Systems nanotechnology: Identification, estimation, and control of nanoscale systems. - Zachary W. Ulissi; Mark C. Molaro; Michael S. Strano; Richard D. Braatz (ACC, 2012)

Control of nano and microchemical systems. - Zachary W. Ulissi; Michael S. Strano; Richard D. Braatz (Comput. Chem. Eng., 2013)

Dynamic Workflows for Routine Materials Discovery in Surface Science. - Kevin Tran; Aini Palizhati; Seoin Back; Zachary W. Ulissi (J. Chem. Inf. Model., 2018)

Toward Predicting Intermetallics Surface Properties with High-Throughput DFT and Convolutional Neural Networks. - Aini Palizhati; Wen Zhong; Kevin Tran; Seoin Back; Zachary W. Ulissi (J. Chem. Inf. Model., 2019)

An Introduction to Electrocatalyst Design using Machine Learning for Renewable Energy Storage. - C. Lawrence Zitnick; Lowik Chanussot; Abhishek Das; Siddharth Goyal; Javier Heras-Domingo; Caleb Ho; Weihua Hu; Thibaut Lavril; Aini Palizhati; Morgane Riviere; Muhammed Shuaibi; Anuroop Sriram; et al. (CoRR, 2020)

The Open Catalyst 2020 (OC20) Dataset and Community Challenges. - Lowik Chanussot; Abhishek Das; Siddharth Goyal; Thibaut Lavril; Muhammed Shuaibi; Morgane Riviere; Kevin Tran; Javier Heras-Domingo; Caleb Ho; Weihua Hu; Aini Palizhati; Anuroop Sriram; et al. (CoRR, 2020)

Methods for comparing uncertainty quantifications for material property predictions. - Kevin Tran; Willie Neiswanger; Junwoong Yoon; Qingyang Zhang; Eric P. Xing; Zachary W. Ulissi (Mach. Learn. Sci. Technol., 2020)

The Open Catalyst Challenge 2021: Competition Report. - Abhishek Das; Muhammed Shuaibi; Aini Palizhati; Siddharth Goyal; Aditya Grover; Adeesh Kolluru; Janice Lan; Ammar Rizvi; Anuroop Sriram; Brandon M. Wood; Devi Parikh; Zachary W. Ulissi; et al. (NeurIPS (Competition and Demos), 2021)

Rotation Invariant Graph Neural Networks using Spin Convolutions. - Muhammed Shuaibi; Adeesh Kolluru; Abhishek Das; Aditya Grover; Anuroop Sriram; Zachary W. Ulissi; C. Lawrence Zitnick (CoRR, 2021)

Enabling robust offline active learning for machine learning potentials using simple physics-based priors. - Muhammed Shuaibi; Saurabh Sivakumar; Rui Qi Chen; Zachary W. Ulissi (Mach. Learn. Sci. Technol., 2021)

Deep reinforcement learning for predicting kinetic pathways to surface reconstruction in a ternary alloy. - Junwoong Yoon; Zhonglin Cao; Rajesh K. Raju; Yuyang Wang 005; Robert Burnley; Andrew J. Gellman; Amir Barati Farimani; Zachary W. Ulissi (Mach. Learn. Sci. Technol., 2021)

Spherical Channels for Modeling Atomic Interactions. - Larry Zitnick; Abhishek Das; Adeesh Kolluru; Janice Lan; Muhammed Shuaibi; Anuroop Sriram; Zachary W. Ulissi; Brandon M. Wood (NeurIPS, 2022)

How Do Graph Networks Generalize to Large and Diverse Molecular Systems? - Johannes Gasteiger; Muhammed Shuaibi; Anuroop Sriram; Stephan Günnemann; Zachary W. Ulissi; C. Lawrence Zitnick; Abhishek Das (CoRR, 2022)

The Open Catalyst 2022 (OC22) Dataset and Challenges for Oxide Electrocatalysis. - Richard Tran; Janice Lan; Muhammed Shuaibi; Siddharth Goyal; Brandon M. Wood; Abhishek Das; Javier Heras-Domingo; Adeesh Kolluru; Ammar Rizvi; Nima Shoghi; Anuroop Sriram; Zachary W. Ulissi; et al. (CoRR, 2022)

AdsorbML: Accelerating Adsorption Energy Calculations with Machine Learning. - Janice Lan; Aini Palizhati; Muhammed Shuaibi; Brandon M. Wood; Brook Wander; Abhishek Das; Matt Uyttendaele; C. Lawrence Zitnick; Zachary W. Ulissi (CoRR, 2022)

GemNet-OC: Developing Graph Neural Networks for Large and Diverse Molecular Simulation Datasets. - Johannes Gasteiger; Muhammed Shuaibi; Anuroop Sriram; Stephan Günnemann; Zachary W. Ulissi; C. Lawrence Zitnick; Abhishek Das (Trans. Mach. Learn. Res., 2022)

FINETUNA: fine-tuning accelerated molecular simulations. - Joseph Musielewicz; Xiaoxiao Wang; Tian Tian; Zachary W. Ulissi (Mach. Learn. Sci. Technol., 2022)

Robust and scalable uncertainty estimation with conformal prediction for machine-learned interatomic potentials. - Yuge Hu; Joseph Musielewicz; Zachary W. Ulissi; Andrew J. Medford (Mach. Learn. Sci. Technol., 2022)

The Open DAC 2023 Dataset and Challenges for Sorbent Discovery in Direct Air Capture. - Anuroop Sriram; Sihoon Choi; Xiaohan Yu; Logan M. Brabson; Abhishek Das; Zachary W. Ulissi; Matt Uyttendaele; Andrew J. Medford; David S. Sholl (CoRR, 2023)

AmpTorch: A Python package for scalable fingerprint-based neural network training on multi-element systems with integrated uncertainty quantification. - Muhammed Shuaibi; Yuge Hu; Xiangyun Lei; Benjamin M. Comer; Matt Adams; Jacob Paras; Rui Qi Chen; Eric Musa; Joseph Musielewicz; Andrew A. Peterson; Andrew J. Medford; Zachary W. Ulissi (J. Open Source Softw., 2023)

WhereWulff: A Semiautonomous Workflow for Systematic Catalyst Surface Reactivity under Reaction Conditions. - Rohan Yuri Sanspeur; Javier Heras-Domingo; John R. Kitchin; Zachary W. Ulissi (J. Chem. Inf. Model., 2023)

Cluster-MLP: An Active Learning Genetic Algorithm Framework for Accelerated Discovery of Global Minimum Configurations of Pure and Alloyed Nanoclusters. - Rajesh K. Raju; Saurabh Sivakumar; Xiaoxiao Wang; Zachary W. Ulissi (J. Chem. Inf. Model., 2023)

Applying Large Graph Neural Networks to Predict Transition Metal Complex Energies Using the tmQM_wB97MV Data Set. - Aaron G. Garrison; Javier Heras-Domingo; John R. Kitchin; Gabriel dos Passos Gomes; Zachary W. Ulissi; Samuel M. Blau (J. Chem. Inf. Model., 2023)

Fine-Tuned Language Models Generate Stable Inorganic Materials as Text. - Nate Gruver; Anuroop Sriram; Andrea Madotto; Andrew Gordon Wilson; C. Lawrence Zitnick; Zachary W. Ulissi (ICLR, 2024)

From Molecules to Materials: Pre-training Large Generalizable Models for Atomic Property Prediction. - Nima Shoghi; Adeesh Kolluru; John R. Kitchin; Zachary W. Ulissi; C. Lawrence Zitnick; Brandon M. Wood (ICLR, 2024)

Adapting OC20-trained EquiformerV2 Models for High-Entropy Materials. - Christian M. Clausen; Jan Rossmeisl; Zachary W. Ulissi (CoRR, 2024)

Open Materials 2024 (OMat24) Inorganic Materials Dataset and Models. - Luis Barroso-Luque; Muhammed Shuaibi; Xiang Fu 005; Brandon M. Wood; Misko Dzamba; Meng Gao; Ammar Rizvi; C. Lawrence Zitnick; Zachary W. Ulissi (CoRR, 2024)

Generalization of graph-based active learning relaxation strategies across materials. - Xiaoxiao Wang; Joseph Musielewicz; Richard Tran; Sudheesh Kumar Ethirajan; Xiaoyan Fu; Hilda Mera; John R. Kitchin; Rachel C. Kurchin; Zachary W. Ulissi (Mach. Learn. Sci. Technol., 2024)

All-atom Diffusion Transformers: Unified generative modelling of molecules and materials. - Chaitanya K. Joshi; Xiang Fu 005; Yi-Lun Liao; Vahe Gharakhanyan; Benjamin Kurt Miller; Anuroop Sriram; Zachary W. Ulissi (CoRR, 2025)

UMA: A Family of Universal Models for Atoms. - Brandon M. Wood; Misko Dzamba; Xiang Fu 005; Meng Gao; Muhammed Shuaibi; Luis Barroso-Luque; Kareem Abdelmaqsoud; Vahe Gharakhanyan; John R. Kitchin; Daniel S. Levine 003; Kyle Michel; Anuroop Sriram; et al. (CoRR, 2025)