Teaching · Spring 2026
AI for Mathematics and Optimization
Bachelor and master seminar · Spring Semester 2026 · ETH Zürich
Course code252-5256-00L
TermSpring 2026
LevelB.Sc. & M.Sc. seminar
Projects9
Overview
This seminar course explores how AI can support research in mathematics and optimization. Students work in small groups on an open research problem, using modern AI tools as tutor, literature assistant, coding assistant, proof critic, formalization assistant and exploration partner.
Course information
- Lecturers
- Prof. Dr. Niao He, Dr. Zebang Shen
- Format
- Group projects on open problems in optimization, each supervised by a member of the group.
- Participants
- 35 students, most of them bachelor (18) or master (17) students without formal optimization training. The seminar tested whether AI support lets such students make research-level progress on open problems within a single semester — something that would ordinarily be unusual.
- Language
- English
Target of the course
- Engage meaningfully with an open research problem in optimization, with AI tools lowering the barrier to the required background.
- Read and reconstruct the relevant literature, and judge which results bear on the problem at hand.
- Use AI assistance critically: as a proof critic and formalization assistant rather than an oracle.
- Report the outcome of the project in a form that another reader can follow and check.