During my Summer 2024 internship, I developed and fine-tuned a YOLOv8 object detection and segmentation model aimed at accurately identifying and segmenting wheat fields. I successfully achieved 82% accuracy for object detection and 84% for segmentation, optimizing the model for real-world agricultural applications. Additionally, I worked with multispectral and RGB imaging data to extract key crop features, calculating essential vegetative indices like the Soil Crop Index and Green Normalized Difference Index (GNDI) to assess crop health. By applying machine learning techniques to analyze these features, I contributed to a more accurate prediction of field conditions, supporting data-driven decision-making in agricultural practices.

On the Integration Hub team, I worked on both Confluent-Kafka and Elasticsearch python scripts. Such scripts varied from pushing data or consuming said data and updating the GitHub accordingly. Specifically, for the Confluent-Kafka script, I worked on creating a consumer client to consume the data produced by producer client and print the data in the terminal. As for the Elasticsearch (ELK), I help create a python script that indexed data to Elasticsearch as well as exporting the data to other file types.

During the Spring 2023 semester, I assisted both Mr. Strother and Dr. Zhang in grading, holding weekly labs, and holding office hours. In the weekly lab, I aided students in completing mini programming assignments, similar to those learned in the lectures. As for office hours, I helped student's programming questions on assignments, labs, practice exam questions, etc.

During the weekends, I supervised the facilities of the pilot plant during the co-manufacturing of sugar syrup at the Arkansas Food Innovation Center. At the pilot plant, roughly 200 bottles of sugar syrup were put through the process of being cooked in kettle, bottled, and labelled.

Created a website where the user can search up any foods (like eggs or ground beef) or input custom food property types (the percentage of protein, carbs, water, fat, fiber, and ash in that product). Once all the food properties, description, and temperature are filled in you can find the total density, specific heat, and total thermal conductivity and diffusivity of that product.

I assisted a team of 10 graduate and staff member on swarm 3D printing for autonomous manufacturing. Mostly spent my time testing python code used for controlling the swarm robots and the GUI for moving the swarm 3D printing robots.