The rapidly evolving domain of data-driven science marks a transformative shift across various scientific disciplines, establishing itself as a cornerstone alongside traditional pillars such as experimentation, theoretical analysis, and computation. At the heart of this paradigm shift is Artificial Intelligence (AI), which offers unparalleled opportunities for unveiling the intricate relationships between composition, structure, and the properties or performance of materials. This revolution paves the way for accelerated materials discovery and innovation, propelling the field into a new era of research and development.

     In response to the burgeoning impact of AI on materials science, the International Workshop on Data-Driven Computational and Theoretical Materials Design (DCTMD2024) emerges as a pivotal event to “unlock the AI future of Materials Science”. This workshop is the result of a collaborative effort between Shanghai University (SHU) in China and the NOMAD Lab at the Fritz Haber Institute in Germany. DCTMD2024 is designed to serve as a confluence for leading scientists and researchers specializing in the cutting-edge realm of data-driven AI methodologies and their applications in both computational and experimental materials design.

     The primary objective of DCTMD2024 is to facilitate a comprehensive exchange of the latest research findings and breakthroughs in the field. By congregating a diverse assembly of experts and pioneers, the workshop endeavors to ignite stimulating discussions on the myriad of challenges and burgeoning opportunities within data-driven materials science. It is a forum intended not just for showcasing the current state of the art but also for exploring future directions and fostering collaborative networks among attendees.

     The significance of events like DCTMD2024 cannot be understated. They act as critical catalysts for advancing the frontier of materials research in the AI age, encouraging a synthesis of ideas and methodologies that could lead to the next wave of innovations. Through such collaborative and interdisciplinary exchanges, the workshop aims to chart a course for the future of materials design, one that is increasingly informed by the insights and efficiencies offered by AI and data-driven approaches.

Workshop Chairs of DCTMD2024:

- Matthias Scheffler (Fritz Haber Institute, Germany) 

- Tong-Yi Zhang (Shanghai University, China)

Program Organizers of DCTMD2024:

- Matthias Scheffler (Fritz Haber Institute, Germany) 

- Yi Liu (Shanghai University, China)

- Markus Buehler (Massachusetts Institute of Technology, US)

- Rika Kobayashi (Australian National University, Australia)

Local Organizing Committee of DCTMD2024:

- Jinchang Zhang, Lingyan Feng, Wei Ren, Junyi Ge, Yi Liu, Runhai Ouyang, Quan Qian, Zihan Wang, Jiani Sun (SHU, China）