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252-5256-00L 3 Credits BSC , MSC D-INFK , D-MATH , D-ITET

AI for Mathematics and Optimization

Lecturers & Examiners: Prof. Dr. Niao He, Dr. Zebang Shen
The deadline for deregistering expires at the end of the second week of the semester. Students who are still registered after that date, but do not attend the seminar, will officially fail the seminar.
VVZ CR n/a

Last Updated: 2026-06-03 00:14:14

Abstract

Artificial intelligence (AI) and machine learning (ML) offer significant potential to revolutionize the fundamentals of scientific computation and discovery. In recent years, AI-driven approaches have begun to reshape how we understand, prove, and optimize mathematical systems — from symbolic reasoning and theorem proving to mathematical optimization and numerical analysis.

Objective

The goal of this seminar course is to expose students to the rapidly developing field of AI for Science, with a particular focus on applications in mathematics and optimization. Through readings, discussions, and hands-on projects, students will explore how modern AI tools (e.g., large language models, neural networks, reinforcement learning, and symbolic AI) can assist in mathematical discovery, automate problem solving, and generate new insights into open problems. By the end of the course, each student will complete a research-oriented project that applies AI methods to a mathematical or optimization challenge — for instance verifying proofs, discovering patterns, or accelerating solvers. The seminar aims to develop students’ skills in presenting scientific results, both in written and oral form, and to inspire creative uses of AI in advancing the frontiers of mathematical research.

Resources

Learning Materials (Links)

General Information

Language
English
Levels
BSC , MSC
Frequency
Yearly recurring

Examination

Type
graded semester performance
The students can select one from a collection of papers and present the key idea and algorithm design. Further, they should implement the selected method and demonstrate the correctness of their implementation via empirical evaluations.

Registration & Places

Max Places
40
Priority: Registration for the course unit is until 25.02.2026 only possible for the primary target group

Course Components

Type Title Time & Place Hours
seminar AI for Mathematics and Optimization
Kick-off Meeting: 20 February 2026, 12-14 h, OAT S 15-17 Mid-term presentation session: Saturday, 18 April 2026, 09-16 h, CAB H 52 Final presentation session: Saturday, 23 May 2026, 09-16 h, OAT S 15-17
  • 20.02 Date 12:00-14:00 (OAT S 15)
  • 18.04 Date 09:15-16:00 (CAB H 52)
  • 23.05 Date 09:00-16:00 (OAT S 15)
2 h weekly

Offered In