VVZ API is not affiliated with ETH Zurich. Data might be outdated or incorrect. Please view the official ETHZ Vorlesungsverzeichnis for binding information.

252-5256-00L 2 Credits BSC D-INFK
You're viewing possible stale or outdated data. Please check the latest semester for more up-to-date information.

AI for Science Seminar

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: 2026-02-05 16:38:15

Abstract

Artificial intelligence (AI) and machine learning (ML) offer significant potential to revolutionize the fundamentals of scientific computation and discovery today. The goal of this seminar course is to expose student to the recent development of "AI for Science".

Objective

The aim of this course is to showcase how AI techniques, such as deep learning, can enhance scientific research in the field of Physics. Students will first learn about relevant scientific models, such as key Partial Differential Equations and their associated dynamical systems. They will also explore various AI methods designed to advance traditional approaches. Furthermore, we will guide students through the actual implementation of foundational algorithms, enabling them to address critical scientific issues hands-on.

Content

1. Introduction to related scientific models. 2. AI methods designed to address the scientific problem. 3. Implementation of some fundamental algorithms.

Resources

Literature

The related papers will be released in the first session of the seminar.

General Information

Language
English
Levels
BSC
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
24
Priority: Registration for the course unit is until 28.02.2024 only possible for the primary target group

Course Components

Type Title Time & Place Hours
seminar AI for Science Seminar
Kick-off Meeting: February 21, 2024; 12:15-14:00; CAB G 56 Saturday sessions: May 25 and June 1, 2024, from 08:30 - 13:00, OAT seminar room
  • Wed 12:15-14:00 (CAB G 56)
2 h weekly

Offered In

  • Computer Science Bachelor
    • Seminar (Students may also choose a seminar from the Master's program in Computer Science. It is their responsibility to make sure that they meet the requirements and conditions for this seminar.)