Current instructor
Original student reviews · all captured dates
5-star reviews are coming from top students who stand from their perspectives. If you only took probability, calc3, and linear algebra, and are still a freshman like me, wait for Prof. Sala's section (GOAT). The ability to break down complex theories extremely clearly to the dumb(me) is the true ability. Teaching is an art, and Sala masters it.Rate My Professors ↗
Prof. Zhu will have a 100+ slide presentation for each lecture. However, he reads off the slides and its tough to follow. He also doesn't really respond well on the course Piazza. He is also not professional in terms of meeting his own deadlines. The projects will change them often after they are due. His exams also don't really test material well.Rate My Professors ↗
The material for the class was interesting, but taught in a very lazy way. Dr. Zhu didn't prepare for lectures at all and gave the impression that he didn't care about his students. The regrades on the homework penalized you even if you just made a small, insignificant mistake. The class was poorly taught.Rate My Professors ↗
I respect Dr. Zhu and his career, but his undergrad class is horrible. Lectures are disorganized. Poor designing. The class average was less than 60% for the first midterm. There are basically no resources. There are thousands of pages worth of badly written slideshows that are given, but no one is told which parts of the slides to actually study.Rate My Professors ↗
Prof Zhu is a solid professor, not the best, not the worst. His lectures, while not the most captivating, are worth attending since his examples generally do a better job helping you understand new concepts than his slides alone. He is a very nice guy, but homework instructions were often disorganized, and midterm exam feedback took WEEKS.Rate My Professors ↗
He has a knack for explaining difficult concepts in an accessible way. Even still, you need a solid math foundation to fully understand the algorithms he covers, but having a basic grasp of the algorithms is often all you need for a good grade.Rate My Professors ↗
Personal experiences, not a representative survey. Profile matching and captured coverage are shown in the source details.
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
Individual study for seniors completing theses for honors in the Computer Sciences major, continuing COMP SCI 681.
Offering recorded · Spring 2027 · Sources
No recorded grade history
Directed study projects for Computer Science juniors and seniors, arranged with a faculty member.
Offering recorded · Spring 2027 · Sources
historical GPA · grades
Fall 2022–Spring 2026 · limited sampleGrad st; Master's candidates only
Offering recorded · Spring 2027 · Sources
No recorded grade history
Offering recorded · Spring 2027 · Sources
No recorded grade history
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
Advanced level mentored reading and research for students with dissertator status.
Offering recorded · Spring 2027 · Sources
No recorded grade history
Theoretical Foundations of Machine Learning covers advanced mathematical theory including statistical learning theory, Vapnik-Chevronenkis Theory, model selection, high-dimensional models, nonparametric methods, probabilistic analysis, and.
Offering recorded · Spring 2027 · Sources
historical GPA · grades
Fall 2022–Fall 2025 · limited sampleDistinct courses recorded per term
Explore courses taught by this instructor →| Term | Course | Title |
|---|---|---|
| Spring 2027 | COMPSCI 681 | Senior Honors Thesis |
| Spring 2027 | COMPSCI 682 | Senior Honors Thesis |
| Spring 2027 | COMPSCI 699 | Directed Study |
| Spring 2027 | COMPSCI 790 | Master's Thesis |
| Spring 2027 | COMPSCI 799 | Master's Research |
| Spring 2027 | COMPSCI 899 | Pre-dissertator Research |
| Spring 2027 | COMPSCI 990 | Dissertation |
| Spring 2027 | COMPSCI/ECE/STAT 861 | Theoretical Foundations of Machine Learning |
| Fall 2026 | COMPSCI 681 | Senior Honors Thesis |
| Fall 2026 | COMPSCI 682 | Senior Honors Thesis |
| Fall 2026 | COMPSCI 691 | Senior Thesis |
| Fall 2026 | COMPSCI 692 | Senior Thesis |
| Fall 2026 | COMPSCI 699 | Directed Study |
| Fall 2026 | COMPSCI 790 | Master's Thesis |
| Fall 2026 | COMPSCI 799 | Master's Research |
| Fall 2026 | COMPSCI 899 | Pre-dissertator Research |
| Fall 2026 | COMPSCI 990 | Dissertation |
| Fall 2026 | COMPSCI/ECE 760 | Machine Learning |
Teaching history may be incomplete. Course pages contain course-specific feedback and citations.
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