First and foremost, I’m a data tinkerer based out of the Portland metropolitan area. I specialize in artificial intelligence, data science, machine learning, and data visualization, although I’m always learning something new to make myself more useful to my clients and collaborators. I regularly write about my latest work on my personal blog, where I’ve become known for computing optimal road trips around the world and solving Where’s Waldo?, among many other things. My work has been featured all over the world and in the news, including the New York Times, Wired, FiveThirtyEight, and much more.

I work tirelessly to promote open and reproducible science, leading by example and openly publishing my work on GitHub and open access journals. I’m also passionate about training the next generation of data scientists to be more efficient, effective, and collaborative in their work, and do so by writing online tutorials, recording video tutorials, teaching hands-on workshops, and mentoring local students in my research specialties. If you would like to commission me to teach a workshop or give a talk in your area, please get in touch.

Randal S. Olson

You can follow me on Twitter or Facebook, where I post new data visualizations every day. (Disclaimer: The data visualizations aren’t always created by me.) I’m also a community leader for the popular data visualization subreddit /r/DataIsBeautiful, which now serves over 2 million unique readers every month.

When I’m not glued to the computer working on research, I enjoy traveling, geocaching, weight lifting, playing PC and board games, karaoke, and taste testing the fine products of Portland’s breweries. (The latter two often together.) I’m always looking for something new to do or try, so if you need a partner for your latest adventure, send me an email.

Last but not least, I’m a proud dog owner and enthusiast. Pictured below is my basenji / jack russell mix, Zack. He is a little ball of energy and happiness that never ceases to make me smile.

Photo: Zack


Prior to my current role, I spent three years working with Prof. Jason H. Moore at the University of Pennsylvania Institute for Biomedical Informatics, where I developed state-of-the-art, open source AI and machine learning tools with a focus on biomedical applications. One of my most successful projects with Prof. Moore was the invention and development of the Automated Machine Learning tool TPOT, which remains one of the most widely-used open source Automated Machine Learning tools in the world to this day.

For my graduate education, I spent four years working on my dual Ph.D. in Computer Science & Ecology, Evolutionary Biology, and Behavior (EEBB) with Prof. Chris Adami at Michigan State University, culminating in a Ph.D. thesis on the evolution of intelligent animal behavior that guides much of my thinking in regards to Artificial Intelligence research today.

I attended the University of Central Florida for my undergraduate degree in Computer Science. During my time there, I was awarded the prestigious Department of Defense SMART Scholarship to complete an undergraduate Honors thesis developing automated robotic locomotion methods with Prof. Kenneth Stanley.

If you would like to read more about my academic accomplishments, please see my CV.