Michael Sorenson

Coaching volleyball team of 12-14 college women, providing instruction, giving technical feedback, setting lineups, organizing and leading tournaments.

Teaching AP Computer Science Principles and Geometry (5 sections) to high school students.

Created data visualizations of more than 20 variables, measured across ~1,500 samples from 90 stations over six years, capturing temporal, regional, and ecological changes. Generated a co-occurrence network from the same dataset using a supercomputer at SDSC, with ~4,800 nodes and ~54,000 edges, identifying new interactions and validating known relationships between microbial groups and environmen

Developed predictive machine learning models in Python (logistic regression, decision tree, gradient-boosted LightGBM classifier, neural networks) using ~10 days of high-frequency 500 Hz time-series data to understand sleep patterns in eight northern elephant seals. Led end-to-end development and documentation, encompassing ETL, feature extraction, model training, testing, prediction, results anal

Researched and developed integrations in JavaScript between xMatters and over 30 DevOps software tools, including GCP, AWS, Microsoft Azure, Zoom, and WebEx. Created automation tool to systematically generate JavaScript code for redundant parts of new integrations, saving xMatters software engineers 100s of hours of development time.

Completed a Master of Science in Data Science, gaining advanced knowledge in data analysis, machine learning, and predictive modeling. Focused on developing and applying sophisticated data science techniques to real-world problems.

Earned a Bachelor of Science in Data Science, building a strong foundation in statistical and general-purpose programming languages. Developed expertise in data cleaning, exploration, and visualization.