AI in the Sciences and Engineering (2024)

Description

AI is having a profound impact on science by accelerating discoveries across physics, chemistry, biology, and engineering. This course presents a highly topical selection of AI applications across these fields. Emphasis is placed on using AI, particularly deep learning, to understand systems modelled by PDEs, and key scientific machine learning concepts and themes are discussed.

Learning objectives

  • Aware of advanced applications of AI in the sciences and engineering
  • Familiar with the design, implementation, and theory of these algorithms
  • Understand the pros/cons of using AI and deep learning for science
  • Understand key scientific machine learning concepts and themes
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Lecturers

Prof. Dr. Siddhartha Mishra
Full Professor at the Department of Mathematics
Deputy head of Seminar for Applied Mathematics
  • HG G 57.2
  • +41 44 632 75 63

Seminar für Angewandte Mathematik
Rämistrasse 101
8092 Zürich
Switzerland

Prof. Dr.  Siddhartha Mishra
Dr. Benjamin Moseley
Lecturer at the Department of Mathematics
  • OAT X 16

ETH AI Center
Andreasstrasse 5
8092 Zürich
Switzerland

Dr.  Benjamin Moseley

Guest Lecturer

David Graber
Seminar for Applied Mathematics

ETH Zurich
Department of Mathematics
HG G 54.1
Rämistrasse 101
8092 Zurich
Switzerland

Teaching Assistants

Victor Armegioiu
  • HG G 54.1

Seminar für Angewandte Mathematik
Rämistrasse 101
8092 Zürich
Switzerland

Bogdan Raonic
  • OAT X 16

ETH AI Center
Andreasstrasse 5
8092 Zürich
Switzerland

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