AI4Chemistry&Materials

Molecular simulations of perovskites CsXI 3 (X = Pb, Sn) using machine-learning interatomic potentials
Atefe Ebrahimi (SISSA)*

Overcoming Data and Validation Bottlenecks in Machine Learning Workflows for the Accelerated Discovery of Half-Heusler Thermoelectric Materials
Shoeb Athar (Institute Charles Gerhardt Montpellier )*; Adrien Mecibah (Institute Charles Gerhardt Montpellier ); Philippe Jund (Institute Charles Gerhardt Montpellier )

Agentic Active Learning for Materials Discovery with Uncertainty-Gated Surrogate Simulation and First-Principles Labelling
Massimilano Lupo Pasini (Oak Ridge National Lab)*; Zekun Chen (Lawerence Berkeley National Laboratory); Anubhav Jain (Lawrence Berkeley National Laboratory )

End-to-End Uncertainty Quantification for Atomistic Machine Learning
Matthias Kellner (EPFL)*

Machine Learning-Accelerated Discovery of Sustainable Redox-Active Polymers for Next-Generation Batteries
Venkata Sai Subhash Ganti (University of Bayreuth)*

From Hansen Solubility Parameters to Deep Eutectic Solvents: A SMILES Foundation Model for Industrial Formulation Discovery
Eswar Nagireddy (Sasol Chemicals); Florian Kretzschmar (SingularIT); Nikita Dalvi (Sasol Chemicals); Stefan Heyder (SingularIT); Arjan Gelissen (Sasol Chemicals)*; Mattis Hartwig (SingularIT); Allen Kelley (Sasol Chemicals)

Data Quality as the Foundation of AI-Driven Drug Discovery
Uday Abu-Shehab (University of Vienna); Hosein Fooladi (University of Vienna); Steffen Hirte (University of Vienna); Thi Ngoc Lan Vu (University of Vienna); Matthias Welsch (University of Vienna); Johannes Kirchmair (University of Vienna)*

Learning from Loss Landscapes: Stochastic Optimization for Molecular Energies
Jennifer Leclaire (JGU Mainz)*; Andreas Hildebrandt (JGU Mainz)

Reasoning in Chemical Space: Structured Molecular Reasoning Models for Constrained Generation
Christoph Bartmann (Johannes Kepler University Linz); Johannes Schimunek (Johannes Kepler University Linz)*; Sohvi Luukkonen (Johannes Kepler University Linz); Günter Klambauer (Johannes Kepler University Linz)

Robust Mechanism-of-Action Prediction in High-Content Microscopy Images through Test-Time Adaptation and Scaling
Ana Sanchez-Fernandez (LIT AI Lab, Institute for Machine Learning, Johannes Kepler University Linz, Austria)*; Günter Klambauer (LIT AI Lab, Institute for Machine Learning, Johannes Kepler University Linz, Austria)

Four-View Contrastive Learning for Metabolite Identification from Tandem Mass Spectra
Manuel Ruiz Botella (Universitat Rovira i Virgili)*; Marta Sales-Pardo (Universitat Rovira i Virgili); Roger Guimerà (Universitat Rovira i Virgili)

MatSearch: Materials Substructure Search via Late Interaction of Atom-wise Embeddings
Mark Spillman (Cusp.ai)*; Sina Samangooei (Cusp.ai); Sindy Löwe (Cusp.ai); Dario Coscia (Cusp.ai); Thomas Bridge (Cusp.ai); Hannah Openshaw (Cusp.ai); Felix Hanke (Cusp.ai)

Bypassing Aggregation Noise in ChEMBL Using Context-Conditioned Transformers
Michael Backenköhler (Helmholtz HIPS)*; Joschka Groß (Saarland University); Andrea Volkamer (Saarland University)

A (deep) learning jouney from point clouds to proteins
Sofia Imperatore (TU Eindhoven)*

Towards Minimum Energy Pathways with Reinforcement Learning
Jan Felix Kleuker (Leiden University)*; Aleksandra Bobrova (Leiden University); Thor van Heesch (University of Amsterdam); Rik Breebaart (University of Amsterdam); Thomas Moerland (Leiden University)

When Code Does Not Run: Reproducibility Challenges in Materials Machine Learning Benchmarks
Bohui Lyu (KAUST)*; Kangming Li (KAUST)

From Molecular Structure to Formulation-Relevant Properties: A Data-Driven Workflow for Surfactant Design
Arjan Gelissen (Sasol Chemicals)*; Britta Jakobs-Sauter (Sasol Chemicals); Allen Kelley (Sasol Chemicals)

Coverage-Guided Data Pruning for Materials Learning
Ran Zhao (KAUST)*; Kangming Li (KAUST)

From Drop Dynamics to Fluid Properties: An Image-Based Deep Learning Framework
Yassin Riyazi (Max-Planck-Institut for Polymer research)*; Sajjad Shumally (Max-Planck-Institut for Polymer research); Leonard Ries (Max-Planck-Institut for Polymer research); Oleksandra Kukharenko (Max-Planck-Institut for Polymer research); Alice Allen (Max-Planck-Institut for Polymer research); Peter Stephan (TU darmstadt); Hans-Juergen Butt (Max-Planck-Institut for Polymer research); Ruediger Berger (Max-Planck-Institut for Polymer research)

CoCoGraph: A Collaborative Constrained Graph Diffusion Model for the Generation of Realistic Synthetic Molecules in Drug Discovery
Manuel Ruiz Botella (Universitat Rovira i Virgili)*; Marta Sales-Pardo (Universitat Rovira i Virgili); Roger Guimerà (Universitat Rovira i Virgili)

Explaining What Matters: Faithfulness in Molecular Deep Learning
Marcel Hiltscher (TU/e)*; Marc Bianciotto (Sanofi); Francesca Grisoni (TU/e)

Mimosa Framework: Toward Evolving Multi-Agent Systems for Scientific Research
Martin Legrand (CNRS & Université Côte d'Azur & Centre Inria d'Université Côte d'Azur & 3iA Côte d'Azur); Tao Jiang ( CNRS & Université Côte d'Azur & Centre Inria d'Université Côte d'Azur & 3iA Côte d'Azur); Matthieu Féraud ( CNRS & Université Côte d'Azur & Centre Inria d'Université Côte d'Azur & 3iA Côte d'Azur); Benjamin Navet (CNRS & Université Côte d'Azur & Centre Inria d'Université Côte d'Azur & 3iA Côte d'Azur); Yousouf Tagzhouti (CNRS & Université Côte d'Azur & Centre Inria d'Université Côte d'Azur & 3iA Côte d'Azur); Deniz Ertuğrul (CNRS & Université Côte d'Azur & Centre Inria d'Université Côte d'Azur & 3iA Côte d'Azur); Thaiz R. Teixeira (CNRS & Université Côte d'Azur & Centre Inria d'Université Côte d'Azur & 3iA Côte d'Azur); Franck Michel (Inria, Université Côte d’Azur, CNRS, I3S); Fabien Gandon (Inria, Université Côte d’Azur, CNRS, I3S); Elise Dumont (CNRS & Université Côte d'Azur & Centre Inria d'Université Côte d'Azur & 3iA Côte d'Azur); Louis-Félix Nothias ( CNRS & Université Côte d'Azur & Centre Inria d'Université Côte d'Azur & 3iA Côte d'Azur)*

Chemical reaction extraction from chemical schemes: extension to Markush representation
Ulrick Fineddie Randriharimanamizara (ICMUB UBE)*

AI4Humanities&SocialSciences

Generative AI, Literary Studies, and the Plausibility of Interpretations
Tim Lanzendörfer (Goethe University)*

Predicting the Future of Publishing: Multi-Agent Social Simulation as a Methodological Tool for Creative Industries Research
Miriam Johnson (Oxford Brookes University)*

Analyzing Historical Biographies with eXplainable AI
Patrick Brookshire (Akademie der Wissenschaften und der Literatur | Mainz)*

Re-thinking and re-narrating "intelligence" for inclusive AI-futures
Angela Kölling (Mainz University)*

Towards AI generated Philosophy through Autoformalization
Maximilian Noichl (Utrecht University)*

ConflictBench: Benchmarking Scientific Conflict Reasoning for AI-Assisted Research
Islam Mesabah (DFKI)*; Brian Moser (DFKI); Sebastian Vollmer (DFKI)

Generative AI in the Humanities: Theory, Culture, Methodology
Fabio Ciotti (Università di Roma Tor Vergata)*

Interpretability and Explainable AI for the Humanities and Social Sciences: From Plausible Stories to Testable Evidence
Vera Schmitt (Johannes Gutenberg-Universität Mainz)*; Charlott Jakob (TU Berlin); Swarnadeep Bhar (Johannes Gutenberg-Universität Mainz); Raphael Fischer (Johannes Gutenberg-Universität Mainz)

Potentials and Dangers of Using AI for Politics
Charlott Jakob (TU Berlin)*; Raphael Fischer (Johannes Gutenberg-Universität Mainz); Vera Schmitt (Johannes Gutenberg-Universität Mainz)

From Science Fiction to Strategic Foresight
Can-Elliot Sachs (LMU München)*; Linnetq Moxon (THI); Johanna Mauermann (JGU); Markus May (LMU); Jan Oliver Schwarz (THI); Christoph Bläsi (JGU)

Which kind of experts in what loops?
Moritz Schaeffer (Johannes Gutenberg-Universität Mainz)*; Dominik Sobania (Johannes Gutenberg-Universität Mainz); Martin Briesch (Johannes Gutenberg-Universität Mainz); Franz Rothlauf (Johannes Gutenberg-Universität Mainz)

My best was never good enough: failure, bias, and the limits of AI in a large-scale community heritage project
Lorna Hughes (University of Glasgow); Marc Alexander (University of Glasgow)*; Hanna Schmück (University of Augsburg)

AI4LifeSciences

Auditing Sybil: Explaining Deep Lung Cancer Risk Prediction Through Generative Interventional
Attributions Bartłomiej Sobieski (University of Warsaw)*; Jakub Grzywaczewski (Warsaw University of Technology); Karol Dobiczek (Jagiellonian University); Mateusz Wójcik (Warsaw University of Technology); Tomasz Bartczak (Google); Patryk Szatkowski (Medical University of Warsaw); Przemysław Bombiński (Medical University of Warsaw); Matthew Tivnan (Harvard Medical School); Przemysław Biecek (University of Warsaw, Centre for Credible AI Warsaw University of Technology)

Towards Observable Continuous-Time Models for Causal Treatment Effect Estimation in Healthcare
Maik Kschischo (University of Koblenz)*; Jennifer Wendland (University of Koblenz); Nicolas Freitag (University of Koblenz); Philipp Wendland (University of Applied Sciences Koblenz)

Guideline Controlled AI for Clinical Decision Support
Jonas Flechsig (Fraunhofer Institute for Industrial Mathematics)*

EVIDENT: Structuring Computational Trust for AI-Assisted Scientific Software in the Life Sciences
David Teschner (JGU Mainz)*; Thomas Kemmer (JGU Mainz); Maximilian Sprang (Department of Dermatology, University Medical Center of the Johannes Gutenberg University Mainz); Stefan Tenzer (University Medical Center, Johannes Gutenberg University, 55131 Mainz, Germany); Andreas Hildebrandt (Institute of Computer Science, Johannes Gutenberg University, 55128 Mainz, Germany)

Open Tools for More Accessible and Transparent Biologically Informed Deep Learning
David Selby (Deutsches Forschungszentrum für Künstliche Intelligenz)*; Daria Pavliuk (Deutsches Forschungszentrum für Künstliche Intelligenz); Gerrit Grossmann (Deutsches Forschungszentrum für Künstliche Intelligenz); Sebastian Vollmer (Deutsches Forschungszentrum für Künstliche Intelligenz)

Benchmarking agentic solutions for automated immunogenomics data analysis
Oleh Kovalyshyn (Kyiv School of Economics)*; Nadiia Kasianchuk (Kyiv School of Economics); Serghei Mangul (Jagiellonian University)

A Generalized Framework for Designing Complex Assemblies from Modular Components
Soeren Brandt (Sail Biomedicines)*; Usman Mahmood (Sail Biomedicines); Mark Umbarger (Sail Biomedicines)

Securing sequence design: a safety-centric analysis and expert consensus on governance for generative AI in biology
Maximilian Sprang (University Medical Center of The Johannes Gutenberg University Mainz)*

Constructing a Literature-Derived Functional Annotation Layer for Descending Neurons in the Drosophila Connectome
Tokuma Hayashi (Universität Osnabrück)*

Toward an Adaptable Foundation Model for Unified Computational Drug Discovery
Lisa Schneckenreiter (ELLIS Unit Linz, LIT AI Lab, and Institute for Machine Learning, Johannes Kepler University, Linz)*; Sohvi Luukkonen (ELLIS Unit Linz, LIT AI Lab, Institute for Machine Learning, Johannes Kepler University, Linz); Günter Klambauer (ELLIS Unit Linz, LIT AI Lab, Institute for Machine Learning and Clinical Research Institute for Medical Artificial Intelligence, Johannes Kepler University, Linz)

Expanding immune module based classification of inflammatory skin diseases using RNA seq integration and machine learning
Emre Kilic (University Medical Center of the Johannes Gutenberg University Mainz)*; Maximilian Sprang (University Medical Center of the Johannes Gutenberg University Mainz); Johannes U. Mayer (University Medical Center of the Johannes Gutenberg University Mainz)

The SAGE-Immune clock: Determining Sex-Specific Patterns of Immune Cell Aging
Zhilin Zou (University Medical Center of the Johannes Gutenberg-University Mainz); Emre Kilic (University Medical Center of the Johannes Gutenberg-University Mainz); Mihai Netea (Radboud University Nijmegen Medical Centre); Maximilian Sprang (University Medical Center of the Johannes Gutenberg-University Mainz); Johannes Mayer (University Medical Center of the Johannes Gutenberg-University Mainz)*

On the Challenges of Maintaining Hierarchical Knowledge Bases for Clinical Decision Support
Leandro Teixeira Crespo (Institute of Computer Science, Johannes Gutenberg University, Mainz; Institute of Medical Biostatistics, Epidemiology and Informatics (IMBEI), Mainz)*; Daan Apeldoorn (Institute of Medical Biostatistics, Epidemiology and Informatics (IMBEI), Mainz; IU International University of Applied Sciences, Düsseldorf); Felix Schuhknecht (Institute of Computer Science, Johannes Gutenberg University, Mainz); Andre Thevapalan (Institute of Medical Biostatistics, Epidemiology and Informatics (IMBEI), Mainz)

A Novel Neural Network Model To Predict And Enable Prevention Of Honey Bee Colony Collapse
Charles Brum (Stanford Online High School)*

Estimating Demographic Attributes from Skin Lesion Images for Fairness Auditing in Dermatological
AI Arib Yousuf (RPTU Kaiserslautern-Landau); Ko Watanabe (DFKI GmbH)*; Stanislav Frolov (DFKI GmbH); Aya Hassan (RPTU Kaiserslautern-Landau); Adriano Lucieri (DFKI GmbH); Andreas Dengel (DFKI GmbH)

AI4Physics

Adaptive Loss-Balanced Physics-Informed Neural Networks for Solving Parabolic Partial Differential Equations
Haohuan Tan (同济大学)*

Plausible but Wrong: A Case Study on Agentic Failures in Astrophysical Workflows
Shivam Rawat (Univeristy Bonn)*; Lucie Flek (University Bonn)

DINOspec: Efficient Multimodal Alignment of Vision and Spectral Foundation Models for Astronomy
Erica Lastufka (University of Geneva)*

Simulation-Based Fault Injection for AIEngine-Based ML Triggers
Georgios Sotiropoulos (Karlsruhe Institute of Technology)*; Patrick Schwäbig (Rheinische Friedrich-Wilhelms-Universität Bonn); Foivos Paraskevas (Karlsruhe Institute of Technology); Marc Neu (Karlsruhe Institute of Technology); Tanja Harbaum (Karlsruhe Institute of Technology); Klaus Desch (Karlsruhe Institute of Technology); Torben Ferber (Karlsruhe Institute of Technology); Jürgen Becker (Karlsruhe Institute of Technology)

A critical evaluation of Machine Learning Models for Thermodynamic Modeling of High-Entropy Alloys
Bohui Lyu (KAUST)*; Kangming Li (KAUST)

Magnetism for AI and AI for magnetism: from skyrmion reservoirs to group-scale research acceleration
Aditya Kumar (JGU Mainz)*

Physics-Anchored Semigroup Consistency for Stable Long-Horizon Neural Operator Rollouts
Muhammad Waasif Nadeem (RPTU Kaiserslautern-Landau)*; Jephte Abijuru (RPTU Kaiserslautern-Landau); Marius Kloft (RPTU Kaiserslautern-Landau); Sophie Fellenz (RPTU Kaiserslautern-Landau)

Towards an Autonomous AI Steward for Large-Scale Physics Experiments: Integrating Causal Diagnostics, RAG, and Conformal Prediction
Oliver Noll (Helmholtz-Institut Mainz)*; Nicholas Tan Jerome (Institut für Prozessdatenverarbeitung und Elektronik (IPE, KIT))

A Robot Scientist for Drop Friction Measurements
Jannis Brugger (TU Darmstadt)*; Yassin Riyazi (MPI for Polymer Research); Leonard Ries (MPI for Polymer Research); Mira Mezini (TU Darmstadt); Hans-Jürgen Butt (MPI for Polymer Research); Rüdiger Berger (MPI for Polymer Research); Stefan Kramer (JGU Mainz)

Real-time machine-learning analysis of magnetic skyrmions in Kerr microscopy videos
Kilian Leutner (Institute of Physics, Johannes Gutenberg University Mainz, Mainz)*; Yuean Zhou (Institute of Physics, Johannes Gutenberg University Mainz, Mainz); Thomas Brian Winkler (Institute for Molecules and Materials, Radboud University, Nijmegen); Robert Frömter (Institute of Physics, Johannes Gutenberg University Mainz, Mainz); Hans Fangohr (University of Southampton, Southampton); Mathias Kläui (Institute of Physics, Johannes Gutenberg University Mainz, Mainz)

Accelerating physical systems with imagination models
Arindam Saha (Australian National University)*

Element Representations Shape Generalization in Materials Graph Networks
Ran Zhao (KAUST)*; Kangming Li (KAUST)

Learning the NV-Visible Quotient of Equilibrium Quantum Magnetic Noise
EL Mustapha Mansouri (Institute of Science Tokyo)*

Precision autotuning for iterative solvers: An AMG case study
Junhao Chen (Beijing University of Posts and Telecommunications); Qinmeng Zou (Beijing University of Posts and Telecommunications)*

Autofoam: The self-refining autonomous openfoam agent
Aditya a Sesh (quasi ai)*; Arun Govind Neelan (Centre Européen de Recherche et de Formation Avancée en Calcul Scientifique)

QuSafe Resolver: Grid-Validated Neural Safety Envelopes for Robust Qubit Control
EL Mustapha Mansouri (Institute of Science Tokyo)*

Reweighted Hamiltonian Transport for Fixed Wavefunction Sampling in Variational Monte Carlo
Moxian Qian (Johannes Gutenberg University Mainz)*

A Principled Probabilistic Machine Learning Framework for Optical Communication Channels
Sina Seyfadini Kuhbanani (Aston University)*; Felippe Alves (TELUS Digital Research Hub); David Saad (Aston University); Sergei Turitsyn (Aston University)

Physics-Informed Residuals Are Heavy-Tailed: Why MSE Loss Falls Short
Jephte Abijuru (RPTU Kaiserslautern-Landau)*; Nadeem Muhammad Waasif (RPTU University Kaiseslautern-Landau); Sophie Fellenz (RPTU Kaiserslautern-Landau); Marius Kloft (RPTU Kaiserslautern-Landau)

Filter-Cone Certificates for Simulation-to-Reality Transfer in NV-Center Quantum Protocols
EL Mustapha Mansouri (Institute of Science Tokyo)*; Keigo Arai (Institute of Science Tokyo)