Applied Math -> Computer Science/Computational Engineer/EE

Click For Summary

Discussion Overview

The discussion centers around the selection of upper division courses in applied mathematics that would be beneficial for pursuing a master's degree in computer science, computational engineering, or electrical engineering. Participants explore the relevance of specific topics such as Nonlinear Dynamics, PDEs, Mathematical Optimization, graph theory, Abstract Algebra, and Number Theory.

Discussion Character

  • Exploratory
  • Technical explanation
  • Debate/contested
  • Mathematical reasoning

Main Points Raised

  • One participant suggests that PDEs and Mathematical Optimization are well-suited for the fields of computer science, computational engineering, and electrical engineering, noting that graph theory is likely a compulsory subject in computer science.
  • Another participant expresses uncertainty about the usefulness of PDEs and seeks clarification on their application in the specified fields.
  • A participant highlights that a good PDE course would cover both analytic and numerical methods, suggesting its value in applied science.
  • Concerns are raised about the relevance of Abstract Algebra and Number Theory for engineering, though Number Theory is mentioned as potentially beneficial for computer science, particularly in cryptography.
  • One participant emphasizes the importance of courses that deal with "dirty" models, which are more representative of real-world problems, as opposed to those that focus solely on "nice clean models."
  • Chaos theory and linear dynamics are brought up as additional topics of interest, with a suggestion that fluid dynamics, related to Nonlinear Dynamics, may be relevant.

Areas of Agreement / Disagreement

Participants express differing opinions on the relevance of specific courses, particularly regarding PDEs, Abstract Algebra, and Number Theory. There is no consensus on which courses are definitively the best suited for the fields discussed.

Contextual Notes

Participants acknowledge that the applicability of certain mathematical topics may depend on specific contexts within the fields of computer science, computational engineering, and electrical engineering. There is also mention of varying degrees of rigor in engineering models compared to applied mathematics.

Who May Find This Useful

Students in applied mathematics considering advanced degrees in computer science, computational engineering, or electrical engineering may find this discussion relevant.

MathWarrior
Messages
267
Reaction score
5
I am nearly done with all my basic undergraduate course work and will soon be pursuing the rest of my applied math degree. There are a variety of upper division classes that I have the option of taking. I was wondering which ones seem best suited if you were going to get your masters in either computer science, computational engineering, or EE upon graduating.

Ive been looking into 3 specific topics carefully to see if they are of any use in any of these fields, Nonlinear Dynamics, PDE's, Mathematical Optimization, or graph theory. Which 2 of these topics do you think is best suited?

Thanks.
 
Physics news on Phys.org
MathWarrior said:
I am nearly done with all my basic undergraduate course work and will soon be pursuing the rest of my applied math degree. There are a variety of upper division classes that I have the option of taking. I was wondering which ones seem best suited if you were going to get your masters in either computer science, computational engineering, or EE upon graduating.

Ive been looking into 3 specific topics carefully to see if they are of any use in any of these fields, Nonlinear Dynamics, PDE's, Mathematical Optimization, or graph theory. Which 2 of these topics do you think is best suited?

Thanks.

Hey MathWarrior and welcome to the forums.

My suggestion based on your choices of EE, computer science, or CompE I would say PDE's and Mathematical Optimization. For computer science, graph theory would probably be a compulsory subject or part of a Discrete Mathematics subject that is pretty much required in that degree.

Since you're doing applied math you are obviously going to be better prepared than say only doing pure math subjects.

One thing I should point out to you, is that with engineering you usually have very rigid models that have to be followed and they have to be used because things must work as intended. On saying this some applied math subjects don't start off with the kind of rigid assumptions that an engineering model will use, so just be aware of that.
 
Yeah those two classes are the ones I was thinking of taking, but I am not sure how useful PDE's are? Perhaps someone can enlighten me on where id encounter those in the fields I specified.

There are a few other courses like mathematical modeling for biology, but that seems like it wouldn't be of much use. There is one 2 other classes I am also able to take as extra upper division: Abstract Algebra, or Number Theory. I just want to take whatever will be the best suited for my field.
 
MathWarrior said:
Yeah those two classes are the ones I was thinking of taking, but I am not sure how useful PDE's are? Perhaps someone can enlighten me on where id encounter those in the fields I specified.

There are a few other courses like mathematical modeling for biology, but that seems like it wouldn't be of much use. There is one 2 other classes I am also able to take as extra upper division: Abstract Algebra, or Number Theory. I just want to take whatever will be the best suited for my field.

Many problems in applied science deal with systems that involve more than one input variable. A good PDE course will touch both on analytic methods and numerical methods. From this I think you can see why it would be a valuable subject to choose.

I really can't see a huge amount of benefit for engineering with regard to Number Theory and Abstract Algebra, but for computer science number theory might be beneficial especially in the context of cryptography.

Personally if you want to do engineering any subject where you "get your hands dirty" has my vote. A lot of math courses work with "nice clean models" that have analytic solutions but most modeling problems aren't like that. So if you get courses that deal with "dirty" models that you have to use and analyze in any kind of context (biology, economics, physics, chemistry etc) then that will definitely help you.
 
Is there any use for chaos theory and linear dynamics in any of these fields?
 
MathWarrior said:
Is there any use for chaos theory and linear dynamics in any of these fields?

I am not sure if you meant "nonlinear" instead of "linear" dynamics, but if you meant the former, you might be interested in fluid dynamics which is basically capture in the Navier-Stokes Equations.
 

Similar threads

Applied Math PhD candidate but I hate group theory
  • · Replies 13 ·
Replies
13
Views
3K
Courses Advanced Math for Computational Material Science Engineering
  • · Replies 2 ·
Replies
2
Views
2K
Which MSc to do after BSc physics if you love to code?
  • · Replies 10 ·
Replies
10
Views
3K
Courses Preparation for an applied math career
  • · Replies 5 ·
Replies
5
Views
2K
Programs Is a Physics BA a good route for exciting CS/Engineering Work?
  • · Replies 3 ·
Replies
3
Views
2K
Undergrad Applied Math + Computer Science or Computing
  • · Replies 1 ·
Replies
1
Views
1K
Studying Should I take up electrical engineering or computer science?
  • · Replies 8 ·
Replies
8
Views
4K
Scientific Computing vs Applied Math at UMN
  • · Replies 1 ·
Replies
1
Views
3K
Considering Switching from Physics to Computer Engineering
  • · Replies 7 ·
Replies
7
Views
3K
Programs Electrical Engineering PhD or Applied Physics PhD?
  • · Replies 3 ·
Replies
3
Views
1K