Contact
📧 matthewmartin117@gmail.com
LinkedIn | GitHub
Skills
Languages
Python, C#, Java, SQL, C++
ML & Data Science
TensorFlow, PyTorch, Keras, Pandas, NumPy, Scikit-learn
Web & Full-Stack
Flask, React, Spring Boot, JavaScript
Tools & Cloud
Git, Docker, AWS, Maven, Postman, SFML
Data & Research
Clinical & lab workflows, data preprocessing, ETL pipelines, exploratory data analysis
Projects
★ Featured Project (In Progress - Fall 2025) ★
Java Spring Boot API + ML Classifier for HIPAA Protected Health Data
Developing a secure, full-stack application to classify protected health information (PHI). The project involves building a robust Java Spring Boot API to handle sensitive data securely and integrating a machine learning model for real-time classification.
🔗 View Progress & Documentation ➝
Pneumonia Detection — Deep Learning
Developed a model to classify pneumonia from chest X-rays, overcoming a highly imbalanced dataset. The high recall is critical for minimizing false negatives in a medical context.
Impact: Achieved 86% accuracy and a **recall of 0.92** using a CNN with a VGG16 base and class weighting.
Tech: TensorFlow, Keras, Python
GitHub
Heart Disease Prediction — Supervised Learning
Analyzed a large-scale CDC survey dataset of over 400K responses to predict heart disease risk. Trained and evaluated multiple models to identify key health indicators.
Impact: Gradient Boosting models achieved ~90% recall, vital for identifying at-risk individuals.
Tech: Scikit-learn, Pandas, NumPy
GitHub
Breast Cancer Gene Expression Clustering
Used unsupervised learning to uncover distinct patient subtypes from complex, high-dimensional gene data (54K+ features), demonstrating patterns not visible through simple analysis.
Impact: Applied **PCA for dimensionality reduction** and **K-Means clustering** to identify meaningful biological subgroups.
Tech: Scikit-learn, PCA, K-Means
GitHub
C++ Real-Time Telemetry Data Processing
Engineered a high-performance C++ application to process and visualize high-frequency telemetry data streams in real-time without data loss.
Impact: Successfully parsed complex data packets and rendered dynamic, live-updating charts using the **SFML graphics library**.
Tech: C++, SFML
GitHub
Epidemic Modeling Web Application
Built a full-stack web application that simulates infectious disease spread using the SIRD model. Users can adjust parameters and visualize outcomes via interactive dashboards.
Impact: Provides an accessible tool for understanding epidemiological concepts and the effects of variables like transmission rate.
Tech: Python, Flask, JavaScript
GitHub
HiFive Social Media Web App
Engineered a full-stack social media application from the ground up, allowing users to connect based on shared interests through posts, comments, and a recommendation system.
Impact: A complete MERN-like stack application featuring user authentication, a RESTful API, and a dynamic front-end.
Tech: Python, Flask, React, PostgreSQL
GitHubExperience
Software Engineering Intern | AstraZeneca — May 2025–Aug 2025
- Developed a C#/.NET Windows Forms application to automate ingestion of Excel-based experimental datasets into SQL Server, enabling downstream ML workflows.
- Implemented data parsing, validation, and schema normalization, ensuring large-scale experimental data was clean, structured, and ML-ready.
- Collaborated with data engineers and research scientists in Agile sprints, delivering reproducible ML pipelines with demos and documentation.
- Tech & Tools: C#, .NET, SQL Server, Excel automation, Python (for ML integration), Spotfire, ETL pipelines, Data Modeling, Agile
Sampling Coordinator | United States Pharmacopeia — Mar 2022–Jan 2023
- Managed pharmaceutical data collection and logging using Oracle systems, ensuring data integrity for regulatory submissions.
- Coordinated global logistics of regulated materials, ensuring precision and compliance with data-driven processes.
Research Associate | Curative Health — Aug 2021–Dec 2021
- Processed and analyzed large-scale COVID-19 PCR datasets, including qPCR and CN value tracking.
- Developed methods to ensure data quality at scale, enabling accurate variant monitoring and public health reporting.