Current instructor

Vikas Singh

Adjusted rating
RMP difficulty
captured reviews
About this rating

Raw average: 3.58/5 from 12 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

766 · course not matched
Quality 5/5Difficulty 4/5
I took this class the semester I was leaving with a masters. really enjoyed it and learned a great deal. more than any other class in my two years there. it almost made me want to do research in AI and computer vision. if you are average at math, skip this class. there are three big homeworks and paper reviews each week. plus a research project.
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COMPSCI/ECE 760
Quality 2/5Difficulty 5/5
Enthusiastic teacher but unhelpful outside of class (he talks but it's never useful or direct), rambles on during class and doesn't take into account the workload of students from other classes (assigns endless number of difficult homeworks). I would not take any course with him, just wait until another professor is teaching them.
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CSA · course not matched
Quality 4/5Difficulty 3/5
Great instructor! I took CS540 at UW-Madison as a senior in high school and I still received an A even though I spent most of my time focusing on my high school classes. He was passionate about the topic and was a very nice guy. His slides are the same as his predecessors who taught 540 with some small variation. Great class overall, very valuable.
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COMPSCI 540
Quality 5/5Difficulty 2/5
This class needs LOT of work on programming and math. I barely managed a B. But what Vikes covers is very useful. Two questions on my interview at a tech startup were very similar to the ones on the final exam. I'm on the job for about six months now!!!
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COMPSCI 540
Quality 5/5Difficulty 3/5
this is not an easy class and needs a LOT of work. i loved the second half of 540 (after logic). The svm and perceptron stuff is really really good but very mathy. if you already have a 1-2 semesters of calculus you'll do well. Many grad students take this class, so an A may be hard.
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Personal experiences, not a representative survey. Profile matching and captured coverage are shown in the source details.

Classes with Vikas Singh

BMI 699

Independent Study

1–8 credits

Independent Study is a directed course to pursue knowledge beyond the curriculum. Students apply coursework to real biomedical applications and create literature reviews and publications.

Offering recorded · Spring 2027 · Sources

Recent recorded grades — Spring 2022: 4.00 GPA, 100.0% A/AB (n=1 letter grades).

Richard ChappellMark Craven+21 more

No recorded grade history

BMI 899

Pre-dissertator Research

1–12 credits

Pre-dissertator research course for graduate/professional standing students focused on developing critical, analytical, and independent thinking for independent research.

Offering recorded · Spring 2027 · Sources

Richard ChappellMark Craven+28 more

historical GPA · grades

Fall 2025–Spring 2026 · limited sample
BMI 990

Dissertator Research

1–3 credits

Graduate research course for dissertators focused on developing skills to design, implement, and apply computational and statistical frameworks to address diverse biomedical questions.

Offering recorded · Spring 2027 · Sources

Richard ChappellMark Craven+16 more

No recorded grade history

BMI/COMPSCI 767

Computational Methods for Medical Image Analysis

3 credits

Advanced review of medical image analysis techniques, covering segmentation, registration, and the application of statistical and machine learning methods to medical imaging tasks.

Offering recorded · Spring 2027 · Sources

Recent recorded grades — Spring 2013: 3.90 GPA, 100.0% A/AB (n=5 letter grades); Fall 2016: 3.77 GPA, 86.7% A/AB (n=15 letter grades); Spring 2026: 3.64 GPA, 81.8% A/AB (n=11 letter grades).

Vikas Singh

historical GPA · grades

Spring 2026–Spring 2026 · limited sample
COMPSCI 681

Senior Honors Thesis

3 credits

Senior Honors Thesis is an individual study for seniors completing theses for honors in the Computer Sciences major, arranged with a faculty member.

Offering recorded · Spring 2027 · Sources

Fred SalaMing Liu+20 more

No recorded grade history

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 2027BMI 699Independent Study
Spring 2027BMI 899Pre-dissertator Research
Spring 2027BMI 990Dissertator Research
Spring 2027BMI/COMPSCI 767Computational Methods for Medical Image Analysis
Spring 2027COMPSCI 681Senior Honors Thesis
Spring 2027COMPSCI 682Senior Honors Thesis
Spring 2027COMPSCI 699Directed Study
Spring 2027COMPSCI 790Master's Thesis
Spring 2027COMPSCI 799Master's Research
Spring 2027COMPSCI 899Pre-dissertator Research
Spring 2027COMPSCI 990Dissertation
Fall 2026BMI 699Independent Study
Fall 2026BMI 899Pre-dissertator Research
Fall 2026BMI 990Dissertator Research
Fall 2026COMPSCI 681Senior Honors Thesis
Fall 2026COMPSCI 682Senior Honors Thesis
Fall 2026COMPSCI 699Directed Study
Fall 2026COMPSCI 790Master's Thesis
Fall 2026COMPSCI 799Master's Research
Fall 2026COMPSCI 899Pre-dissertator Research
Fall 2026COMPSCI 990Dissertation

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

Instructor identity & provenance 
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