AI Strategist & Solutions Architect

Education

Ph.D. in Computer Science (AI focus)

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 (AI focus)

University of Central Florida - Orlando, FL - 2005 to 2010

Graduated with Honors In Major

Undergraduate Advisor: Prof. Kenneth Stanley

Professional Experience

Founder & Principal Consultant, AI and Data Science

RO Consulting LLC - Vancouver, WA - 2022 to Present

Steering RO Consulting, I’ve become an invaluable guide for companies seeking to navigate the complexities of data science and AI. My role involves dissecting complex problems and architecting custom AI solutions that drive growth and innovation. My work on an AI-automated travel package system for GuideToEurope is one of many highlights.

Interested in collaborating? Let’s talk.

Head of AI Strategy

AE Studio - Vancouver, WA (Remote) - 2024 to Present

Turning cutting-edge AI into real-world business wins. I translate complex client challenges into concrete technical architectures - from LLM-powered conversational systems and computer vision pipelines to predictive analytics platforms and automated decision engines. Across edtech, biotech, finance, and enterprise sectors, my approach identifies the critical 20% of business effort that delivers 80% of the value, architecting full-stack solutions directly connected to business KPIs.

As a guide through the rapidly evolving AI landscape, I help clients separate genuine opportunities from hype while building future-ready technology strategies. My solutions leverage deep expertise in data science, cloud deployment, and AI engineering to create systems that go beyond showcasing technical capabilities and drive quantifiable ROI through streamlined operations, joyful customer experiences, and truly data-driven decision making.

Senior AI Scientist

Absci - Vancouver, WA - 2021 to 2022

As a founding member of the AI research team, I helped build ETL systems at the intersection of the wet labs and the AI team, cutting data transfer rates from days to minutes. This data pipeline enabled us to pretrain, fine-tune, and evaluate LLMs for drug discovery. My work on the ETL systems and AI solutions contributed significantly to the filing of one patent and remains a cornerstone of Absci’s innovative drug discovery pipeline.

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. This was a part-time contract role.

Chief Data Scientist

FOXO Technologies - Minneapolis, MN - 2020 to 2021

As the foundational Data Scientist, I embarked on a mission to manifest our company’s vision of integrating epigenetic testing into life insurance. Starting from scratch, I built and led a team uniquely equipped to merge cutting-edge epigenetics research with advanced analytics and AI, developing new standards for mortality risk assessment in the industry. 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.

Issued Patents:

• Olson, Randal S. and Chen, Brian H. Machine learned epigenetic status indicator. Issued U.S. Patent 11795495.
• Sabes, Jon; Chen, Brian H.; and Olson, Randal S. Machine learning model trained to determine a biochemical state and/or medical condition using DNA epigenetic data. Issued U.S. Patent 11817214.

Lead Data Scientist

FOXO Technologies - Minneapolis, MN - 2018 to 2020

As the foundational Data Scientist, I embarked on a mission to manifest our company’s vision of integrating epigenetic testing into life insurance. Starting from scratch, I built and led a team uniquely equipped to merge cutting-edge epigenetics research with advanced analytics and AI, developing new standards for mortality risk assessment in the industry.

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:

• https://github.com/EpistasisLab/scikit-rebate
• https://github.com/EpistasisLab/scikit-mdr
• https://github.com/EpistasisLab/pmlb

Postdoctoral Researcher

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.

Software Engineer

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.

Skills

Data Science

• 12+ years work experience as a data scientist

• Data visualization expert

• Expert with Python data science ecosystem: NumPy, SciPy, pandas, matplotlib, Seaborn, Jupyter, BeautifulSoup, NetworkX, and more

Machine Learning

• 8+ years experience as a machine learning engineer

• 3+ years experience as a deep learning model engineer

• 1 year working with LLMs & generative AI (PyTorch & HuggingFace)

• Automated Machine Learning (AutoML) expert

Leadership

• 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

Artificial Intelligence

• Ph.D. thesis and research publications focused on the development of Artificial General Intelligence

• 14+ years experience with optimization methods, particularly Genetic Algorithms and Evolutionary Computation

• 14+ years experience with artificial neural networks and neuroevolution

Software Engineering

• 15+ years experience as a software engineer

• Expert with standard SWE practices: modern software design, documentation, version control, unit testing, continuous integration, Agile, Kanban

• Languages: Python (preferred), bash/zsh, C/C++, Java, R, SQL, HTML, CSS, Markdown, JavaScript

HPC & MLOps

• 10+ years experience using HPC systems to run massively parallel compute jobs

• 6+ years experience implementing and using cloud-first data infrastructure

• 2 years experience using Kubernetes and KubeFlow

Biology & biotechnology

• PhD-level study and research in evolutionary biology, ecology, and behavior

• 4 years experience with DNA methylation microarray data (Illumina)

• 2 years experience with NGS data (Illumina & PacBio)

• 2 years experience with genetic engineering technologies

Publications

I have published over 40 peer-reviewed publications and 17 publications as first author.

My publications have over 4,800 total citations and an h-index of 22.

A complete list of my publications can be found on my Google Scholar page.

Last updated May 2025