Last updated January 2022
I’m the husband to an incredible wife and the proud father of four kids. We live just outside of Bristol, England where I’m the tech co-founder at Envelop Risk Analytics. In whatever time is left I run and explore. I also used to be a pretty serious water skier. And World of Warcraft player. But now just family, work, and running.
Before ultras or triathlons
I grew up exploring the dense mountains and forests around my family’s rural home in Morgan County, TN, constantly trying to keep up with my older brother and cousins. My background is a good parallel to my current mix of interests: one of my grandfathers got an 8th grade education before working to help support his family as a coal miner, a prison guard, and a GI in WW2, and my other grandfather got a PhD in nuclear physics from MIT working with an advisor who would become a Nobel Prize winner. I’m equally proud of both.
I’ve been running most of my life. In high school I was a good, but not great runner. During college and grad school I essentially took a full decade off from the sport. My physical activity consisted primarily of intramural softball and shoveling snow, and while writing my dissertation I weighed a solid 20% more than I do now.
How I got started in endurance sports
After grad school I rediscovered my love of the mountains on a road trip out west that included hiking the John Muir Trail with my aforementioned incredible wife Jessi. She finished (and loved) that hike despite having never camped a single night in the backcountry in her life. Part of that trip can still be found on her old pre-kids blog. After that trip, I decided I wanted to physically challenge myself and see what I was capable of while I was still capable of it.
I ended up running the 2013 Marine Corps Marathon, and it was an absolute disaster. It was my first race in 10 years, my longest race by 20 miles, and my training had been horribly insufficient. Of course immediately after that I said, “I think I can do better” and signed up for another.
A year later I had the Boston Qualifier I had originally been aiming for, but it was a year and a half before I could actually run Boston. I needed something to keep me in shape and challenge me until then. So I decided to give ultras a shot, because I loved trail running. Then I decided to give triathlons a shot, because I loved running and biking and figured I “only” needed to learn how to swim.
I’ve gotten a tremendous amount of joy, strength, and perspective out of both ultrarunning and triathlon. I’ve encountered many of my limits, both physical and mental, and then discovered that I could push them further than I ever thought possible. I still consider myself a trail runner at heart and feel most at home in the ultrarunning community, but I did love the unique challenges that triathlon brought and the wonderful people it gave me the opportunity to meet (although I never did quite figure out that swimming thing). Through this blog I hope to be able share my experiences in those sports with others and motivate them to get out there and enjoy their own adventures.
How I became a data scientist
I’ve always been a math and computer person who enjoys finding patterns and automating complex processes. I was introduced to machine learning while doing my MS at NC State, and then really started to dive into it for my my PhD at Carneie Mellon. My research there was on brain-computer interfaces, and I primarily worked on translating the raw neural signals into usable control signals for computer cursors, robotic arms, and other assistive devices. My work was essentially a two part process: developing digital signal processing algorithms to remove noise from the neural data, and then applying machine learning algorithms to map the clean data to user intent. It was incredible to be a part of that research and it’s still hard to imagine doing work that’s more fulfilling or interesting (Paralyzed man moves robotic arm with his thoughts).
After grad school I joined Lockheed Martin, which is what originally brought us to the DC area. I expanded my work in data science and got to experience firsthand the breadth of domains and applications that machine learning can be applied to. I was essentially an internal machine learning consultant and became the Technical Lead for Corporate Data Analytics. I was exposed to incredible technologies and was able to work on some highly rewarding projects, but in the end the corporate lifestyle wasn’t for me.
An opportunity at a startup, where there was less bureaucracy and I would have more influence over research and applications, was something I couldn’t walk away from. In the summer of 2015, around the same time that I got serious about ultrarunning and triathlons, I made the jump to become the Director of Analytics at QxBranch, a data analytics and quantum computing software startup in downtown DC that was eventually acquired by Rigetti Computing. I greatly enjoyed my time there and got to help grow the company from just five people to over 30 and beyond a Series A fundraise.
Despite the heavy workload and unpredictable hours of being at an early stage startup, it actually helped my training tremendously. The schedule flexibility allowed me to take care of family responsibilities and fit training in whenever I could, and I even had a very nice route through Rock Creek Park that I could run or bike as my commute. Most importantly, no one cared if I showed up to the office covered in sweat, rain, or mud after a long run!
One of the projects I led at QxBranch was a system to quantify companies’ cyber risk to more effectively price insurance for that risk. We partnered with a company in the UK to create another startup, Envelop Risk, that could better deliver that product to customers and insurance partners. In 2019 we moved to Bristol so that I could build our team there, and in 2021 we completed a Series B round led by SoftBank. In 2022 we’re moving back to the US where I’ll continue working for Envelop remotely.