Time Day 1 Tuesday, June 16 Day 2 Wednesday, June 17 Day 3 Thursday, June 18 Day 4 Friday, June 19
09:00 09:15 Kostya Novoselov & Alán Aspuru-Guzik: Opening Chair: Shi Xuan Leong Eun-Ah Kim: Learning Quantum Matter from Data: Data Centric AI for Scientific Discovery Chair: Yong Tao Tan Vivek Natarajan: General-purpose AI systems from Google DeepMind designed to accelerate scientific discovery and democratize medical expertise Chair: Melodie Christensen Torsten Hoefler: Can we build an AI Climate Scientist? Chair: Simon Billinge
09:15 09:30 Ulrich S. Schubert: Combining online characterization and synthetic robots – On the road to self-driving labs
09:30 09:45 Editors Panel - Scientific Publishing in the AI Era Ray Meng Gao: New Frontiers in Machine Learned Quantum Chemistry Alex Hammer: Beyond the Proof of Concept: Autonomous Electrocatalyst Discovery Within Industrial Constraints
09:45 10:00 Tommaso Dorigo: The second AI revolution in fundamental science Michele Ceriotti: Let them learn: AI models that master materials physics Felix Hanke: Orchestrating the Three-Body Problem of Machine Learning, Simulation, and Experiments in Materials Discovery
10:00 10:15 Ryutaro Uchiyama: AI-Driven Scaffolding of Open-ended Movement Exploration Artem Mishchenko: Why Experimental Data is the Next Frontier for AI x Materials
10:15 10:30 Tejs Vegge: MaterialsCommons for Europe – SDLs and FAIR workflows for federated discovery of advanced materials Truyen Tran: The New Scientific Method: Taste, Truth, and Thinking with AI Qianxiao Li: Learning mesoscopic dynamics
10:30 11:00 Tea Break Sponsored by SEA Garena Tea Break Tea Break Tea Break
11:00 11:30 Curtis Berlinguette: Ada-Carbon: A self-driving laboratory to enable the lowest-cost pathway to scalable $\ce{CO_2}$-to-fuels conversion Chair: Jacqueline Cole Giacomo Indiveri: Bridging natural and artificial intelligence with mixed-signal neuromorphic circuits Chair: Jennifer Dodgson Bartosz Grzybowski: Can robots help us redefine chemical reactions? Chair: Beatrice Soh Jacqueline Cole: Data-Driven Materials Science for Energy-Sustainable Applications Chair: Mohamad Moosavi
11:30 11:45 Maria K. Y. Chan: Seeing the invisible in materials with AI Ngiam Kee Yuan: CASCADE AI - An Agentic AI Variant-to-Disease Mechanism Discovery Adam Gormley: Polymer Biomaterials in a Self-Driving Lab Berend Smit: AI-driven discovery of nanoporous materials
11:45 12:00 Lesley Schultz, Santha Santhakumar (TECAN & Acceleration Consortium): Accelerating Hit Optimization with Automated Parallel Synthesis Aruhan Rui Shi: Macroeconomic Modeling and Forecasting with AI Tools Shyue Ping Ong: Physics, Scaling and Data in Foundation Potentials Steinn Sigurdsson: Surviving the Transition: Doing Science in an Age of AI Accelerated Discovery
12:00 12:15 Break Jun Jiang: Building a Global Infrastructure for AI-Driven Innovation Karsten Reuter: When the Algorithms Take Over: AI for Experiment Planning and Control Break
12:15 12:30 Laura Matz: Unlocking Precision Medicine | The Digital Ecosystem Powering Tomorrow's Therapies Chair: Kostya Novoselov Carlo Vittorio Cannistraci: Brain-inspired sparse network science for next generation efficient and sustainable AI Chair: Gavin Koon
12:30 12:45 Poster Session #1 / Lunch Poster Session #2 / Lunch
12:45 13:00 Maksym Plakhotnyuk, ATLANT 3D: The Autonomous Materials Foundry: The Physical Infrastructure for AI-Driven Materials Discovery with Direct Atomic Layer Processing (DALP®) Technology Tapio Schneider: First Principles, Fast Algorithms: The Physics-AI Synthesis in Earth System Modeling
13:00 13:15 Tan Chorh Chuan: Launch of AI for Science: Accelerating Discovery Through AI AI4X Organizers: 🏆 AI4X Rising Star Awardee Presentation
13:15 14:45 Lunch Sponsored by JEOL Asia Pte Ltd Lunch
Venues Olivia Sophia Moor Morrison Hullet Olivia Sophia Moor Morrison Hullet Olivia Sophia Moor Morrison Hullet Olivia Sophia Moor Morrison Hullet
14:45 15:00 Linh La: A Disorder-Aware Multi-fidelity Framework for Robust Prediction of Superconducting Critical Temperature Chair: Artem Maevskiy Kye Sung Park: Learning Arrow Pushing for Reaction Space Prediction and Exploration Chair: Benjamin Chen Julian Prieto: The Geopolitics of AI Driven Scientific Discovery: Uneven Geographies of Self Driving Laboratories Chair: Kourosh Darvish
15:00 15:15 Shigeru Kobayashi: Development of a benchtop self-driving laboratory for electrocatalyst deposition and evaluation Stephen Dale: High-index saddle dynamics for the automated mapping of reaction routes Mathilde Franckel: Accelerating Ammonia Decomposition Catalyst Discovery with AI Ngoc Duy Dinh: Large Language Model Agents Enable Autonomous Design and Image Analysis of Microwell Microfluidics Andrey Ustyuzhanin: Directing Open-Ended Evolution in Artificial Life via Temporal Multi-Scale Structural Complexity Zhuoying Zhu: Accelerating materials innovation through automated theoretical-experimental iterations empowered by AI-Chemist Martin Seifrid: Toward Generalizable, Data-Efficient Self-Driving Laboratories for Organic Materials Haobo Li: Active Learning Interatomic Potentials-Enhanced Molecular Dynamics for Grain Boundary Engineering in Antiperovskite Solid Electrolytes Alokendra Ghosh: Inferring Oocyte Cytoplasmic Material Properties from Cytoplasmic Streaming Movies Using Physics-Informed Neural Networks Feixiang Ren: Towards Critical Branching Mechanism in Recurrent Neural Networks Yuanchao Hu: Graph learning metallic glass discovery from Wikipedia Christopher Hassam: Add, Mix, Heat, Filter - Repeat, Repeat, Repeat Galymzhan Moldagulov: Hybrid Computational Strategy for Predicting Complex Ligand–Metal Architectures Hongmin Chen: Instructing a Chatbot to Design Nucleic Acid Probes for Diagnostics Sergey Grebenchuk: Machine Learning-Assisted Search for Skyrmion-Hosting Heterostructures for Device Applications Zheng Jie Liew: Learning Nonlinear Dissolution Trajectories in Binary Polymer–Solvent Systems Andy Anker: Autonomous nanoparticle synthesis by design Viktor Schlegel: MIRA: Medical Time Series Foundation Model for Real-World Health Data Maryam Ebrahimiazar: Self Driving Discovery of Immersion Cooling Fluids for Data Center
15:15 15:30 Naruki Yoshikawa: NIMO Controller: An accessible self-driving laboratory orchestrator based on the model context protocol Florian Boser: PlateOpt: Bayesian Optimization for Organic Catalysis in Combinatorial Well Plates Yue Yifei: Towards ab-initio quality description of porous materials: Developing general Machine-Learned Potentials to simulate physical and adsorption properties of Metal-Organic Frameworks Samuel Addington: Neurosymbolic Guardrails for World-Model Digital Twins: Securing AI-Driven Scientific Discovery and Autonomy Maxime Goulet: Self-Driven Process Optimization in Pneumatic 3D Printing: From Static Ensemble Learning to Autonomous Bayesian Method Hirokuni Jintoku: Accelerating Nanocarbon Dispersion Research via Machine Learning and Automated Experimentation Timothy McClure: An Integrated Platform for In Situ Electroanalytical–Driven Reaction Optimization Autonomous Discovery of High-performance Ni–Mo Electrocatalysts for Green Hydrogen Production Zhen Yuan Yeo: Inferring the hidden and long-range dengue transmission routes in Singapore Ling Feng: Order-chaos transition in deep neural network and its application to the training process Jingbei Bai: Machine learning reveals transferable rules for predicting grain boundary segregation Hugo Kvanta: A Self-Driving Lab for Novel Energy Material Discovery Victor Posligua: Predictive mass spectrometry from quantum-mechanical fragmentation and intensity modelling Wanyu Lin; Haowei Hua: Local-Global Associative Frames for Symmetry-Preserving Crystal Structure Modeling Juntao Yang: From Global to Local: AI-based Climate Downscaling for Southeast Asia Mathilde Franckel: High-throughput ML Screening of Doped Cathode Active Materials Andy Paul Chen: Atomic Sudoku: Stochastic approaches for correlated disorder materials Muye Xiao: Kinetic study of the aqueous Kolbe-Schmitt reaction enabled by automated reaction analysis Lyubomir Kotopanov: From In Silico Design to Automated Synthesis: An AI-Driven Framework for Late-Stage Functionalization Syed Momin Naqvi: Defending Federated Learning: Adaptive Integration of Differential Privacy, SMPC, and Byzantine Robustness
15:30 15:45 Calvin Phan: AutoMEA - an automated electrolyser device for self-driving labs Xiao Li: A Self-Driving Closed-Loop Workflow for Data-Efficient Kinetic Modeling and Op-timization of the Aldol Reaction Ivan Kruglov; Liudmila Klimova: Diffusion-Driven Generation of Novel Crystalline Materials with Target Optical Properties Yitian Huang: How Prompt Structural Framing and Cognitive Scaffolding Influence Performance in Generative AI Design? Paola Driza: A Framework for Bayesian Optimization in Mixture Spaces Kensei Terashima: Automated Bulk Intermetallic Synthesis via Orchestrated Heterogeneous Laboratory Machines Jeongwook Lim: Designing of Microfluidic Concentration Generator Module for Self-Driving Fluid Mixing System Qi Jie Yeow: Large Language Model Assisted Optimisation of Photocatalytic Hydrogen Production Giacomo Indiveri: Event driven neural network on a mixed signal neuromorphic processor for detecting EEG based epileptic seizure Mengyi Chen: Scalable learning of macroscopic stochastic dynamics Guangcun Shan: Atomic-Level Interpretable Multimodal Graph Neural Network for Predicting Carbon Capture in Metal-Organic Frameworks Tim Kodalle: Combining robotic deposition tools and advanced characterization to enable ML-guided material discovery Maik Gabriel Niedziella: ReactionEye: Integrating GC–MS Data and Chemical Context for Multimodal Structure Elucidation in Reaction Screening Yoshinori Hayakawa: Bridging LLM-based planning and workflow languages for automated, validated, scalable exploration of scRNA-seq analyses George Turkiyyah: Synthetic Geology: Structural Geology Meets Deep Learning Xiangwen Wang: Discovery of flat-band 2D materials via physics-informed scoring and structure-based learning Zhenzhu Li: Platonic representation of foundation machine learning interatomic potentials Yuanyuan Zhou: Deciphering the operando mechanism of Haber-Bosch process Theo Tait: Agentic AI–Enabled Integration of a Hybrid System of Predictive Models for Accelerated Direct‑Compression Drug Product Development Minh Tri Nguyen: The Economy of Reasoning: Incentivizing Epistemic Diversity in Decentralized Scientific Swarms
15:45 16:00 Han Hao: Integrating Multimodal Knowledge Mining and Autonomous Experimentation for Accelerated Electrosynthesis Discovery Chen Jie: A systematic effort toward establishing an automatic end-to-end synthesis workflow for small molecules Alastair Price: Atom-in-molecule based quantum machine learning of defect formation energies Mengjia Zhu: Can We Automate Scientific Reasoning in Closed-Loop Experiments using Large Language Models? Hongbin Zhang: Bayesian Optimization for the Inverse Problems in Materials Science Kazunori Nishio: Exploration of Ternary Thin-Film Lithium Solid Electrolyte Composites Using the Digital Laboratory for Enhanced Lithium-Ion Conductivity Owen Melville: Resource-efficient Bayesian optimization for self-calibrating liquid handling Yonatan Kurniawan: A reinforcement learning approach to generate equivalent circuit models for Electrochemical Impedance Spectroscopy Poorva Pandya: Conceptualising Case Formulation as a Neurosymbolic AI Framework for Mental Health Zhuoyuan Li: Learning non-equilibrium mesoscopic dynamics with Onsager principle Adrien Goldszal: Discovery of Sustainable Refrigerants through Physics-Informed RL Fine-Tuning of Sequence Models Linden Schrecker: Printing kinetic data and microkinetic models in an automated lab Alexander Ryabov: Towards Data-Driven Nonlocal Density Functionals: Deep Learning DFT with Attention to approach Chemical Accuracy yuxuan Ren: From Molecules to Materials and Proteins: Flow Autoencoders as Lossless and Unified Tokenizers Nguyen Minh: Physics-informed Deep Operator Networks for Real-Time Spatiotemporal Monitoring of Indoor Air Quality Liudmila Klimova: Materials informatics framework for accelerated discovery of high-refractive-index 2D materials Litong Wu: The Zintl–Klemm Concept in the Amorphous State: A Case Study of Na–P Battery Anodes Zhengzuo Liu: A Data-driven Closed-looped High-throughput Platform for Thermocatalyst Discovery Sven Papidocha: From Model to Molecule: Rapid Discovery of Potent CDK2 Inhibitors Using Boltz-2 Dean Thomas: Securing Autonomous Chemical Robots Through Physical and Digital Containment
16:00 16:15 Ivory Wenyu Zhang: IvoryOS: An Interoperable Platform and Community for Self-Driving Laboratories Wendi Cai: Automation and AI-Powered Prediction in Chromatographic Separation Patrick Butler: AI-guided experimental design of zirconium MOPs with The World Avatar for sustainable photocatalysis Yu Chinen: Evolving collaborative research ideas with multi-agent grounding in lab-specific contexts and literature Yuki Takezawa: Meta Bayesian Optimization to Discover a Problem Worth Optimizing Haiwen Dai: Closed Loop Inorganic Material Discovery with Design-Test-Make-Analyze Paradigm David Scott Lewis: ACHT-World: Causal World Models for Closed-Loop Self-Driving Laboratories Yicheng Chen: Benchmarking Foundation Potentials against Quantum Chemistry Methods for Predicting Molecular Redox Potentials Malik Saif: The Cognitive Clinical OS: Architecting Asynchronous Agentic Reasoning for Real-Time Decision Support Zhichao Han: Learning Permutation-invariant Macroscopic Dynamics Shuya Yamazaki: CSX Framework for Synthesis-Oriented Generative Materials Discovery Maria Politi: An End-to-end, Autonomous Platform for Liquid-liquid Extraction Optimization Ekaterina Skorb: Nanostructured Material Design via a Retrieval-Augmented Generation (RAG) Approach: Bridging Laboratory Practice and Scientific Literature Junhan Wang: Latent World Models of Cell Painting Data for In Silico Phenotypic Screening Huixuan Sun: AI-Enabled 3D Glare Assessment Framework for Urban Solar Planning Yihao Wei: Beyond Known Archetypes: A Generative AI Framework for Inverse Design of Flat-Band Materials from Geometric Outliers Martin Hoffmann Petersen: Importance of Electronic Entropy for Machine Learning Interatomic Potentials Ailsa Edward: Development of a Platform for Sustainable Metal-Organic Framework (MOF) Synthesis, MABIL: MOF Automation using Biomass-Inspired Linkers Daniel Yanes: A machine learning workflow to accelerate the design of in vitro release tests from liposomes David T T Tran; Ernest E Y Chan: Edge-AI Driven Automation for Scalable E-Waste Recycling
16:15 16:45 Tea Break Tea Break Tea Break Tea Break
Venues Olivia Sophia Moor Morrison Hullet Olivia Sophia Moor Morrison Hullet Olivia Sophia Moor Morrison Hullet Olivia Sophia Moor Morrison Hullet
16:45 17:00 Stuart Miller: Building a Decision-Driven Materials Discovery Institute: Early Insights from MDRI Chair: Santiago Miret Yijun Li: AFPFusionLM: A Hybrid Sequence–Structure Protein Language Model for Antifreeze Protein Function Prediction Chair: Yongcun Song
17:00 17:15 Sergei Tatarin: Towards accelerating the discovery of efficient iridium(III) emitters using a novel database and machine learning based only on structural formulas Sanna Jarl: Machine learning for in-situ composition mapping in a self-driving magnetron sputtering system Marcel Mueller: La Agente Optima – orchestrated Bayesian optimization and active learning for accelerated in-silico compound discovery Fengxu Yang: A Universal Autonomous Agent for Atomistic Simulation and Benchmarking Its Capabilities Abdul Kadir: A Three-Level Feature Selection Framework for Android Malware Detection Hangwei Qian: A Multimodal Conditional JEPA for Composite Materials Yuuya Nagata: Closed-loop Optimization of Mono-functionalization via Suzuki-Miyaura Reaction Santhosh Sivasubramani: LLM-Powered Autonomous Agents for Spintronic Device Optimization: From Rule-Based to AI-Driven Design Yueming Lyu: NeCLO: Neural Convolutional Learning Optimizer for Electromagnetics Honghao Chen: CatMaster: An Agentic Autonomous System for Computational Heterogeneous Catalysis Research Kiran Vaddi: Beyond Point Sampling: Autonomous Phase Mapping of Biologic Formulation Stability via Hierarchical and Manifold Active Learning Jiangjie Qiu: AdsorbFlow: energy-conditioned flow matching enables fast and realistic adsorbate placement Shuan Chen: SynTwins: A Retrosynthesis-Guided Framework for Synthesizable Molecular Analog Generation Martin Hoffmann Petersen: 🏆 Best Poster: Computational Investigation and Generation of Site-Disordered Sodium Ion Cathode Materials Yang Choo: A Standard Physical Environment for Benchmarking AI-driven Cell Biology Ryo Akiba: Multi-objective optimization for designing structurally similar proteins with dissimilar sequences Qixiang Zhang: PieLoT — LLM-driven Toolbox for Theorem Proving Education Tanja Duric: $2k_F$ instability and chiral spin density wave at the 1/9 magnetization plateau in the kagome antiferromagnets
17:15 17:30 Lulu Wang: Data-scarce synthesis-by-design of ferroelectric Dion–Jacobson 2D hybrid organic–inorganic perovskites Matthew Osvaldo: When is Bayesian Optimization Beneficial? A Critical Assessment of Optimization Strategies in High-Throughput Organic Photovoltaic Manufacturing Jiaru Bai: El Agente Gráfico: Structured Execution Graph for Scientific Agents Ioana Zelko: DarkMatterFM: An Agentic Foundation Model for Multimodal Dark-Matter Inference with GPU-Accelerated Emulators Leonardo Pesce: Exiaa: Explainable Injections for Adversarial Attack Bo Hu: Test-Time Self-Evolution in Multi-Agent Systems for Materials Discovery Nicholas Warren: Flow Chemistry as a Platform for Experimental Multi-objective Optimization of Heterogeneous Polymer Synthesis Jiadong Dan: Symmetry-Aware Deep Learning for Generalizable STEM Phase Classification Santhosh Sivasubramani: Design Methodologies for Skyrmion-Based Circuits and Systems in AI-Driven Applications: Bi-Directional Integration Chun-Sung Jao: AI for Plasma Diagnostics in Laboratory Astrophysics: Reconstructing Invisible Fields from Proton Images Dorye Luis Esteras: Exploration and simulation of emergent magnetic materials via AI-driven workflows Shun Muroga: Self-Driving Labs for Nanomaterials Development for Energy Applications: Syn-thesis, Dispersion, and Composite Forming Jiaqi Zheng, SEA Garena: Toward GPU-Native Electronic Structure Calculations Jan Christopher Spies: Yield Prediction of Organic Reactions in Biased Datasets via Positive-Unlabeled Learning Nikita Kazeev: LeMat-GenBench: A Unified Evaluation Framework for Crystal Generative Models Tong Xie: MiST: Understanding the Role of Mid-Stage Scientific Training in Developing Chemical Reasoning Models Fushuai Wang: End-to-end neural reconstruction of DNA structures from single-frame fluorescence images Viktor Schlegel: BRIDGE: Bootstrapping Text to Control Time-Series Generation via Multi-Agent Iterative Optimization and Diffusion Modeling Xianquan Yan: HSG-12M: A Large-Scale Benchmark of Spatial Multigraphs from the Energy Spectra of Non-Hermitian Crystals
17:30 17:45 SWITCH: SWITCH (EnterpriseSG) Talk Fanjin Wang: Constrained composite Bayesian optimisation for rational synthesis of polymeric particles Shruti Badhwar: SciAgent: Containerized Code Generation for Scientific Computing with Verification Zonglin Yang: MOOSE-Chem2: Exploring LLM Limits in Fine-Grained Scientific Hypothesis Discovery via Hierarchical Search Qian Yang: MultiTaskDeltaNet: Change Detection-based Image Segmentation for operando ETEM with Application to Carbon Gasification Kinetics Ben Rowlinson: Data-Driven Property Prediction for Memristor Resistive Switching Layers Ryo Tamura: NIMO: Universal Middleware for Closed-Loop Materials Exploration Reena Shadaan: Ethical Nail Salons: A community-governed and SDL-facilitated approach to mitigate occupational chemical hazards in nail salons Yue Yifei: Mapping diverse structures of liquid water and ice using variational autoencoders: A vector quantization approach to discover structural motifs in model latent spaces Santhosh Sivasubramani: Ultra-low-energy skyrmion-based learning automata element for adaptive edge intelligence Nagendra Nagaraja, QpiAI India: Quantum AI Jaehwan Choi: Materealize: a multi-agent deliberation system for end-to-end material design and synthesis Udo Bach: An Autonomous Discovery Platform for Inorganic Photovoltaic Absorbers Beyond Lead Halide Perovskites Ultrafast Spectroscopy Meets Data-Driven Materials Discovery at the Institut Courtois, Université de Montréal Balamurugan Ramalingam: Generative Design and Experimental Validation of Non-Fullerene Acceptors for Photovoltaics Manuel Kober-Czerny: Using Time-Series Forecasting to Accelerate Materials Stability Assessments Sayan Doloi: Democratizing Discovery: Ultra-Low-Cost Self-Driving Laboratories for Materials Science Poompol Buathong: Better Protein Function Prediction by Modeling Survivorship Bias Linus Ng: Beyond Semantic Similarity: A Two-Phase Non-Parametric Retrieval Workflow for Corporate Credit Underwriting Zekun Shi, SEA Garena: Flow-Distorted Plane Waves
17:45 18:00 Emha Bayu Miftahullatif: High-Throughput In-Device Screening of Printable Lead-Free Halide Perovskite Memristors via Machine Learning-Driven Optimization Lars Sonneveld: Autonomous Optimization of Perovskite Solar Cell Thin Films via Robotic Spin-Coating and Bayesian Optimization Zijian Zhang: El Agente Forjador: Task-Driven Agent Generation for Quantum Simulation Jingyu Feng: DIGIBAT: Bridging the gap between physical automation and AI in energy research Bohui lyu: Code and Data are not all you need for reproducibility Atish Dixit: EMOS: The Unified AI Platform for Electronic Materials Discovery MCP-Enabled LLM Agents for Closed-Loop Optimization in Real-Time Physical Experiments Eric J. W. Orlowski: AI & Culture Alignment: Interpretation over Measurement Qianshu Ye: VLM4Physics: Equation Discovery Using Multi-modal Inputs Jianlong Lu: Spectrum-Aware Quantum Control beyond Classical Spectral Access Subhajit Dandapat: Transformers with Physics-informed encodings and Simulation-Based inference for robust Gravitational-Wave detection in Pulsar Timing Array data Yizhe Chen: SemiMat: A Semi-Supervised Toolkit for Data-Scarce Materials Property Prediction Holger RöHM: E-MAP – A Self Driving Lab for Solution Based Combinatorial Semiconductor Discovery Nitish Govindarajan: The Open Catalyst 2025 (OC25) Dataset and Models for Solid-Liquid Interfaces Amirreza Mottafegh: Adaptive Human-in-the-Loop Optimization Using Language-Guided Priors for Chemical Synthesis Ivan Trofimov: Symmetry‐Aware Equivariant Network for Discovering SHG‐Active Materials Shreyas Pethe: Automated High Throughput Optimization for Halide Perovskite Memristors Michal Kobiela: Risk-averse optimization of genetic circuits under uncertainty Thi Ngoc Nguyen: ESS-MOTIFS: Discovering Rubric-Aligned Motifs for Cohort-Level Essay Assessment Jonas Elsborg: Global Plane Waves From Local Gaussians: Periodic Charge Densities in a Blink