Graph theory - it has an immense amount of overlap with computer science.
What are the math heavy CS areas with high demand?
21–30 of 54 posts
Re: What are the math heavy CS areas with high demand?
#22Graph theory - it has an immense amount of overlap with computer science.
Sure, but is there work in graph theory outside of academia? Obviously there are people who use it to solve real problems but I'm unsure if you can really get a job as a graph guy.
Re: What are the math heavy CS areas with high demand?
#23Quant / algorithmic trading
Computational biology
Scientific/industrial simulation
Re: What are the math heavy CS areas with high demand?
#24Earlier quoted context omitted.
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 vi…
Very inaccurate and misleading. You're confusing learning an API (easy) with doing actual graphics programming. Graphics programming involves deep understanding of the target hardware. The level of sophistication of the hardware determines which graphics techniques to pursue for the best results. Often it's a balance of your ability to optimize along with achieving the highest fidelity of output.
For example, availability of floating point render targets -- how do you use them, and for what? How does the hardware handle them? It's different across devices even in the same generation! How does the hardware optimize rendering of opaque vs transparent objects? It's different across devices. Let's get really specific -- how many cycles does a medium precision square root take? Do you use pow or not? How much does a texture lookup cost? Hopefully you can guess the answer by now -- it's different on every device.
It gets exciting when a blend of API and hardware (which includes additional supported and unsupported extensions, which yes, also change with every OS/hardware combination) requires the invention of a novel technique to fully utilize the resources at hand. It's a continual balancing act of visual fidelity and performance with the end goal of squeezing out every last bit of memory and computational bandwidth.
Enough about hardware which is really just an important detail of the field. Being a great graphics programmer requires keeping up to date with the community of blogs and published papers, all of which are a constantly updating source of experimentation and novel techniques. This doesn't even touch on the artistry involved. Being at the top of the field takes extreme dedication and is absolutely not a "learn once and refresh now and then" activity.
Summary: real-time graphics programming is one of -the- most difficult fields to stay at the forefront.
Re: What are the math heavy CS areas with high demand?
#25How about computational finance? Finance is what drives pretty much all modern economic activity around the world, and the fundamental concepts in finance haven't changed for hundreds of years, which takes care of both the stable/slow-changing and in demand criteria. It is also heavily mathematical if you choose to focus on the quant side, with probability, statistics, stochastic calculus, PDE's, and even measure theory being used in some form. Also, software is becoming an increasingly important part of modern finance, with things like electronic exchanges, high frequency trading, complex derivative/option pricing, prop trading, and actuarial science.
And the skills you'll learn in finance will be transferable to a range of other fields - advertising and cloud distribution, which pretty much drive most tech startups' revenue, heavily rely on concepts and techniques that you'll learn in finance.
Here's an interesting course you can take a look at: http://www.algorithm.cs.sunysb.edu/computationalfinance/ Note that this is by steven skiena, the author of the well-known Alogrithmm Design Manual. Khan Academy also has a pretty extensive series on modern finance.
Re: What are the math heavy CS areas with high demand?
#26I 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…
It depends on what side of AI/ML you end up on, though. The research-heavy side involves lots of math and requires a PhD (or a MS + experience, in industry); the data engineering & infrastructure side is almost solely coding (and distributed systems design).
Re: What are the math heavy CS areas with high demand?
#27Quick question- are you aiming for a computer science/software job with lots of math, or a math job that involves computing?
It's an important distinction. The people who are doing math with the help of computers (rather than doing software that uses math) are much more involved in mathematics.
Re: What are the math heavy CS areas with high demand?
#28There's a machine learning path that fits this: study math/stats/algorithms, get a graduate degree, work on research in industry or academia.
Your question is somewhat vague, though. Do you want to spend the majority of your time working on math? Even machine learning researchers only spend a majority of their time on annoying data cleanup issues, model coding, or data infrastructure. Further, as you become more successful you worry about grant-writing, lab management, or stressing about tenure (or, if industry, department cuts). What's your motivation for entering a "slow" field? Regression is going nowhere but ML's research frontiers are expanding rapidly right now.
Note also that you won't land this work with just an undergrad degree, so you should add another 2-5 years of schooling if considering ML.
Re: What are the math heavy CS areas with high demand?
#29I think you're setting yourself up for disappointment with unrealistic expectations. People that are in demand are programmers and good programmers code 90% of time. Some people, including yourself, suggested graphics but read the history of DOOM and read its source code: despite being a cutting edge technology at the time, 90% of the code is the non-math drudgery: reading and writing files, networking code, performa…
This is an excellent point, although I disagree with 90%. Lots of a developer's time goes into QA/testing, design, and conversations about requirements and goals. I think developers spend much less than 90% of their time with an IDE open.
Re: What are the math heavy CS areas with high demand?
#30DSP related jobs are pretty math heavy, albeit in a very particular focused area of math. These jobs are in demand and highly specialized, so you aren't going to see a thousand job postings, but when you find one, if you are good, they will want you.