AI4X 2027 · Third edition · First in Europe
The AI conference for science and deep-tech applications
AI4X 2027 is coming to Bremen, Germany. Held on the Constructor University campus, it brings together students, researchers, industry, government and thought leaders from around the world to share the latest ideas and research.
- Constructor University Campus, Bremen, Germany
Conference opens in
AI4X 2027 edition
AI4X in numbers
Confirmed speakers
Who you will hear
Invited speaker
Sergei V. Kalinin
University of Tennessee, Knoxville
Sergei V. Kalinin is a Weston Fulton chair professor at the University of Tennessee, Knoxville. In 2022 – 2023, he has been a principal scientist at Amazon (moon shot factory). Before then, he spent 20 years at ORNL where he was corporate fellow and group leader at the Center for Nanophase Materials Sciences. His research focuses on the applications of ML/AI methods in materials synthesis, discovery, and optimization, automated experiment and autonomous imaging and characterization workflows in scanning transmission electron microscopy and scanning probes for physics discovery, atomic fabrication, as well as mesoscopic studies of electrochemical, ferroelectric, and transport phenomena. Sergei has co-authored >700 publications, with a total citation of ~66,000 and an h-index of ~128. He is a fellow of NAI, Academia Europaea, AAAS, RSC, MRS, APS, IoP, IEEE, Foresight Institute, and AVS; a recipient of the Feynmann Prize of Foresight Institute (2022), Blavatnik Award for Physical Sciences (2018), RMS medal for Scanning Probe Microscopy (2015), Burton medal of Microscopy Society of America (2010) and a number of other distinctions.- Links
- Google Scholar
Invited speaker
Yang-Hui He
London Institute for Mathematical Sciences; University of Oxford
Fellow at the London Institute for Mathematical Sciences, Royal Institution; Lecturer in mathematics at Merton College, University of Oxford, Visiting Professor at City St George's, University of London, and Chang-Jiang Chair at Nankai University
Invited speaker
Kristin Persson
University of California, Berkeley
Kristin A. Persson is the Daniel M. Tellep Distinguished Professor at the University of California, Berkeley and a Senior Faculty Scientist at Lawrence Berkeley National Laboratory. She is the Director and founder of the Materials Project (materialsproject.org) which is a world-leading resource for materials data, design and the training of machine learning algorithms. She is an elected member of the Royal Swedish Academy of Science, the US National Academy of Engineering and the American Academy of the Arts and Sciences. She was named an Office of Science Distinguished Scientist Fellow in 2024. She holds several patents in the clean energy space and has co-authored more than 300 peer-reviewed publications.
Invited speaker
Nicola Marzari
EPFL; NCCR MARVEL
Full Professor at École Polytechnique Fédérale de Lausanne and Director of NCCR MARVEL
Invited speaker
Gábor Csányi
University of Cambridge
Gábor Csányi FRS is a Hungarian-born scientist at the University of Cambridge and a Director of the Max Planck Institute for Polymer Research. He read mathematics in Cambridge as an undergraduate at St. John’s College and did his PhD work in physics at MIT. After postdoctoral research in the Cavendish Laboratory, he joined the faculty in the Department of Engineering at Cambridge. He won an F. W. Bessel award from the Alexander von Humboldt foundation. His work is in the field of computational chemistry, and is focused on developing algorithms to predict the properties of materials and molecules from first principles. He pioneered the application of machine learning to molecular modeling which lead to enormous gains in the efficiency of molecular dynamics simulation.
Invited speaker
Gerbrand Ceder
University of California, Berkeley
Professor and Samsung Distinguished Chair in Nanoscience and Nanotechnology Research at the University of California, Berkeley
Invited speaker
Alexandre Tkatchenko
University of Luxembourg
Full professor in Theoretical Condensed Matter Physics at the University of Luxembourg
Invited speaker
Xavier Bresson
National University of Singapore
Xavier Bresson is an Associate Professor in the Department of Computer Science at the National University of Singapore (NUS). His research focuses on Graph Deep Learning, a new framework that combines graph theory and neural networks to tackle complex data domains. In 2017, he received the USD 2M NRF Fellowship, the largest individual grant in Singapore, to develop this new framework. He was also awarded several research grants in the U.S. and Hong Kong. He co-authored one of the most cited works in this domain (10th most cited paper at NeurIPS) and has significantly contributed to mature these emerging techniques. He has organized several conferences, workshops and tutorials on graph deep learning such as the 2022 conference on “Learning on Graphs”, the IPAM'23 workshops on "Learning and Emergence in Molecular Systems", the IPAM'23'21 workshops on "Deep Learning and Combinatorial Optimization", the MLSys'21 workshop on "Graph Neural Networks and Systems", the IPAM'19 and IPAM'18 workshops on "New Deep Learning Techniques", and the NeurIPS'17, CVPR'17 and SIAM'18 tutorials on "Geometric Deep Learning on Graphs and Manifolds". He has been a regular invited speaker at universities and companies to share his work. He has also been a speaker at the NeurIPS'22, KDD'21, AAAI'21 and ICML'20 workshops on "Graph Representation Learning", and the ICLR'20 workshop on "Deep Neural Models and Differential Equations". He has taught undergraduate and graduate courses on Deep Learning and Graph Neural Networks since 2014.
Invited speaker
Yu Xie
Microsoft AI for Science, Berlin
Senior Researcher at Microsoft AI4Science Berlin- Links
- Website
Invited speaker
Valentine P. Ananikov
Lomonosov Moscow State University
Professor, Chemistry Department, Moscow State University; Head of Chemistry Section of Russian Academy of Sciences
Invited speaker
Dong-Ling Deng
Tsinghua University
Tenured Associate Professor at the Institute for Interdisciplinary Information Sciences (IIIS), Tsinghua University
Invited speaker
Artem Oganov
Skolkovo Institute of Science and Technology (Skoltech)
Artem R. Oganov is a crystallographer, chemist, and materials scientist, widely recognized for pioneering the use of artificial intelligence and evolutionary algorithms in the discovery of new materials. He is a Distinguished Professor at the Skolkovo Institute of Science and Technology (Skoltech) in Moscow, where he heads the Material Discovery Laboratory. Since 2026 he is also a Chief Scientific Officer of Sber University. Oganov is the creator of the USPEX (Universal Structure Predictor: Evolutionary Xtallography) method, a revolutionary computational approach that combines evolutionary algorithms with quantum mechanics to predict crystal structures. This breakthrough has fundamentally transformed the field, enabling scientists to predict stable compounds and their properties under extreme conditions such as deep within the Earth or on other planets - before they are synthesized in the laboratory.His research sits at the intersection of computer science, physics, and chemistry. He has made significant contributions to the discovery of novel superconductors, superhard materials, and exotic states of matter. His work has been recognized with numerous prestigious awards, the most recent of which - the International Science and Technology award of China, - was given to him by Chairman Xi Jinping in 2026.
Oganov is actively engaged in popular science activities and is a proud father of 4 children.
- Links
- Website
Invited speaker
Klaus-Robert Müller
Technische Universität Berlin; BIFOLD
Technische Universität Berlin; BIFOLD
Invited speaker
Sergei Gukov
California Institute of Technology (Caltech)
Director, Merkin Center for Pure and Applied Mathematics; Executive Director, American Institute of Mathematics; John D. MacArthur Professor of Theoretical Physics and Mathematics, California Institute of Technology- Links
- Website
Invited speaker
Andrey Ustyuzhanin
Constructor University; I-FIM, National University of Singapore
Constructor University; I-FIM, National University of Singapore- Links
- Website
Invited speaker
Nenad Filipović
University of Kragujevac
Nenad Filipovic is former Director of Science Fund of the Republic Serbia and former Rector of University of Kragujevac, Serbia, full Professor at Faculty of Engineering and Head of Center for Bioengineering at University of Kragujevac, Serbia. He was Research Associate at Harvard School of Public Health in Boston, US. His research interests are in the area of computational mechanics, artificial intelligence, biomedical engineering, cardiovascular disease, fluid-structure interaction, biomechanics, bioinformatics, biomedical image processing, medical informatics, multi-scale modeling, software engineering, parallel computing, computational chemistry and bioprocess modeling. He is author and co-author 11 textbooks and 9 monographies, over 400 publications in peer review journals and over 10 software for modeling with finite element method and discrete methods from fluid mechanics and multiphysics. He also leads a number of national and international projects in EU and US in area of bioengineering, artificial intelligence and software development.
Invited speaker
Stephan Roche
ICREA; Catalan Institute of Nanoscience and Nanotechnology (ICN2)
ICREA; Catalan Institute of Nanoscience and Nanotechnology (ICN2)- Links
- Website
Invited speaker
Sašo Džeroski
Jožef Stefan Institute, Ljubljana
Head of the Department of Knowledge Technologies at the Jožef Stefan Institute (Ljubljana)
Invited speaker
Denis Anikiev
King Fahd University of Petroleum and Minerals
Denis Anikiev is a Research Scientist at the Center for Integrative Petroleum Research of King Fahd University of Petroleum and Minerals (KFUPM), Saudi Arabia, where he leads research and development of physics-based, AI-driven methods for the geosciences and teaches an undergraduate course in computational geophysics. Previously, he worked at the GFZ Helmholtz Centre for Geosciences in Potsdam, Germany, where he specialized in structural geological modeling and physics-based simulation of subsurface processes. Since 2019, he has been leading IGMAS+, a 3D gravity and magnetic modeling platform used by researchers around the world. He also has industry experience in microseismic data analytics and software development. His current research focuses on generative, agentic and explainable AI for seismic imaging and subsurface model building, and on physics-informed deep learning for fiber-optic seismic data processing.
Invited speaker
David Balcells
Hylleraas Centre for Quantum Molecular Sciences, Department of Chemistry, University of Oslo
David Balcells received his PhD in Computational Chemistry from the Autonomous University of Barcelona in 2006. Following research positions at the University of Montpellier and the University of Oslo, where he investigated reaction mechanisms and catalyst design, he established a research program in 2018 focused on the development and application of AI methods for transition metal chemistry. He is the lead author of the tmQM dataset series, a widely used resource for developing and benchmarking AI models for metal complexes. His work combines quantum chemistry and data-driven discovery to accelerate molecular design with both discriminative and generative AI models, including synergies with evolutionary computing. He received the Young Researcher Group Leader Award from the Spanish Royal Society of Chemistry in 2020, and the Ground-Breaking Research Grant from the Norwegian Research Council in 2021. Since 2021, he has led the machine learning section of the Hylleraas Centre of Excellence for Quantum Molecular Sciences at the University of Oslo.
Invited speaker
Christoph Brabec
FAU
Christoph J. Brabec
Professor, Head of Institute of Materials for Electronics and Energy Technology (FAU), Director IMD-3 at (FZJ).
Christoph J. Brabec received his PhD (1995) from Linz University, Austria. After a postdoc period under Serdar Sariciftci and Alan Heeger, he joined the SIEMENS research labs (project leader) in 2001, Konarka in 2004 (CTO), Erlangen University (full professor) in 2009, ZAE Bayern e.V. (scientific director, board member) in 2010, Interdisciplinary Center for Nanostructured Films (spokesman) in 2013, became director at FZ Jülich (IEK-11) in 2018, honorary professor at the University of Groningen as well in 2018 and is heading the Photovoltaic Institute in Jülich (IMD-3) since 2025.
Since 2022 he is the spokesperson of the profile center FAU Solar, since 2023 he is the spokesperson of the Energy Campus Nürnberg, since 2024 a Fellow of the Royal Society of Chemistry and since 2025 a member of the Bavarian Academy of Science.
His research interests include all aspects of solution processing organic, hybrid and inorganics semiconductor devices with a focus on photovoltaics and renewable energy systems, for which he was honoured as “Highly Cited Researcher” for the last years. His most recent research interests are centered around the autonomous discovery of tailored materials with highly automated labs. He has published over 100 patents and a total of more than 1000 articles, about 900 of them peer-reviewed, and received more than 100.000 citations.
Invited speaker
Robert G. Palgrave
EPSRC National XPS Facility; University College London (UCL)
Robert Palgrave studied Chemistry at UCL, before postdoctoral work at Oxford and Liverpool. He rejoined UCL Chemistry in 2012 and is now Head of Inorganic and Materials Chemistry. His research is on experimental materials synthesis and characterisation, focusing on energy materials and structure property relationships. He also works on machine learning approaches to data analysis, and is director of the UK National X-ray Photoelectron Service, HarwellXPS.
Invited speaker
Isao Tanaka
Kyoto University
Isao Tanaka is a Professor at the Kyoto University Institute for Advanced Study, where he is affiliated with the AI for Materials (AI4M) hub. He served as Professor of Materials Science and Engineering at Kyoto University from 2003 to 2025 and directed the Element Strategy Initiative for Structural Materials from 2012 to 2022. In 2008, he received the Philipp Franz von Siebold Award from the President of the Federal Republic of Germany. His research focuses on first-principles calculations, materials informatics, and machine learning for accelerated materials discovery, integrating computational approaches with advanced experimental characterization. He is currently focusing on AI for Materials and serves as the principal investigator of ARiSE, a major Japanese AI for Science (AI4S) research project launched in 2026.
Invited speaker
Giovanni Volpe
University of Gothenburg, Department of Physics
Giovanni Volpe is Professor of Physics at the University of Gothenburg, Sweden, where he leads the Soft Matter Lab. His research lies at the intersection of physics, artificial intelligence, and complex systems, with a particular focus on developing AI-driven methods for scientific discovery. His work spans soft matter, biophysics, active matter, neuroscience, and machine learning, combining fundamental research with the development of computational and experimental tools. He has pioneered deep-learning approaches to microscopy, particle tracking, and the analysis of complex biological systems, with contributions published in leading journals including Nature, Nature Methods, Nature Machine Intelligence, and Nature Communications. He is also the co-founder of AI-based technology startups including IFLAI AB and Valkyray AB, and the lead author of Deep Learning Crash Course (No Starch Press, 2026). His current interests include making AI more accessible, efficient, and reliable as a tool for scientific research. He’s one of the developers of DeepTrack, Deeplay, and KíLín.
Conference topics
Where AI meets the sciences
20+ topics, from particle physics to finance, in one program.
- AI for Physics
- AI for Materials Science
- AI for Particle Physics
- AI for Chemistry
- AI for Math
- ML for Algorithmic Advances
- AI for Biotech
- AI for Medicine and Healthcare
- AI for Climate
- AI for Earth Science
- AI for Space
- AI for Autonomous Navigation
- Self-Driving Labs
- AI for Quantum Technology
- AI for Cybersecurity
- AI Agents and LLMs for Science
- AI for Business
- AI for FinTech
- AI for EdTech
- AI for Society
- Unconventional Computing
- AI for Economics
Two formats
Six days in June
Format 01
Tutorial Weekend
Two days of hands-on workshops on practical, state-of-the-art methods, for students and researchers as well as engineers and R&D teams.
June 12–13, 2027
Saturday and Sunday
Format 02
Conference
Four days of keynotes, invited and contributed talks, poster sessions and networking, bringing together top voices in AI for science across academia, industry and government.
June 14–17, 2027
Monday to Thursday
Venue
Constructor University Campus, Bremen
Meet on Constructor University’s green, tree-shaded 34-hectare campus in Bremen, a former military barracks now home to a research community from over 120 nations, where talks, posters and conversations all happen within a short walk of each other.
Explore Past Editions
2025 · Singapore
AI4X 2025
July 8–11, 2025
500+ participants, 60+ speakers, plus a tutorial day.
2026 · Singapore
AI4X - Accelerate Conference 2026
June 15–19, 2026
800+ participants, 60+ invited speakers.