ALUMNI SPOTLIGHT: Bryan Bischof '08

Since graduating from Mother Fair 16 years ago, Bryan Bischof ’08 has earned a PhD, traveled the world, authored a book, developed a system to help you identify your favorite coffee flavor, walked every street* in Berkeley, CA, and still found time to talk to his undergrad alma mater about how classes at Westminster helped form connections to the AI magic he works on developing today. 

We recently caught up with the mathematician, author, teacher, team leader, mentor, city-walking near-completionist and coffee connoisseur, to help us solve for how his career has taken shape since his time on campus. 

Can you tell us about your career path since graduating from WC?

After graduating from Westminster in 2008 with a degree in Mathematics (which included a lot of coursework in physics, philosophy, and computer science), I went into a PhD program in math at Kansas State University. I spent 6 years as a pure mathematician in areas related to algebra, geometry, and mathematical physics. I had the opportunity to travel frequently, including experiences in Japan and Germany as a visiting researcher. During my fifth year of graduate school, my advisor sadly passed away, so I extended my timeline by a year. Due to financial constraints at that time, I decided that I should enter industry work, despite my love of research and pure math. 

I applied for jobs in data science and software engineering, ultimately choosing to join a recently IBM-acquired startup company in California as a scientist working on time series processing. From there, I moved to a job at Blue Bottle Coffee to lead their data engineering technology. This was my first time managing others in addition to technical expectations. I built ML (machine learning) models and engineering systems, including a recommendation system to tell you what kind of coffee you’d like based on your favorite flavors in food! 

After the Nestle acquisition of Blue Bottle, I joined the personal styling company Stitch Fix, where I worked on many deep problems in machine learning, optimization, logistics, recommendation systems, and more. I worked on a truly impressive team of scientists with backgrounds in everything from anthropology to astrophysics. 

From Stitch Fix, I moved to another startup company, building the teams from scratch and working with the executive team as the company went through hyperscaling. I then left this role following my love of research, focusing on AI (artificial intelligence) at an institute in Berkeley, California.  

What kind of work do you do currently?

I currently lead the AI team at Hex, a business-to-business SaaS (Software as a Service) company, which combines my experience as a data scientist with AI-language modeling. The startup makes software for data analysts and data scientists. Professionals in industries like healthcare, education, biotech, and many more use hex like a “lab notebook” to do all of their data work.

What were some of the classes and/or organizations at Westminster that helped shape your journey?

Because I started out in math, many of my math classes were very important; algebra, topology, and linear algebra especially. My math PhD taught me a lot of ways of thinking which built on these undergrad classes and are still relevant today. 

I also took computer science classes at Westminster just for fun and as part of the WC liberal arts education, and those have turned out more relevant than I expected. I especially remember computer architecture which helped me learn to form connections between math and computer science. 

Do you have a moment or experience from your time at WC that you’ll never forget?

I once stayed very late in the physics lounge before an exam and… well, accidentally fell asleep. My professor woke me up in the morning and told me my exam was about to start. I also have very fond memories of my undergraduate research at Westminster. 

What do you do in your spare time?

I am a man of many hobbies. Lately, I’ve been on an adventure to walk every road (285 miles+) in Berkeley, California as documented in this 2023 Berkeleyside.org community story. 

However, I'm also extremely interested in side projects around recreational math, hard biking routes, and specialty coffee. 

In December 2023, my first book was published. Building Recommendation Systems in Python and JAX is now available on Amazon. 

In addition, I am an adjunct professor teaching data science to Master of Business Science students at Rutgers University. This opportunity came from Westminster connection, Dr. Christie Nelson ’06, and I’ve been teaching for the last 4 years. 

From your experience working for a coffee company....how do you take your coffee and do you have a favorite type?

I drink black coffee and I brew as a pourover or an espresso. My favorites are bright and delicate coffees; frequently African coffees are among my favorites.

Do you have any advice for college students looking to work in AI?

Start now. Everyone. Even if you have no interest in computer science or software or math. Start playing with AI tools IMMEDIATELY. AI is not going to turn into robotic overlords soon, but AI is going to be like excel in a few years: if you can’t use it you’ll be left behind by your colleagues. 

If you want to work on AI itself, don’t skip the math! The secret is that you don’t need a deep understanding of math and statistics to develop AI applications, but it’s like hiking in a backcountry without bear spray: you may find yourself in danger! AI is much easier understood, when you have a curiosity for new mathematical ideas.

Can you offer some ideas how your fellow Titan alumni should begin their exploration with AI - where's a good place to start? How can the average person use AI to their advantage?

The easiest way to get started is to play with ChatGPT, and use other tools more relevant to your jobs/hobbies. When getting started on some research, start by asking perplexity or ChatGPT (but make sure you fact check!). When thinking about planning a trip, see what chatGPT might recommend. Interested in getting into video editing? Try Runway or Descript. There are plenty of exciting tools being released and it’s important to start adjusting to them. 

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