About Me
Hello! I'm Michael Ellis, an Applied Scientist working at the intersection of mathematics, statistics, and software engineering. I'm passionate about solving complex problems through data-driven solutions and building impactful products. My mission is to make a scientific process of exploration and experimentation more accessible, fostering collaboration and innovation in technology development.
Areas of Expertise
AI & Machine Learning
Building intelligent systems that make automated processes while maintaining high ethical standards and reliability.
Statistical Methods
Applying robust statistical approaches to quantify uncertainty and improve decision-making processes.
Software Engineering
Developing scalable, maintainable systems that transform theoretical concepts into practical solutions.
Professional Journey
Senior Data Scientist & Data Scientist
Technical lead, collaborating with cross-functional teams to leverage generative AI, large language models (LLMs), and NLP to build task-oriented dialogue systems with both text-based and voice interfaces capable of autonomous customer support.
Data Scientist
Collaborated with a team to developed a large-scale probabilistic forecasting system for natural gas consumption.
Academic Background
PhD Coursework in Mathematics
- Research focused on scalable Bayesian methodologies for high dimensional datasets.
- Course work including: Measure-Theory Probability, Mathematical Statistics, Experimental Design, Computational Statistics, Real Analysis, Differential Equations.
Master's in Statistics
- Research focused on scalable Bayesian methodologies and Sequential Monte Carlo methods for time-series data.
- Master's Thesis: Sequential Monte Carlo Methods for Hidden Markov Models