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Mark O

- Research Program Mentor

PhD candidate at University of Chicago


Foundations of data science, machine learning, mathematics, probability, statistics


I work in mathematics research, in particular on probability theory. The models that I work with were originally defined by statistical physicists, trying to answer questions about molecular structures, ferromagnetism, and even string theory. I work to better understand the mathematical structure that makes the models useful in understanding the real world. In my free time, I am the music director for an all scientist graduate student a capella group at UChicago. I also enjoy spending time outdoors, and am a member of really far too many book clubs.

Project ideas

Project ideas are meant to help inspire student thinking about their own project. Students are in the driver seat of their research and are free to use any or none of the ideas shared by their mentors.

Looking inside the black box: why machine learning works

When we read about machine learning in media, it's often presented as a black box; that is, data goes in, the computer does some magic, and out comes a recommendation for which socks you will find most comfortable. While it is true that machine learning algorithms must be complex to solve complex problems, with a little bit of work, we can develop a remarkably deep understanding for why certain models behave as they do. Together, my student and I can pick a problem that we think machine learning might be able to offer a solution to. We can explore a variety of methods, experiment with them to see which may offer the best results, and dive into some theory to understand why we are seeing the results that we observe. At the end of our time together I hope that my student will have developed some experience with programming, will have learned some mathematics that they likely won't encounter again until they reach university and will be able to explain the core idea behind several machine learning methods. I would like to conclude our time together by authoring a technical piece of writing (or preparing a technical presentation) which encapsulates the work that we have done together.

Coding skills

Python, MatLab, C, Java, Mathematica, R, JavaScript, RISC-V

Languages I know

Swedish - fluent

Teaching experience

I've began teaching as a piano teacher in high school. Soon after I started tutoring in math as well. I've continued as a private math tutor all the way through college and graduate school. I currently teach in the UChicago math department and take part actively in Chicago Center for Teaching and Learning programs on pedagogical development.


Work experience

The Voleon Group (2020 - 2020)
Research Engineering Intern
Center for Integrative Planetary Science, UC Berkeley (2019 - 2021)
The University of Chicago (2021 - Current)
Graduate Student Researcher


University of California Berkeley (UC Berkeley)
BA Bachelor of Arts (2021)
Mathematics and computer science
University of Chicago
MS Master of Science
Applied Mathematics
University of Chicago
PhD Doctor of Philosophy candidate
Applied Mathematics

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