Spring 2027

Introduction to Design Optimization

Introduction to Design Optimization covers basic concepts and techniques for optimizing engineering design components and systems, including solving truss and finite-element-based problems.

no offering record for this termCredits unavailable
Recorded instructors · Spring 2027 No instructors listed

Summary

1 / 6

Past student reviews · Krishnan Suresh

Group projects were rough because MATLAB isn't good for collaboration. Exams were take-home and pretty easy, keeping the workload reasonable.

What you’ll be able to do

  • Translate a loosely worded optimization problem into a mathematical statement

  • Use the MATLAB optimization toolbox

  • Apply the fundamental theorems of optimization

  • Analyze and optimize structural designs

  • Implement numerical methods of optimization

Source: UW Guide

Grade history

↗
average GPA
letter grades
A
AB
B
BC
C
D
F

All recorded terms · compare terms & instructors

Prerequisites

Course map

M E 306 orE M A 303, or graduate/professional standing, or member of Engineering Guest Students

    • M E 306
    • EMA 303
    • graduate/professional standing
    • member of Engineering Guest Students
    take one
ME 548 used by

“Used by” includes alternatives; linked courses may have other requirements. This is a best-effort interpretation; check the catalog requirements above.

Prerequisite text tree
  • Any of
    • M E 306
    • EMA 303
    • graduate/professional standing
    • member of Engineering Guest Students

Professors

Spring 2027

No instructors recorded for this selection.

Historical instructors & teaching patterns

KRISHNAN SURESH is recorded teaching in Spring 2020, Spring 2022, Spring 2023, Fall 2024. Recorded history may be incomplete and does not establish a future schedule.

Recorded history may be incomplete and does not establish a future schedule.

Calendar & sections

Spring 2027

Schedule loads here as you scroll.

SectionModeEnrolled / capacityWaitlist

Times are Central. Select a meeting for details; export includes recorded dates for the selected sections.

Meeting source records

No records available.

Student experience

the class

Past student reviews · Krishnan Suresh

The course is very MATLAB-focused, and exams were take-home and pretty easy. Grading was lenient, and the overall workload was reasonable.

Recent recorded grades — Spring 2022: 3.87 GPA, 97.1% A/AB (n=34 letter grades); Spring 2023: 3.69 GPA, 85.7% A/AB (n=49 letter grades); Fall 2024: 3.93 GPA, 100.0% A/AB (n=23 letter grades).

difficulty & workload

Past student reviews · Krishnan Suresh

Group projects were rough because MATLAB isn't good for collaboration. Exams were take-home and pretty easy, keeping the workload reasonable.

Past student reviews · Krishnan Suresh

Lectures helped, but notes and powerpoints weren't written very clearly. You didn't have to attend, but it would have helped to follow along.

Topics

  • Optimization of engineering design components and systems
  • Truss and finite-element-based optimization
  • Fundamental theorems of optimization
  • Numerical methods of optimization

Skills

  • Formulating optimization problems mathematically
  • Using MATLAB for optimization tasks
  • Applying optimization theorems
  • Analyzing and optimizing structural designs
  • Implementing numerical optimization methods

Grades

Latest available · Fall 2024— not enough history to project Spring 2027.

average GPA
A / AB grades
letter grades
Instructor

Grade distribution · % of letter grades

A
AB
B
BC
C
D
F

Grades over time

Through Fall 2024

More grade details Grade mix, volume & source data

Not enough comparable courses for Spring 2027 in UW–Madison.

Sources & history

UW–Madison

Catalog & offerings

Descriptions, prerequisites, and recorded course offerings.

Catalog observation history

Observations at scan time; dates do not imply when a catalog change took effect.

Download part 1
Selected offering source records

No offering records for the selected term.

Raw records 
[]
Rate My Professors

Student reviews

Original comments behind the course and instructor summaries.

Read original reviews
Download part 1
Madgrades

Grade history

Recorded grade distributions by term, section, and instructor.

Explore recorded grades
Dataset & model

Recorded 2026-10-14

View the dataset on Hugging Face
Model outputs & technical records
Qwen/Qwen3.8-27B
LLM outputs across runs
Download part 1
Full model traces

Recorded model configuration, reasoning, and tool conversations.

Download part 1
Model & dataset provenance 
{
  "model": "Qwen/Qwen3.8-27B",
  "model_revision": "1d4bf0f2ff6012fd82039f2fa52739d0dd7c60c0",
  "task_version": "17",
  "output_id": "71cb263350d1bb05d2fac588019c81ce8870ee85434442401dd7ef5df29fe529",
  "requirements_status": "needs_review",
  "dataset_revision": "fc1811fa52e581ea57a35c0cf3343f8740a8ffbf",
  "observed_at": "2026-10-14 17:50:09.728220+00:00"
}