Matt Gietl, MPCS part-time student: “Learn from world-class faculty and strike a solid work-life balance.”

University of Chicago Masters Program in Computer Science students push boundaries and innovate across many facets of industry. Whether it’s developing seamless UX interfaces, engineering software at fortune 500 companies, working in big data or keeping networks secure; our students use their applied skills education from MPCS to problem-solve, create, and elevate the computer science field. Learn from their stories and discover how a CS background can prepare you for cutting-edge careers.

Matt Gietl University of Chicago MPCS

Matt Gietl, Algorithmic Trader at TransMarket Group, is a current part-time student at MPCS. He tells us how his education at MPCS has helped him at work, his favorite course at MPCS so far, and why attending part-time is a great choice for work-life balance.

How has your MPCS education thus far contributed to your workday?

One of the earliest things I recall explicitly benefiting my work came out of taking the Computer Architecture course. We were talking about how more modern hardware-level computing advances mostly benefit parallel applications when it hit me: I was running most of my research-oriented code (on some high-powered multi-core servers) completely in serial, even though it had natural, trivially parallelizable breaking points.

I've since changed that and seen a pretty hefty productivity boost as a result.

What motivated you to apply and enroll to the MPCS?

After I finished undergrad and started working full-time, I still wanted to learn more about CS. I'd often try picking up online courses or various textbooks, but I'd quickly find myself falling off-track a couple of weeks in. I felt that I'd be better able to stay on track with more explicit structure and with real feedback.

Please tell us about attending MPCS as a part-time student. We'd love to hear more about that experience (why you chose to go part-time) and how it works for you.

The part-time MPCS program strikes a great balance of letting you carry on with your career while also providing a structured setting for learning more about CS. Something I've noticed about being in this program part-time while also working is that when I learn about a topic in class, I'm often able to map it out and connect it to something I care about from a work perspective - or at least understand why people would care about it, which I feel enriches my learning experience.

Would you recommend MPCS to others? If so, why?

I'd definitely recommend MPCS to others. One thing in particular that has impressed me is that people can come into the program from many different CS background levels. Even if you have no prior experience, you can still find a good balance of accessibility and rigor based on the way that placements and introductory courses are set up.

The biggest reason I would give to somebody in my shoes (decent academic technical background and works in a CS-oriented job) is that many of the people you have a chance to learn from truly are world-class in their field and have a lot of insight to bring to what they teach.

What has been your favorite MPCS course so far?

One course in particular that I loved was High Performance Computing. While it had the highest workload of any course I've taken in MPCS so far, working through the class gave me a good appreciation for the work and the sorts of problems that really seem to be driving computing technology forward. This also helped me to get a sense for how and why we've arrived at some of the hardware/software solutions that exist today.

One of my favorite course projects (in MPCS, but also likely ever) was the final project for this class. We were tasked with simulating an n-body problem in 3D space of up to 1,000,000 points. Essentially, we needed to simulate what happens if each of these points starts with some initial position and velocity while all gravitationally attracted to one another. We ultimately got to run it on a supercomputing cluster at Argonne National Lab across 1024 nodes! I remember the excitement when the full code ran successfully (along with some level of shock that it did).

Do you have any advice for someone considering applying to MPCS?

If you're looking to get a stronger base in CS or to develop one, I think this program can be valuable. For those attending part-time with reasonably heavy workloads, I'd recommend planning to take one class a quarter: this has given me a solid work-life balance.

What are your goals upon graduation?

For the foreseeable future, I plan to continue working in the algorithmic trading space. While I'm not sure yet what I'd like to pursue farther out from that, I've considered the possibilities of trying to teach or work in more of a scientific computing research role (the latter being inspired by my experience in HPC-oriented courses).