Publications

A more complete list can be found on Google Scholar.

Peer-reviewed articles and accepted papers

• Hadler, N.; Rinehart, N. I.; Elkin, M.; Nicolai, J.; Gheibi, G.; Chen, J.; Avaylon, M.; Maciejewski, R.; Weber, G. H.; Mahoney, M. W.; Perciano, T.; Hartwig, J. F. 3D, Structure-Based, Deep Learning Approach to Predict the Regioselectivity of Olefin Hydroformylations. JACS, 2026, 148 (34), 37167–37179.

  

• Liu, S.; Chen, J.; Hadler, N.; Hnatyshyn, R.; Mahoney, M. W.; Perciano, T.; Hartwig, J. F.; Weber, G. H.; Maciejewski, R. LatentFlow: Visual Analytics for Latent Space Analysis in Molecular Graph Neural Networks. IEEE VIS, 2026 (accepted). Manuscript: arXiv:2607.21941 (v1).

  

• Hadler, N.; Ramirez, E.; Avaylon, M.; Elkin, M.; Rinehart, N. I.; Mahoney, M. W.; Weber, G. H.; Hoche, J.; Brandenburg, J. G.; Perciano, T.; Hartwig, J. F. Predicting Enantioselectivity of Ruthenium-Catalyzed Ketone Hydrogenation with 3D Structure-Based Deep Learning. JACS, 2026, 148 (30), 31627–31633.

  

• Lambert, W. D.*; Felten, S.*; Hadler, N.; Rinehart, N. I.; Swiatowiec, R.; Storer, G. E.; Henle, J.; Servos, M. A.; Yang, C.; Bay, A. V.; Eyimegwu, P. N.; Shekhar, S.; Hartwig, J. Unleashing the Power of Potassium 2-Ethylhexanoate as a Mild and Soluble Base for Pd-Catalyzed C–N Cross-Coupling. JACS, 2025, 147 (50), 45871–45883. (*equal contribution)

  

• Yuan, T.; Tang, Q.; Shan, C.; Ye, X.; Wang, J.; Zhao, P.; Wojtas, L.; Hadler, N.; Chen, H.; Shi, X. Alkyne Trifunctionalization via Divergent Gold Catalysis: Combining π-Acid Activation, Vinyl-Gold Addition, and Redox Catalysis. JACS, 2021, 143 (10), 4074–4082.

  

Preprints

• Chen, J.*; Hadler, N.*; Xie, T.; Hnatyshyn, R.; Geniesse, C.; Yang, Y.; Mahoney, M. W.; Perciano, T.; Hartwig, J. F.; Maciejewski, R.; Weber, G. H. Landscaper: Understanding Loss Landscapes Through Multi-Dimensional Topological Analysis. arXiv, 2026, 2602.07135 (v3). (*equal contribution)

  

• Hadler, N.; Rinehart, N. I.; Elkin, M.; Nicolai, J.; Gheibi, G.; Chen, J.; Avaylon, M.; Maciejewski, R.; Weber, G. H.; Mahoney, M. W.; Perciano, T.; Hartwig, J. F. A 3D, Structure-Based, Deep Learning Approach for Predicting the Regioselectivity of Transition-Metal Catalysis. ChemRxiv, 2026, v1.

  

Software

• Weber, G.; Hadler, N.; Xie, T.; Chen, J.; Hnatyshyn, R. Landscaper v1. 2025. Software release. Code · DOE CODE record.

Conference abstracts

• Hadler, N., A 3D, Structure-Based, Deep Learning Approach for Predicting the Regioselectivity of Olefin Hydroformylation, Oral Presentation at the 8th Artificial Intelligence in Chemistry Symposium, Cambridge, London, UK, September 2025.
• Hadler, N., Predicting the Regioselectivity of Olefin Hydroformylation with Machine Learning, Invited Poster Presentation: “Unlocking a New Era: How AI is Transforming Drug Discovery and Development Symposium”, ACS Spring, 2025.
• Hadler, N., Predicting the Regioselectivity of Olefin Hydroformylation with Machine Learning, Bay Area Chemistry Symposium, 2024.