I design and develop advanced convolutional neural network (CNN) models to tackle detection, segmentation, and classification of lung nodules, contributing directly to improving early diagnosis and treatment planning for lung cancer. Our work combines deep learning research with practical engineering to deliver accurate, reliable models for clinical applications.

To ensure these models are usable by multiple engineers and easy to maintain, I configure and containerize our deep learning server environments. This setup allows the team to run, test, and deploy models consistently across different development and production systems, speeding up collaboration and reducing setup errors.

I also take the lead in organizing and constructing complex medical imaging datasets used for training and testing our models. This involves curating diverse, high-quality data, ensuring proper labeling and preprocessing, and structuring the data pipelines so that our models are robust, generalizable, and ready for real-world scenarios.

In Software Development, I focused on designing, developing, and maintaining advanced automatic and manual route planning algorithms for in-airway and transthoracic navigation to support precise, minimally invasive procedures. I restructured core library modules to clearly separate public, private, build, and install interfaces, which makes the codebase cleaner and easier to maintain. I also handled exporting thoracic segmentations as DICOM-RT objects, implement geometric post-processing to detect CT image landmarks, and enable background case processing to streamline user workflows. To modernize our build process and development tools, I rewrote our CMake system to be target-based instead of directory-based and upgraded our development environment from Visual Studio 2015 to 2022.

On the Systems Engineering side, I worked on the system integration for key hardware, including the Matrox Orion HD and Clarity UHD capture cards as well as the NDI Vega and Polaris trackers, ensuring smooth performance and compatibility with our platform. I developed specialized engineering tools to test, verify, and integrate new features into our core algorithms, and I created utility programs that help field teams easily extract, troubleshoot, and analyze complex patient cases, as well as manage equipment calibrations and registrations in the field.

In Development Operations, I played a key role in scaling our practices from a small local team of four to a global team of forty by developing standard operating procedures and protocols. I migrated our self-hosted GitLab repositories, issue boards, and documentation to GitLab.com to improve collaboration and maintainability. Additionally, I maintained our software builds for product releases and serve as the administrator and maintainer for our GitLab groups and projects, ensuring that our version control and release processes run smoothly for the entire team.

For EE 350 – Continuous-Time Linear Systems, I hosted two of six weekly recitation sections supporting lectures for 130 students and contributed to exam creation, supervision, and grading.

For EE 455 – Digital Image Processing, I led MATLAB tutorials, held office hours to support students, and handled grading responsibilities for a class of 60 students.