Dr. Randal S. Olson
Ph.D. in Computer Science
Michigan State University - East Lansing, MI - 2011 to 2015
Graduated with dual major in Ecology, Evolutionary Biology, and Behavior
Doctoral Advisor: Prof. Christoph Adami
B.S. in Computer Science
University of Central Florida - Orlando, FL - 2005 to 2010
Graduated with Honors In Major
Undergraduate Advisor: Prof. Kenneth Stanley
Consultant, Trainer, and Mentor
Randal S. Olson - Vancouver, WA - 2013 to Present
Strategic advising and hands-on solutions to maximize value from data science and AI. Organizing and teaching workshops to train the next generation of data scientists. Mentoring future leaders in data science.
Founder and Principal Investigator
Private Research Lab - Vancouver, WA - 2022 to Present
Leading a private AI & ML research lab.
Data Science and Machine Learning Advisor
FOXO Technologies - Minneapolis, MN - 2021 to 2022
I sat on the FOXO Scientific Advisory Board and advised on the data science and machine learning technology developments at FOXO.
Senior AI Scientist
Absci - Vancouver, WA - 2021 to 2022
I worked at the intersection of the Absci wet labs and AI group to make sure that our ML engineers are getting the data they need, and to make sure that the models the ML engineers are building are adding value to Absci’s strain engineering and drug discovery technology.
Chief Data Scientist
FOXO Technologies - Minneapolis, MN - 2020 to 2021
I was hired as the Lead Data Scientist and eventually promoted to Chief Data Scientist so I could better serve the company mission. While holding this role, I built a data science and software engineering team from the ground up. The purpose of this team was to merge cutting edge epigenetics research with advanced machine learning technology to improve mortality assessment for the life insurance industry and beyond. Since 2018, my team and I:
- conducted observational research studies with human subjects,
- performed data collection and cleaning on datasets containing over 800,000 molecular measurements and hundreds of human and wellness indicators,
- developed custom DNA methylation processing software from scratch (e.g., https://github.com/FoxoTech/methylprep),
- built a cloud-based serverless automated DNA methylation processing platform,
- curated our data into a proprietary research database on the cloud,
- prototyped MVP machine learning models based on our proprietary research database using a state-of-the-art AutoML platform,
- deployed said MVP models into production with a state-of-the-art MLOps platform, and
- integrated said deployed models into a customer-facing web platform.
Lead Data Scientist
FOXO Technologies - Minneapolis, MN - 2018 to 2020
I was hired as the Lead Data Scientist to establish a data science and engineering team to execute the company mission. While holding this role, I built a data science and software engineering team from the ground up. The purpose of this team was to merge cutting edge epigenetics research with advanced machine learning technology to improve mortality assessment for the life insurance industry and beyond.
Senior Data Scientist
University of Pennsylvania - Philadelphia, PA - 2016 to 2018
After working as a postdoctoral researcher for a year, I transitioned into a staff researcher position in Prof. Jason H. Moore’s lab at Penn’s Institute for Biomedical Informatics. At Penn, I continued developing state-of-the-art machine learning algorithms with a focus on biomedical applications. I also continued aiding Prof. Moore in developing a biomedical visualization laboratory, which will offer machine learning and data analysis as a service to PennMed faculty and physicians. While holding this role, I also assisted the lab in integrating the lab’s research projects into the Python data science ecosystem. This entailed translating research code into performant and well-engineered software. Some of those projects include:
University of Pennsylvania - Philadelphia, PA - 2015 to 2016
I joined Prof. Jason H. Moore’s research lab at Penn’s Institute for Biomedical Informatics. At Penn, I developed state-of-the-art machine learning algorithms with a focus on biomedical applications. I also aided Prof. Moore in laying the groundwork for a biomedical visualization laboratory that will be used as a collaborative research space by the Penn medical school. While holding this role, I pioneered the field of Automated Machine Learning (AutoML) and built TPOT, one of the most-used open source AutoML libraries in the world. TPOT has since grown into a mature open source library on its own: https://github.com/EpistasisLab/tpot
Graduate Research Assistant
Michigan State University - East Lansing, MI - 2011 to 2015
I spent 4 years working on a dual major Ph.D. at Michigan State University working with Prof. Christoph Adami. During my time there, I developed a high-performance C++ platform for digitally studying the evolution of intelligent animal behavior over long, evolutionary timescales. Using this platform, I published several articles in peer-reviewed journals and conference proceedings to share what I learned about the evolution of cooperation and intelligence.
Warner Robins AFB - Warner Robins, GA - 2010 to 2011
I worked as a civilian employee for the Air Force developing tools for the Electronic Warfare division. My time here was primarily spent as a software engineer working on classified software in a larger software development team.
10+ years experience as a data scientist
Data visualization expert
Expert with Python ecosystem: NumPy, SciPy, pandas, matplotlib, Seaborn, Jupyter, BeautifulSoup, NetworkX, and more
8+ years experience as a machine learning engineer
3+ years experience as a deep learning & NLP model engineer
Automated Machine Learning (AutoML) expert
Expert with Python ecosystem: scikit-learn, Keras, PyTorch, HuggingFace, Weights & Biases
4+ years experience as a data science & machine learning engineer manager
4+ years experience as a technical strategic leader in biotechnology startups
Built, grew, and trained effective technical teams from the ground up
Ph.D. thesis and research publications focused on the development of Artificial General Intelligence
12+ years experience with optimization methods, particularly Genetic Algorithms and Evolutionary Computation
12+ years experience with Artificial Neural Networks and Neuroevolution
12+ years experience as a software engineer
Expert with standard SWE practices: modern software design, documentation, version control, unit testing, continuous integration, Agile, Kanban
HPC & MLOps
10+ years experience using HPC systems to run massively parallel compute jobs
4+ years experience using Kubernetes and KubeFlow
4+ years experience implementing and using cloud-first data infrastructure
Biology & biotechnology
PhD-level study and research in evolutionary biology
4+ years experience with DNA methylation microarray data (Illumina)
2+ years experience with NGS data (Illumina & PacBio)
2+ years experience with genetic engineering technologies
I have published over 40 peer-reviewed publications and 17 publications as first author.
My publications have over 3,000 total citations and an h-index of 19.
A complete list of my publications can be found on my Google Scholar page.
Last updated July 2022