Current instructor

Stephen Wright

Adjusted rating
RMP difficulty
captured reviews
About this rating

Raw average: 4.20/5 from 10 quality ratings. The adjusted rating blends this with the UW review average (3.66/5), weighted as 20 additional ratings. Smaller samples stay closer to that average. Each captured review is counted once in the prior; this does not correct who chooses to leave a review.

RMP profile ↗ · All captured review dates; profile matched by name.

What students say

Original student reviews · all captured dates

COMPSCI/ECE/ISYE 524
Quality 5/5Difficulty 4/5
Steve is providing really great lecture and is really nice to talk to after class. He is really knowledgable and gives very great introduction to how optimization works. This is a class that you don't want to miss if you are interesting how optimization works. The project are in julia code, which is super nice to use.
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COMPSCI/ECE/ISYE 524
Quality 5/5Difficulty 4/5
If you just want to get an A in this course, then the difficulty of this course is 2-3, but the content and the topics of the lectures are more difficult than average. Those topics are insightful and will help you succeed in future CS learning (especially for algorithm and machine learning). Prof. Wright is very kind and generous in grading.
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COMPSCI/ECE/ISYE 524
Quality 3/5Difficulty 5/5
This class was so much more difficult than it needed to be. That being said, aside from general disorganization in lectures, he does a good job of presenting the material during lectures. My only qualm with this prof is that his grading criteria is very (and unnecessarily) harsh.
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COMPSCI/ISYE/MATH/STAT 726
Quality 2/5Difficulty 5/5
Professor Wright's lectures involve little more than transcribing the textbook on the board. Their focus is on rigor over intuition. Logistics are not managed well. TA contact information and grading criteria were never provided. This is a notoriously difficult course. In a class full of math and CS PhD students, the average grade is about a B.
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COMPSCI/ISYE/MATH/STAT 726
Quality 4/5Difficulty 4/5
Stephen is a good teacher and certainly is respected by every student. He has written several books and usually lectures from them, which makes it easier to catch up if you missed lectures. The assignments were graded in an insanely harsh way, though, and the professor doesn't seem eager to answer questions during office hours.
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Personal experiences, not a representative survey. Profile matching and captured coverage are shown in the source details.

Classes with Stephen Wright

COMPSCI 541

Theory & Algorithms for Data Science

3 credits

Theory & Algorithms for Data Science covers probability, concentration inequalities, high-dimensional geometry, estimation, optimization, PAC learning, and distribution testing using Python.

Offering recorded · Spring 2027 · Sources

Stephen Wright

historical GPA · grades

Spring 2025–Spring 2026 · limited sample
COMPSCI 699

Directed Study

1–6 credits

Directed study projects for Computer Science juniors and seniors, arranged with a faculty member.

Offering recorded · Spring 2027 · Sources

Fred SalaDan Negrut+49 more

historical GPA · grades

Fall 2022–Spring 2026 · limited sample
COMPSCI 899

Pre-dissertator Research

1–9 credits

Pre-dissertator independent research supervised by a faculty member for students who have completed a master's degree but have not reached dissertator status.

Offering recorded · Spring 2027 · Sources

Fred SalaSong Gao+63 more

No recorded grade history

Recorded teaching history

Distinct courses recorded per term

Explore courses taught by this instructor →
Browse recorded courses
TermCourseTitle
Spring 2027COMPSCI 541Theory & Algorithms for Data Science
Spring 2027COMPSCI 699Directed Study
Spring 2027COMPSCI 790Master's Thesis
Spring 2027COMPSCI 799Master's Research
Spring 2027COMPSCI 899Pre-dissertator Research
Spring 2027COMPSCI 990Dissertation
Spring 2027ISYE 890Pre-dissertator's Research
Spring 2027ISYE 990Research and Thesis
Fall 2026COMPSCI 699Directed Study
Fall 2026COMPSCI 790Master's Thesis
Fall 2026COMPSCI 799Master's Research
Fall 2026COMPSCI 899Pre-dissertator Research
Fall 2026COMPSCI 990Dissertation
Fall 2026COMPSCI/ISYE/MATH/STAT 726Nonlinear Optimization I
Fall 2026ISYE 890Pre-dissertator's Research
Fall 2026ISYE 990Research and Thesis
Fall 2026MATH 698Directed Study

Teaching history may be incomplete. Course pages contain course-specific feedback and citations.

Instructor identity & provenance 
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