Kamyar Barakati – Physics of superconductors form image analysis

Maitreyo Biswas – Ensemble-based learning methods for halide perovskite discovery

Safak Callioglu – Inverse Design of Quasicrystals and Complex Nanoparticle Architectures through ML Approaches

Ching-Chien Chen – Discovery of high-pressure phases – integrating high-throughput DFT simulations, graphic neural networks, and active learning

Je Chen – Automated Diffraction Pattern Analysis for Identifying Crystal Systems Using Multiview Opinion Fusion Machine Learning

Migon Choi – Data Driven Analysis of 2D Perovskite Solar Cells

Yigitcan Comlek – Interpretable Multi-Source Materials Data Fusion through Latent Variable Gaussian Process

Rushik Desai – Multi-component, multi-phase Perovskite Database

Vishu Gupta – Structure-Aware Graph Neural Network Based Deep Transfer Learning Framework For Enhanced Predictive Analytics On Diverse Materials Datasets

Ghazal Khalighinejad – Benchmarking LLMs on Extracting Polymer Nanocomposite Samples

Yu Liu – Automated experiment with SPM

Scott McClellan – Semantic Tools for Materials Metadata

Saswat Mishra – Refractory Oxidation Database (RefOxDB): A FAIR Approach to Analyzing Oxidation Kinetics and Enhancing Oxidation Resistance

Aditya Raghavan – Machine Learning Analysis of Cathodoluminescence Data of MZO Thin Films

Md Habibur Rahman – Accelerating Defect Prediction in Semiconductors Using Graph Neural Networks (GNNs)

Jonathan Schmidt – Machine Learning for Materials Discovery

Jiale Shi – Calculating Pairwise Similarity of Polymer Ensembles via Earth Mover’s Distance

Boris Slautin – Multimodal Navigation for Exploring Structure-Property Relationships in Combinatorial Libraries via Multi-Task Bayesian Optimization

Darryl Taylor – Machine Learning Guided Optimization of Hydrogel Composition for Enhanced Metal Intercalation

Vineeth Venugopal – MatKG-2: Unveiling precise material science ontology through autonomous committees of LLMs

William Vittetoe – Automated Experiment on STEM and SPM