How can I combine my interests for pure mathematics and computer science in college? I’m a high school senior who's gone through quite the self-introspection the past few months while applying for college, and I have a bit of a dilemma. All my life, I've loved &amp; excelled at mathematics, and wants to study &amp; explore it very much in depth in college. I get very excited when I read up on fields such as number theory, analysis, topology, and algebraic geometry. On top of that, I've also realized that although I have no experience programming, there are wonderful merits to applying math to computer science and would love to apply my math skills to a fast-growing industry.

I feel, however, that studying comp sci will "limit" the scope and depth of the math I study, because joint programs of math and comp sci will only make you take math classes relevant to the study of computer science. Out of the Common App colleges I'm applying to, Emory, NYU, and BU have joint majors in math and computer science, while UMiami only has a BS in mathematics, and Georgia Tech has BSs in discrete and applied mathematics. For Emory, for instance, I'll be "missing out" on multivariable calculus, complex variables, real analysis, and abstract algebra.

If there is a way to combine these two interests without limiting the mathematics I learn, that'd be amazing, but if not, so be it. If you feel I have certain misconceptions, please feel free to point them out. Lastly, I know this is not the best place to ask this question, as it is directed towards students and researchers of computer science, but I would love your input and appreciate it ahead of time!

Thank you!
Math is heavily used in both computer security, machine learning and AI.


Computer Security, such as encryption and related fields is all about finding math that makes it impossible to retrieve information without being the intended recipient.  With quantum computing possibility being a reality within the next 10 - 20 years there is a lot of work needed to come up with new ways of securing data.  Number theory is very relevant here.
Machine learning is heavily based on statistics.  new algo's with better capability of prediction is always relevant, and a very hot topic.
AI, while strictly an area of machine learning, are typically resolving to other areas of of learning than typical stats.  Any advancements in this areas will be done by people with strong math background.