Hi, I’m Alex — an applied mathematician, machine learning scientist, and educator.
I hold a Ph.D. in Applied Mathematics and Statistics from the Colorado School of Mines. My background spans mathematical research, scientific computing, data science and machine learning, university teaching, and scientific consulting.
I am particularly interested in mathematical modeling, statistical learning, inverse problems, optimization, and scientific machine learning. I am open to full-time research, data science, machine learning, and quantitative roles, as well as teaching and selected scientific collaborations.
Current Work
I currently work with Denver Life Sciences on statistical and mathematical modeling of physiological data related to tissue hydration. My work focuses on developing models that separate stable differences among experiments from physiological changes occurring within experiments over time, with the broader goal of improving both prediction and scientific interpretation.
This work combines statistical estimation, regularization, model validation, and close collaboration with domain experts, and reflects my broader interest in using mathematical and statistical methods to solve problems in the physical and life sciences.
Research
My doctoral research focused on computational methods for large-scale problems in physics, with work spanning optimal transport, optimal control, inverse problems, generative modeling, and scientific computing. I have also worked with hyperspectral remote-sensing data for geologic inference and scientific imaging.
Data Science & Machine Learning
I have several years of industry experience as a senior data scientist and machine learning researcher at On The Barrelhead, NerdWallet, and Launch Potato. My work has included statistical modeling, experimentation, recommendation and ranking systems, optimization, calibration, and machine learning research.
I am particularly interested in data science and ML roles where mathematical and statistical reasoning are central to the work. I am especially drawn to problems in health technology, remote sensing, and scientific data, where my background in inverse problems, statistical inference, and optimization can complement modern machine learning approaches.
Teaching
I enjoy teaching mathematics, statistics, and data science and am available for adjunct, lecturer, and other teaching opportunities. Courses I am especially interested in teaching include:
- Calculus and multivariable calculus
- Linear algebra and differential equations
- Probability and statistics
- Numerical analysis and scientific computing
- Optimization and operations research
- Mathematical modeling
- Data science and machine learning
Get in Touch
I’m always happy to hear about interesting quantitative problems, research collaborations, teaching opportunities, or full-time roles. Please feel free to reach out using the contact information in the sidebar.