• Run descriptive statistics on survey data and summarized the data using numbers, words, and images.• Created a Python script to increase speed of data entry. • Created electronic data collection instruments using REDCap (Research Electronic Data Capture) software to track different study phases and collect research data.

• Automated data entry for a research study using machine learning models. • Trained a YOLO v8 model for object detection and a separate CNN for image classification. • Evaluated model performance using key metrics (image classification accuracy: 99.61%, object detection accuracy: 95%) and optimized models based on feedback.• Presented at a symposium to disseminate the results of the project.

• Created a device adapter to integrate the MCL Magnetic Tweezer into Micro-Manager software.• Created Micro-Manager Java plugins to enable motion control for the Magnetic Tweezer and Nano-Drive devices.• Merged device plugins to create a new comprehensive “Control Panel” to facilitate multiple MCL device control.• Created Python wrappers for previously existing device control APIs.