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What are the math heavy CS areas with high demand?

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What are the math heavy CS areas with high demand?

#1
I'm an undergraduate student who's thinking about a double major in computer science and applied math. I'd like to choose a math heavy, high demand computer science area to specialize in. I like the utility and elegance of math, and I'm trying to find a CS area that uses many different branches of math.

I'd also prefer if the area changes relatively slowly compared to other computer science areas (so maybe not security).

I'm currently thinking that graphics or machine learning would be high demand areas that use a lot of math, but I'm looking for more suggestions and advice. Thanks.

Re: What are the math heavy CS areas with high demand?

#3
Actually computer security doesn't change very fast compared to other industries, and is probably a very good fit if you have a math background. But machine learning would be fun too. Stay far, far away from graphics if you are worried about rapid change.

But really, find what you're interested in and do that. It may involve trying them all out, or reading up some reference works on each. Making an important life decision based on “what's in demand” is a very poor choice.

Re: What are the math heavy CS areas with high demand?

#4
I think your thinking is right, machine learning is probably a good area as far as jobs go. Depending on your CS interests you'll find what areas of math they use most. AI / machine learning, learn lots of probability and statistics. High-performance, scientific computing, graphics, maybe more of a focus on linear algebra. Algorithms or theory or programming languages, lots of discrete math, logics, algebraic structures, etc. Of course it's good to get a good grasp of the basics of all these, since they're definitely not exclusive, and which you'll get from your degree, and beyond that, well explore, and enjoy!! Good luck!

Re: What are the math heavy CS areas with high demand?

#5
post #3

Actually computer security doesn't change very fast compared to other industries, and is probably a very good fit if you have a math background. But machine learning would be fun too. Stay far, far away from graphics if you are worried about rapid change. But really, find what you're interested in and do that. It may involve trying them all out, or reading up some reference works on each. Making an important life dec…

Thanks for the advice. I actually didn't know that graphics changed very fast. I'm only partly making this decision based on what's in demand. As long as the area is math heavy and broadly applicable, I'll probably enjoy it.

Also, I was thinking of "in demand" with a more long term view. I would think that security and artificial intelligence would continue to stay in high demand well into the future.

I mostly just want to choose an area where I can use many different branches of math, so I keep my math skills in practice. I also like writing code, as long as it involves math and is not boilerplate or repetitive.

Re: What are the math heavy CS areas with high demand?

#7
post #5
post #3

Actually computer security doesn't change very fast compared to other industries, and is probably a very good fit if you have a math background. But machine learning would be fun too. Stay far, far away from graphics if you are worried about rapid change. But really, find what you're interested in and do that. It may involve trying them all out, or reading up some reference works on each. Making an important life dec…

Thanks for the advice. I actually didn't know that graphics changed very fast. I'm only partly making this decision based on what's in demand. As long as the area is math heavy and broadly applicable, I'll probably enjoy it. Also, I was thinking of "in demand" with a more long term view. I would think that security and artificial intelligence would continue to stay in high demand well into the future. I mostly just w…

Graphics programming isn't that fluid. A lot of hay was made about moving away from fixed-function to the shader model, but since then it's been iterative API changes and growth to better target certain goals. OpenGL is throwing overboard most of the dumb stuff from its earlier versions and is turning into a pretty nice API overall.

Now there's a lot of innovation in terms of specific techniques to achieve certain visuals, but that's the same as any other field - read the paper, implement it. The core techniques should be fairly static for at least the next 4-5 years (because it'll probably take that long for GLES 3 to be widespread) and evolve incrementally after that.

Change is not something you should be worried about there.

Re: What are the math heavy CS areas with high demand?

#8
In my view, I vote for machine learning. In order to study better in machine learning area, you need to have better understanding in statistics, probability, matrix, optimization and numerical computation. machine learning just like a model, the important thing is that know how to build, it exactly mathematics can help us.

Re: What are the math heavy CS areas with high demand?

#9
post #4

I think your thinking is right, machine learning is probably a good area as far as jobs go. Depending on your CS interests you'll find what areas of math they use most. AI / machine learning, learn lots of probability and statistics. High-performance, scientific computing, graphics, maybe more of a focus on linear algebra. Algorithms or theory or programming languages, lots of discrete math, logics, algebraic structu…

Thanks for the comment. High performance and scientific computing jobs seem a lot rarer than AI / machine learning jobs, which is why I think the latter is a better choice for me (I have no preferences between those areas right now).

I'm also fairly interested to see how AI / machine learning develops in the future, and I think it will involve more math, so it definitely seems to be a good choice.

Re: What are the math heavy CS areas with high demand?

#10
post #8

In my view, I vote for machine learning. In order to study better in machine learning area, you need to have better understanding in statistics, probability, matrix, optimization and numerical computation. machine learning just like a model, the important thing is that know how to build, it exactly mathematics can help us.

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