These tables summarize the quantitative results in the institutional course evaluation reports currently available to me. They are grouped by course rather than by semester so that the page reflects the development of each course over time.

Qualitative comments are not reproduced here. Some reports combine comments that were eligible for wider circulation with feedback explicitly designated for the instructor, as well as evaluations of course assistants. Keeping those comments out of the public summaries respects the context in which the feedback was provided.

Optimization and Simulation Modeling — Stanford GSB

YearCourseSectionsEvaluation responsesInstruction ratingCourse/content rating
2025–26OIT 248 (Advanced)299/119 (83%)4.45–4.624.05–4.25
2024–25OIT 248 (Advanced)290/112 (80%)4.11–4.403.76–4.04
2023–24OIT 248 (Advanced)281/127 (64%)4.40–4.614.05–4.16
2022–23OIT 245 (Base)398/149 (66%)4.70–4.934.43–4.57
2018–19OIT 248 (Advanced)Not available
2017–18OIT 245 (Base)3118/151 (78%)4.70–4.904.30–4.60
2015–16OIT 245 (Base)398/107 (92%)4.50–4.804.20–4.40
2014–15OIT 247 (Accelerated)382/134 (61%)4.00–4.403.70–4.20
2013–14OIT 245 (Base)5175/210 (83%)4.40–4.604.00–4.40
2011–12OIT 247 (Accelerated)376/113 (67%)3.30–3.803.20–3.40

Scores are on a five-point scale. For years with multiple sections, the two rating columns show the range of the section-level means rather than combining them into a new average. “Course/content” reflects the closest overall course or course-content item in the evaluation instrument used that year.

Doctoral courses — Stanford

YearCourseEvaluation responsesInstruction ratingCourse/content rating
2025–26OIT 676 / CME 307 / MS&E 311, Optimization35/54 (65%)4.434.00
2024–25OIT 676 / CME 307 / MS&E 311, Optimization30/44 (68%)4.103.48
2023–24OIT 655, Foundations of Supply Chain Management2/6 (33%)4.504.00
2014–15OIT 624, Models and Applications of Inventory Management7/7 (100%)4.704.40
2012–13OIT 624, Models and Applications of Inventory Management6/8 (75%)4.204.30

Scores are on a five-point scale. The 2024–25 Optimization course was co-taught; the instruction rating shown here is the one reported specifically for Dan Iancu.

Analytics and AI for Responsible Management — INSEAD

Year and campusEvaluation responsesProfessor effectivenessCourse objectives
2022, Fontainebleau25/32 (78%)4.964.56
2022, Singapore8/10 (80%)4.754.63
2021, Fontainebleau (D)30/42 (71%)4.734.33
2021, Singapore (D)17/21 (81%)4.884.65
2021, Fontainebleau (J)11/15 (73%)4.824.64
2021, Singapore (J)9/11 (82%)4.894.89
2020, Fontainebleau (D)22/31 (71%)4.414.00
2020, Singapore (D)11/12 (92%)4.274.36
2020, Fontainebleau (J2)36/44 (82%)4.814.64
2020, Fontainebleau (J3)21/22 (95%)4.484.43
2019, Fontainebleau15/16 (94%)4.674.67
2019, Singapore28/33 (85%)4.544.54

Scores are on a five-point scale. “Course objectives” reports the item asking whether the course achieved the objectives stated in its outline.

Business Analytics and Management Science — the Wharton School

YearCourseSectionsEvaluation responsesInstructor ratingCourse rating
2016–17OIDD 612, Business Analytics286/115 (75%)3.22–3.703.05–3.58
2016–17OIDD 321, Introduction to Management Science277/81 (95%)3.73–3.793.47–3.73

Wharton scores are on a four-point scale. The rating columns show the range of the two section-level means.

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