Poster number | Name | Title |
1 | Abhishek Sose | To Be Determined |
2 | Alexander K Landauer | Uncertainty Estimate Mapping for Digital Image Correlation via Convolutional Neural Networks |
3 | Alexandru Bogdan Georgescu | Quantum Materials with Novel Quantum Building Blocks |
4 | Andy Shufer | Identifying the Mental Models of Scientists for the Use of AI in Accelerating Research |
5 | Bahador Bahmani | To Be Determined |
6 | Chowdhury Mohammad Abid Rahman | Supervised Pretraining for Material Property Prediction |
7 | Derek Juba | Uncertainty Quantification for Texture Directionality |
8 | Eva Natinsky | Machine-learning image reconstruction overcomes data scarcity in atomic force microscopy with domain specific image corruption |
9 | Feng Zhang | To Be Determined |
10 | Frank Abel | Developing Methods, Models, and Datasets for a Self-Driving Magnetic Nanomaterials Laboratory: Application for Thermal Magnetic Particle Imaging |
11 | Haochen Yang | Robotic Automation Discovery of Biodegradable Electronics via Multimodal Active Learning and AI-Guided Design |
12 | Jacob Horne | Predicting semicrystalline polymer properties with physics-informed machine learning models |
13 | Jaehyung Lee | SlakoNet DB: A Unified Tight-Binding Database for Electronic Structure and Bandgaps |
14 | John Head | Library of Geopolymer Chemistry & Applications |
15 | Joshua Young | Navigating High Entropy Alloy Compositional Space for Nitrate Reduction to Ammonia with a Universal Machine Learning Potential |
16 | Ju Sun | Accelerating Materials Discovery via Physics-Informed Constraints |
17 | Kai Wagoner-oshima | High-throughput search for topological materials for interconnects using first-principles transport calculations and machine learning |
18 | Katarina Goodge | Supporting rapid, reliable fiber identification |
19 | Katelyn Jones | Using NexusLIMs to Create Benchmark Datasets and Pretrained Microscopy Models |
20 | Lian Xiang | Machine learning-enabled multiplex biosensing using 2D materials |
21 | Ming-Chiang Chang | Evaluating Vision Transformer Architectures for High-Throughput X-Ray Diffraction Analysis |
22 | Mohamed Salem | MetPFN: The Metrological Prior Fitted Network |
23 | Noah Francis | A Two-Scale Finite Element Coupling Using a Machine Learning Accelerated Stochastic Micromechanics Solver for Thermal Conductivity |
24 | Qingjie Li | To Be Determined |
25 | Quinn Gallagher | Improving Machine Learning Extrapolation for Molecular Discovery |
26 | Ricardo Mathison Fuenmayor | A case study in the development of improved promoted Pt catalysts for propane dehydrogenation through Bayesian optimization with uncertainty quantification |
27 | Rosa Diaz Rivas | Building Quantitative Descriptors for Heterogeneous Semiconductor Interfaces |
28 | Sarala Padi | STAMP: Species- and Topic-aware Representation Learning for Antimicrobial Peptide Discovery |
29 | Shuaijun Li | Predicting Properties from Near-Infrared Spectra with Machine Learning for Improved Polyolefin Differentiation |
30 | Snehi Shrestha | Machine Intelligence Accelerated Design of Conductive MXene Aerogels with Programmable Properties |
31 | Wonseok Jeong | Atomistic Dynamics as Sequential Decision-Making: Toward Experiment-Realistic Simulation |
32 | Yuhao Zhong | Uncertainty-Aware Explainable AI for Process-Structure-Property Discovery |
