Trevor O.

Key Skills

Software

Other

Top Subject Matter

AI/ML fundamentals and quantitative preparation for computer vision workflows

Computer vision object detection (bounding-box labeling/training pipeline)

Top Data Types

Image

Top Task Types

Object Detection

Bounding Box

Freelancer Overview

UNC Tutoring Center — Computer Science & Math Tutor (AI/ML foundational tutoring). Brings 5+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Other. Education includes Bachelor of Science, University of Northern Colorado (2026). AI-training focus includes data types such as Image and labeling workflows including Object Detection and Bounding Box.

Labeling Experience

AI Vision Object Detection System — Python, Machine Learning project

OtherImageBounding Box

Engineered a real-time object detection system using YOLOv8 by iteratively training models with large annotated datasets. Performed data preprocessing and augmentation on annotated data to improve reliability and reduce overfitting for bounding-box-based detection. Applied regression analysis concepts to optimize bounding box predictions and tracking accuracy for dynamic inputs. • Trained YOLOv8 object detector with iterative parameter optimization to exceed 90% precision. • Applied augmentation techniques to improve model robustness and generalization. • Optimized bounding box predictions using regression-related concepts. • Improved tracking accuracy for dynamic inputs via model evaluation and refinement.

2024 - 2026

UNC Tutoring Center — Computer Science & Math Tutor (AI/ML foundational tutoring)

OtherImageObject Detection

Taught computer science and math students by breaking down machine-learning concepts and practical workflows related to vision and data preprocessing, which supports downstream annotation and model training practices. Reviewed learners’ understanding of algorithms, data structures, and quantitative foundations used for training object detection systems. Provided personalized guidance to help students improve performance on technical exam content that maps to ML model development fundamentals. • Instructed students on calculus, physics, algorithms, and data structures to strengthen technical competency for AI workflows. • Diagnosed individual learning gaps and created personalized study plans. • Translated complex technical and mathematical theories into actionable understanding. • Reinforced concepts through measurable exam score improvements and academic performance.

2025 - 2025

Education

Work History