I graduated 10 years ago and never used calculus, differential equations, linear algebra, or physics in my job.
I'm not saying this to say they aren't useful. But does anyone find them generally useful for their job? If so, what for? I'd like to know what I'm missing here, if anything. I don't want to go through a refresher just to forget it in another couple of years.
I left college about 12 years ago and I use physics and linear algebra nearly every day, along with trigonometry and a bunch of other branches of math.
The thing for me is that I didn't use it until 4 years ago and now I find myself going through the bibliography of classes I took more than a decade ago to try and 'remember' all this stuff.
As for what I use it for? Right now I'm doing a bit of 3d stuff in the browser (javascript and three.js), the library takes care of many details, but one of the first things I had to do was print a trigonometry cheatsheat (sin, cos, arctan...) and put it on the wall.
I'm not sure this is relevant to computer science, but as a mechanical engineer, I've used differential equations and topology quite a bit in my coding.
Topology has its important role in CAD and CAE softwares (particularly when dealing with manifold/non manifold objects) where it's important to understand the relation that various geometric entites have with one another (whether you're coding a tool or using one). There is also a good amount of research currently being done on automatic CAD model simplification for analysis (FEM/CFD) based on geometric simplification (various methods exist ranging from topology to fourier analysis [1]). Meshing theory also relies quite a bit on topology. [2] (but I don't think anyone denies the importance of topology in CS though)
As for differential equations and calculus, they are heavily used in FEM [3] and CFD [4] and there is therefore a need to numerically evaluate these equations in a efficient manner. They are also heavily used in controls (for instance, in a quadcopter PID controller [5]). So I'm guessing in that case, differential equations are used to describe something you're then modelling in your code through numerical integration. Numerical methods however rely both on understanding calculus and differential equations as a given numerical scheme may be more adapted to a particular type of DE than others [6][7][8][9] (sorry, couldn't find a comparaison of these schemes on a single link so I'm citing a few).
Signals processing and statistical analysis may also be used in conjunction with differential equations such as in turbulence modeling in CFD. RANS (Reynolds Averaged Navier-Stokes) equations essentially average the NS equations over time in order to locate areas of various turbulence strength [10]. LES (Large Eddy Simulation) filter small eddies out of the NS equations in order to be left with only the large eddies thus requiring less computational power [11] (the filtered eddies are modeled separately for the sake of energy balance).
Finally, I would argue that calculus is also used in optimization codes and neural networks with gradient based descents [12][13]
I hope I didn't go off topic with this post, all I was trying to say is that in some fields of computer science, you do have to come up with algorithms evaluating differential equations using numerical methods, and an understanding of calculus and DE is a definitely plus. I'm sure finance has its share of DE to model requiring their understanding.
EDIT 2:
Optimization methods can be used to find optimal solutions to differential equations [A]. I talked about gradient descent earlier, but there's also the simplex method [B] that makes heavy use of linear algebra and topology to navigate in a solution space in order to optimize a solution.
Math and physics are beautiful and tasteful. So there's a liberal arts-ish component of you'd take a fine arts class as part of your liberal arts component of education to develop at least some minimal aspect of good taste and common sense as part of your education.
Its a very vocational list in general and needs some liberal arts, not just to make life worth living, but to develop good taste as a workers tool. There is a slight glimmer in the list where its advised to learn a little technical communication. However learning a little graphics arts wouldn't hurt. Or a little political history might help navigate corporate structures. Or a little persuasive public speaking for those presentations. Or some art so your diagrams and whiteboard talks don't look awful.
Yet going the opposite direction, if we're currently graduating degree holders with a very small minimum of liberal arts who none the less can't fizzbuzz, then this hyper vocational extremely large curriculum isn't going to fit, or we're going to graduate people who can't fizzbuzz and fail to integrate e to the x and also fail to appreciate Hamlet in its original Klingon. Not sure failing even more generalist stuff is better overall outcome. Maybe it could be a 6 or so year long vocational apprenticeship. Or maybe if high school education didn't generally suck. Maybe.
My two latest research projects required all of those things. More specific, I tried (and failed) to model movement in an environment as a particle in an electric field. Defining this model required physics of a particle, and optimizing the parameters required differential equations. A sub-section of the project (not done by me) defined a grammar, which required some properties over a semi-ring, which I remember from Algebra.
Well, the first part of the project got scrapped, because it turns out people behave like a particle only under trivial conditions (or I modeled the problem wrong, that's also possible). The idea was that, since we know which target is attracting a pedestrian's attention, we could model both as a particle being attracted to a target (and being repelled by distractors). Whatever little remained of that idea ended up in another paper[1]. As for the grammar, the best I have is this paper[2].
I apologize for not having anything less dry to read than papers - as I'm not looking for another job, I don't feel the need to get off my ivory tower too often.
For the first 10 years of my job, I never used them. In my current job (working on hydrologically modelling software), every now and then I wish I could remember highschool maths.
I'm not saying this to say they aren't useful. But does anyone find them generally useful for their job? If so, what for? I'd like to know what I'm missing here, if anything. I don't want to go through a refresher just to forget it in another couple of years.