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Workshop Sun, Apr 26, 2026 • 5:00 AM – 1:00 PM PDT 203 C

AI4MAT-ICLR-2026: ICLR 2026 Workshop on AI for Accelerated Materials Design

Santiago Miret ⋅ Defne Circi ⋅ N. M. Anoop Krishnan ⋅ Emily Jin ⋅ Mohamad Moosavi ⋅ Stefano Martiniani
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Schedule

Timezone: America/Los_Angeles
5:00 AM
Opening Remarks
Santiago Miret ⋅ Defne Circi ⋅ N. M. Anoop Krishnan ⋅ Emily Jin ⋅ Mohamad Moosavi ⋅ Stefano Martiniani
5:50 AM
Coffee Break
6:30 AM
Scientific AI Beyond the Chatbot Era
Swami Sankaranarayanan
7:05 AM
Feedback and Representation Learning for Machine Learning in Materials Science?
Swami Sankaranarayanan ⋅ Pascal Friederich
7:20 AM
Open Materials Generation with Inference-Time Reinforcement Learning
Philipp Höllmer ⋅ Stefano Martiniani
7:35 AM
Discovering Out-of-Distribution Superconductors via Reinforcement Learning and Model Merging
Po-Yen Tung ⋅ David Gunn ⋅ Richard Tomsett ⋅ Jonathon Markanday ⋅ Robert Forrest ⋅ Jonathan Bean
8:05 AM
Poster Session
9:00 AM
Lunch
10:05 AM
Boltzmann Generators for Condensed Matter via Riemannian Flow Matching
Emil Hoffmann ⋅ Leon Klein ⋅ Frank Noe ⋅ Jutta Rogal ⋅ Maximilian SCHEBEK
10:20 AM
Learning Hamiltonian Flow Maps: Mean Flow Consistency for Large-Timestep Molecular Dynamics
Winfried Ripken ⋅ Michael Plainer ⋅ Gregor Lied ⋅ Thorben Frank ⋅ Oliver Unke ⋅ Stefan Chmiela ⋅ Frank Noe ⋅ Klaus R Muller
10:35 AM
Text-Twin-Translation (T$^{3}$): A Full-Stack Machine Learning Framework for Functional Material-Device Systems Discovery
Rui Ding ⋅ Zixin Ding ⋅ Rodrigo Ferreira ⋅ Yuxin Chen ⋅ Junhong Chen
10:50 AM
Diversity-Aware Pretraining in Materials Learning via Task Similarity
Bhanu Mamillapalli ⋅ Mahyar Kochi ⋅ Mohamad Moosavi
11:05 AM
Coffee Break
12:10 PM
NMIRacle: Multi-modal Generative Molecular Elucidation from IR and NMR Spectra
Federico Ottomano ⋅ Yingzhen Li ⋅ Alex Ganose
12:25 PM
Characterizing Microelectronic Devices via Scalable, Confinement-Aware Equivariant Networks
Krishna Bhattaram ⋅ Pratik Brahma ⋅ Sayeef Salahuddin
12:40 PM
Synthesis-constrained molecular design with direct optimization of reaction conditions
Victor Sabanza Gil ⋅ Jeff Guo ⋅ Jeremy Luterbacher ⋅ Philippe Schwaller
12:55 PM
Closing Remarks
Santiago Miret ⋅ Defne Circi ⋅ N. M. Anoop Krishnan ⋅ Emily Jin ⋅ Mohamad Moosavi ⋅ Stefano Martiniani
FragmentFlow: Scalable Transition State Generation for Large Molecules
Ron Shprints ⋅ Peter Holderrieth ⋅ Juno Nam ⋅ Rafael Gomez-Bombarelli ⋅ Tommi Jaakkola
Solvaformer: Unified Geometric Learning for Solubility-Aware Automated Synthesis
Jonathan Broadbent ⋅ Michael Bailey ⋅ Mingxuan Li ⋅ Abhishek Paul ⋅ Louis de Lescure ⋅ Paul Chauvin ⋅ Lorenzo Anele ⋅ Yasser Jangjou ⋅ Sven Jager
Optimizing Materials With CliqueFlowmer
Jakub Kuba ⋅ Benjamin Miller ⋅ Sergey Levine ⋅ Pieter Abbeel
NMIRacle: Multi-modal Generative Molecular Elucidation from IR and NMR Spectra
Federico Ottomano ⋅ Yingzhen Li ⋅ Alex Ganose
Hierarchy-Guided Topology Latent Flow for Molecular Graph Generation
Urvi Awasthi ⋅ Alexander Lobo ⋅ Leonid Zhukov
Feedback-Based Learning of Ground State Properties using Tensor Cross Interpolation
Florian Kiwit ⋅ Bernhard Jobst ⋅ Andre Luckow ⋅ Carlos Riofrío
The Benchmarking Void: A Roadmap for Domain-Adapted Computer Vision in Fuel Cell Defect Detection
Rahul D Ray ⋅ Utkarsh Srivastava ⋅ Rishi Mohapatra ⋅ Naveen Shrivastava
Benchmarking Augmentation Strategies for LLM-Based Solid-State Synthesis Prediction
Thorben Prein ⋅ Elton Pan ⋅ Anass Al ammiri ⋅ Alan Piovesana ⋅ Behsad Riemer ⋅ Elsa Olivetti ⋅ Jennifer Rupp
Sample Efficient Generative Molecular Optimization with Joint Self-Improvement
Serra Korkmaz ⋅ Adam Izdebski ⋅ Jonathan Pirnay ⋅ Rasmus Møller-Larsen ⋅ Michal Kmicikiewicz ⋅ Pankhil Gawade ⋅ Dominik Grimm ⋅ Ewa Szczurek
Towards Intelligent Manufacturing: Spatio-Temporal Learning of Process–Material Dynamics with Attention-Driven Neural Operators
Vispi Karkaria ⋅ Doksoo Lee ⋅ Yi-Ping Chen ⋅ Ying-Kuan Tsai ⋅ Yue Yu ⋅ Wei Chen
Geometry-Aware OOD Generalization for Composite Materials
Abhiroop Bhattacharya ⋅ Hangwei Qian ⋅ Sylvain Cloutier ⋅ Ivor Tsang
Latent Diffusion Pretraining for Crystal Property Prediction
Shrimon Mukherjee ⋅ KISHALAY DAS ⋅ Partha Basuchowdhuri ⋅ Pawan Goyal ⋅ Niloy Ganguly
Context Determines Optimal Architecture in Materials Segmentation
Mingjian Lu ⋅ Pawan Tripathi ⋅ Mark Shteyn ⋅ Debargha Ganguly ⋅ Roger French ⋅ Vipin Chaudhary ⋅ Yinghui Wu
Open Challenges to Unlock Deep Eutectic Solvent Discovery
Anastasia Lavrinenko ⋅ George Puskov ⋅ Rishat Rafikov ⋅ Andrei Dmitrenko
Test-Time Tuned Language Models Enable End-to-end De Novo Molecular Structure Generation from MS/MS Spectra
Laura Mismetti ⋅ Marvin Alberts ⋅ Andreas Krause ⋅ Mara Graziani
Materials Research Agent
Mohd Zaki ⋅ Michael Shields
Accelerating Multi-Property Molecular Design via Entropic-Risk-Based Counterfactual Explanations
Sachindra Pasan Dissanayake ⋅ Po-Yen Chen ⋅ Sanghamitra Dutta
Diversity-Aware Pretraining in Materials Learning via Task Similarity
Bhanu Mamillapalli ⋅ Mahyar Kochi ⋅ Mohamad Moosavi
Molecule property prediction with molecular orbitals
Yan Zhang ⋅ Nhat Khang Ngo ⋅ Sékou-Oumar Kaba ⋅ Daniel Levy ⋅ Siamak Ravanbakhsh ⋅ Aristide Baratin ⋅ Kisoo Kwon ⋅ MiYoung Jang ⋅ Eun Cho ⋅ Sang Ha Park ⋅ Sanghyun Yoo ⋅ Young-Seok Kim ⋅ Hasup Lee
Property-Guided Molecular Generation and Optimization via Latent Flows
Alexander Lobo ⋅ Urvi Awasthi ⋅ Leonid Zhukov
Global Plane Waves From Local Gaussians: Periodic Charge Densities in a Blink
Jonas Elsborg ⋅ Felix Aertebjerg ⋅ Luca Thiede ⋅ Alan Aspuru-Guzik ⋅ Tejs Vegge ⋅ Arghya Bhowmik
Property Prediction of Stacked Bilayer Materials: A Multimodal Learning Approach
An Vuong ⋅ Minh-Hao Van ⋅ Chen Zhao ⋅ Xintao Wu
Framework-Constrained Materials Generation
Maya Martirossyan ⋅ Hillary Pan ⋅ Philipp Höllmer ⋅ Stefano Martiniani
Learning k-Resolved Electronic Structure via Soft Energy Occupancy Prediction
Dongik Park ⋅ Kunmin Jang ⋅ Jaewon Bae ⋅ Dongin Kim ⋅ Chanyoung Park
MatSeek: An Automated Knowledge-Driven Framework for Materials Research
Jianguo Huang ⋅ Yuhao Lu ⋅ Yanchen Deng ⋅ Chendong Zhao ⋅ Penghui Yang ⋅ Zhonghan Zhang ⋅ Yixuan Li ⋅ yushan xiao ⋅ Cuntai Guan ⋅ Bijun Tang ⋅ Xinrun Wang ⋅ Zheng Liu ⋅ Bo An
Enforcing Constraints in Molecular and Crystalline Generative Models via Physics-Constrained Flow Matching
Pengfei Cai ⋅ Utkarsh Utkarsh ⋅ Nofit Segal ⋅ Akshay Subramanian ⋅ ⋅ Elton Pan ⋅ Alan Edelman ⋅ Chris Rackauckas ⋅ Rafael Gomez-Bombarelli
CatAgent: Multi-Agent Orchestration for Electrocatalyst Discovery
Seokhyun Choung ⋅ Hoyun Kim ⋅ Jongheun Kim ⋅ Jeong Han
MSP-LLM: A Unified Large Language Model Framework for Complete Material Synthesis Planning
Heewoong Noh ⋅ Gyoung S. Na ⋅ Namkyeong Lee ⋅ Chanyoung Park
Learning 4D Material-Interface Dynamics From Few X-RAY Projections
Nadav Schneider ⋅ Gershon Hanoch ⋅ Gal Oren
MATRIX: Stress-Testing LLM Reasoning in Materials Science
Junkai Zhang ⋅ Jingru Gan ⋅ Xiaoxuan Wang ⋅ Zian Jia ⋅ Changquan Gu ⋅ Jianpeng Chen ⋅ Yanqiao Zhu ⋅ Mingyu Derek Ma ⋅ Dawei Zhou ⋅ Ling Li ⋅ Wei Wang
From Synthesis to Kinetics: A Data-Driven Deep Learning Framework for Process-Aware Ferroelectric Dynamics
Changhao Wang ⋅ Xinhao Yao ⋅ ⋅ Chaobo Li ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ Riccardo Cantoro
Synthesis-constrained molecular design with direct optimization of reaction conditions
Victor Sabanza Gil ⋅ Jeff Guo ⋅ Jeremy Luterbacher ⋅ Philippe Schwaller
Challenges and Vision For Standardization of Biopolymer Datasets for Machine Learning
Jessica Lalonde ⋅ Defne Circi ⋅ ⋅ Stefan Zauscher ⋅ L. Catherine
AI-Guided Closed-Loop Discovery of Hard Multiple Principal Element Alloys
Maitreyee Priyadarshini ⋅ Eddie gienger ⋅ Jarett Ren ⋅ ⋅ Elizabeth Pogue ⋅ ⋅ ⋅ Paulette Clancy
Learning Hamiltonian Flow Maps: Mean Flow Consistency for Large-Timestep Molecular Dynamics
Winfried Ripken ⋅ Michael Plainer ⋅ Gregor Lied ⋅ Thorben Frank ⋅ Oliver Unke ⋅ Stefan Chmiela ⋅ Frank Noe ⋅ Klaus R Muller
Boltzmann Generators for Condensed Matter via Riemannian Flow Matching
Emil Hoffmann ⋅ Leon Klein ⋅ Frank Noe ⋅ Jutta Rogal ⋅ Maximilian SCHEBEK
A Comparative Study of Molecular Dynamics Approaches for Simulating Ionic Conductivity in Solid Lithium Electrolytes
Dounia Shaaban Kabakibo ⋅ Félix Therrien ⋅ Yoshua Bengio ⋅ Michel Côté ⋅ Hongyu Guo ⋅ Homin Shin ⋅ Alex Hernandez-Garcia
An Orbital-based Geometric Deep Learning Framework for Periodic Materials
Minhyuk Kang ⋅ Beom Kang ⋅ Sergei Kliavinek ⋅ Maurice Hanisch ⋅ ⋅ anima anandkumar
Discovering Out-of-Distribution Superconductors via Reinforcement Learning and Model Merging
Po-Yen Tung ⋅ David Gunn ⋅ Richard Tomsett ⋅ Jonathon Markanday ⋅ Robert Forrest ⋅ Jonathan Bean
Synergistic Multi-Task Learning for Electronic Density of States Prediction
Kunmin Jang ⋅ Dongik Park ⋅ Jaewon Bae ⋅ Chanyoung Park
SynReason: Enhancing Synthesis Reasoning via Reinforcement Learning Experimental Feedback
Elton Pan ⋅ Thorben Prein ⋅ Juno Nam ⋅ Xiaochen Du ⋅ Soojung Yang ⋅ Pengfei Cai ⋅ Jennifer Rupp ⋅ Rafael Gomez-Bombarelli ⋅ Elsa Olivetti
Exploring Transfer Learning for Materials Property Prediction
Bashar Albakri ⋅ Alexander Kiser ⋅ Philipp Benner ⋅ Janine George
Getting the Data Right: A Physics-Consistent, Calibrated Dataset for SEM-Based Defect Localization in PEM Fuel Cells
Rahul D Ray ⋅ Utkarsh Srivastava ⋅ Rishi Mohapatra ⋅ Naveen Shrivastava