Perspectives in Data-Driven Materials Design

From Machine Learning to Autonomous Labs

August 25 – 29, 2025
an International Summer School
organized by the
D³ Research Training Group 2868, the Dresden Center for Computational Materials Science (DCMS) and the Dresden Center for Intelligent Materials (DCIM).


Data science and machine learning have deeply affected the field of material science. The upcoming of data-driven methods redefined both objectives and tasks and lead to the development of utterly new methods. This summer school offer comprehensive, multidisciplinary insights into these new developments, extending from machine learning to experimental characterization, including alloy design and mechanistic modeling. Internationally renowned speakers will share their perspectives in a 5-day workshop in the spectrum of data-driven design of materials and structures. The lectures will be extended by hands-on sessions to achieve a greater understanding of the latest scientifical developments.
To foster interaction between participants, experts and D³ fellows, the school is complemented by a social program.
The Summer School is organized by fellows of the Research Training Group 2868 D³ - Data-Driven Design of resilient metamaterials together with the Dresden Center for Materials Science (DCMS) and the Dresden Center for Intelligent Materials (DCIM). It is scheduled for August 25 – 29, 2025. Venue is TUD University of Technology Dresden

  • Structural Optimization
  • Architected Materials
  • Inverse Material Design
  • Material Manufacturing
  • Alloy Design
  • Multiscale Modeling
  • Phase Diagrams
  • Machine Learning
  • Experimental Characterization
  • Computational Mechanics
  • Computational Material Science
  • Model Discovery and Parametrization
Credits: Jiuguang Wang ( CC BY-SA 2.0 )

Confirmed Lecturers

Professor Mohr is conducting extensive research on the design and manufacturing of novel architected materials via the development of experimentally-validated computational models. More specifically, this includes the study of the thermo-mechanical behaviour of materials at high strain rates, crashworthiness as well as the mechanics of constructed cellular materials. Having obtained his P.h.D from the Massachusetts Institute of Technology, he had the opportunity to conduct research at the École Polytechnique as well as at MIT. He is currently full professor at ETH Zürich and head of the Institute of Virtual Manufacturing.

ETH

ETH

Professor Bessa is leading a research group for the development of artificial intelligence-based methods to design novel materials and structures with innovative properties This includes multi-scale modeling of material as well as material optimization via physics-informed machine learning. He achieved his PhD in Northwestern University and pursued his research with a short postdoctoral position at Caltech as well as a position at TU Delft. He is now an associate professor at Brown University focusing on computational mechanics and machine learning.

Professor Leineweber is known for his work on various aspects of solid-solid phase transformations, especially in the case of steel/cast iron as well as various types of intermetallics. He is currently full professor at the TUB Freiberg, where he heads the group "Applied Materials Science" at the Institute of Material Science.

Professor Kästner is focusing on the development of data-driven analysis and techniques for material multi-scale modeling along with the experimental characterization of additively manufactured materials. His research interests encompass a large scope of subjects, from inverse material design to damage and fracture analysis. He is a full professor at the TU Dresden where he received his PhD in 2015. Among his projects belongs the research training group D³ on data-driven design of metamaterials aiming to develop novel resilient materials.

The research training group D³ - Data-Driven design of metamaterials - is aiming to the exploration of novel cross-scale materials and structures achieving enhanced mechanical performances. This challenge is tackled by an interdisciplinary team involving experts in computational mechanics, data and computer science, materials science, mechanical engineering, mathematics, and physics. To achieve its objectives, the D³ adresses various challenges, from the structure optimization to the functionalization, including the alloy design and the mechanical testing.

Programme


Perspectives in Data-Driven Materials Design is first of all a school. Its aim is to teach 5 days long the novel concepts and methods uprising in material science to a large public of master and PhD students. We consequently believe that it should have a programme proper to a school and not to a conference, allowing a real grasp of the topics beyond a simple overview.

The summer school will be organized around 5 main courses presented by internationally renowned scientists and covering various disciplines of material science. Each course will be decomposed into two lectures, offering both an introduction as well as advanced considerations of each topic. These two lectures can be expanded by a hands-on session to develop a concrete understanding of the concepts. Besides these courses, one-shot lectures will propose novel and broader insight into the current research.

We do strongly believe that a summer school is not only a place to learn, but also a place to meet other scientists. After mutually meeting each other during the poster session, we offer numerous social events, including a visit of the Dresden city, to get in touch with new persons and expand your professional and personal contacts.

The following timetable is provisional and is subject to changes. The final program will be uploaded soon.

Application


Applications will be accepted until Monday, May 19 2025, at 10 am (CET). The Summer School targets master students and PhD students working on or interested in computational mechanics and materials science as well as topics related to synthesis, novel fabrication methods and experimental high-throughput methods. To apply for the school, the following documents are needed and have to be uploaded as a PDF in the online form (see below).

The participants will be selected from the applications as soon as the application period ends and be informed about the decision shortly afterwards. A limited number scholarships, i.e. travel awards, will be awarded for the best applications.
 

APPLY NOW

Important for applicants who need a visa to travel to Germany:
  • Please check as soon as possible the visa regulations to visit Germany.
  • Contact the office responsible for issuing visas to enter Germany (embassy, consulate, agency) near your place of residence as soon as possible and find out about waiting times and the duration of visa preparation.
  • Invitation letters will be sent out during the second half of June.

Venue

The summer school will take place
at the Görges Bau on the TU Dresden main campus.

Suggestions for accommodation:

Scientific Board/Organizers

Organizing Board

Acknowledgements


This Summer School is co-funded by the Federal Ministry of Education and Research (BMBF) and the Free State of Saxony as part of the Excellence Strategy of the federal and state governments. The DRESDEN-concept Science and Innovation Campus measure supports, among other things, summer schools in order to strengthen the cooperation of the implementing institutions, to bundle their research expertise, especially in interdisciplinary topics, and thus to further increase the attractiveness of the location for (inter)national students and postdocs.