Kevin S.

Key Skills

Software

No software listed

Top Subject Matter

Wildfire Damage Prediction

Medical/Colorectal Polyp Detection

Plant Species Classification

Top Data Types

Image

Text

Document

Top Task Types

Classification

Object Detection

Freelancer Overview

Wildfire Structural Damage Prediction - Data Science Bootcamp Project. Brings 10+ years of professional experience across legal operations, contract review, compliance, and structured analysis. Core strengths include Jupyter. Education includes Master of Science, University of Washington (2024) and Bachelor of Science, Worcester Polytechnic Institute (2017). AI-training focus includes data types such as Image and Tabular and labeling workflows including Classification and Object Detection.

Labeling Experience

Image-Based Colorectal Polyp Detection - Data Science Bootcamp Project

ImageObject Detection

In the Image-Based Colorectal Polyp Detection project, I utilized computer vision models to identify potentially cancerous polyps in colonoscopy images. My contributions included labeling polyp regions for supervised training, model tuning, and assisting in validation by comparing manual and automated detection results. The project enabled me to develop essential labeling and annotation skills in the medical imaging domain. • Performed data annotation on colonoscopy images. • Used object detection frameworks for model training. • Conducted manual review versus model predictions. • Collaborated on team-based data labeling for medical diagnostics.

2025 - 2025

Wildfire Structural Damage Prediction - Data Science Bootcamp Project

ImageClassification

I participated in a Wildfire Structural Damage Prediction project as part of a data science bootcamp, implementing classification of buildings affected by wildfires using structural and geographic features. My tasks included preparing building data, training a classification model, and validating results to predict destroyed versus non-destroyed structures. This experience involved direct data labeling for supervised learning and hands-on teamwork in the data annotation process. • Applied classification techniques for building destruction prediction. • Cleaned and labeled structural and geographic feature data. • Used Jupyter and Scikit-Learn for model training and validation. • Collaborated with a team to support accurate data labeling.

2025 - 2025

Computational Methods for Data Analysis – Leaf Classification Project

Classification

For a Computational Methods for Data Analysis class, I completed a project involving classification of leaf measurement samples as different plant species. I performed data cleaning, manual labeling, and supervised learning to assign ground truth species labels. This reinforced my annotation experience in biological datasets with Python-based tools. • Cleaned and organized tabular plant dataset. • Labeled samples for ground truth species identity. • Trained classification models in Jupyter notebooks. • Evaluated model accuracy against human-provided labels.

2024 - 2024

Education

Work History