cv

Research Assistant

The Ohio State University - College of Food, Agriculture, and Environmental Sciences

Developed software and conducted research for remote sensing agricultural researchers.

Bachelor of Science

The Ohio State University

Electrical and Computer Engineering

Cyberinfrastructure for Machine Learning Applications in Agriculture: Experiences, Analysis, and Vision

Frontiers in Artificial Intelligence

Introduction: Advancements in machine learning (ML) algorithms that make predictions from data without being explicitly programmed and the increased computational speeds of graphics processing units (GPUs) over the last decade have led to remarkable progress in the capabilities of ML. In many fields, including agriculture, this progress has outpaced the availability of sufficiently diverse and high-quality datasets, which now serve as a limiting factor. While many agricultural use cases appear feasible with current compute resources and ML algorithms, the lack of reusable hardware and software components, referred to as cyberinfrastructure (CI), for collecting, transmitting, cleaning, labeling, and training datasets is a major hindrance toward developing solutions to address agricultural use cases. This study focuses on addressing these challenges by exploring the collection, processing, and training of ML models using a multimodal dataset and providing a vision for agriculture-focused CI to accelerate innovation in the field.

FieldVision

A web app that provides the user with agricultural insights using deep learning

• Trained a YOLO deep learning model on over 2000 annotated images to identify crops in drone imagery
• Tuned hyperparameters of deep learning model, resulting in a mAP50 accuracy score of around 90%
• Deployed a web dashboard with PostgreSQL and AI integration, user log-in, and image upload interface
• Integrated the model into a web application built using Python and Flask

Chatbot

A ChatGPT clone

• Built a web application using Django and JavaScript
• Deployed to Heroku, using AWS S3 for data storage
• Devised and implemented a CI/CD pipeline using GitHub Actions
• Used prompt engineering to integrate an LLM from Hugging Face into an interactive application

Structured Light Camera

Device used to capture the 3D shape of an object by projecting light patterns and recording with a camera

• Built a stereo vision system on Jetson Nano, creating accurate point clouds to aid in 3D reconstruction
• Collaborated in an Agile team to implement advanced triangulation algorithms with Python and OpenCV
• Developed a web interface with 3D point cloud display using Flask and Three.js