Gabriel dos Passos Gomes

Universidade de Brasília — Brazil

Materials Science · Physical Sciences

36h-index4.9kcitations172works3.42yr avg
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Research Topics

Crystallization and Solubility Studies(46), X-ray Diffraction in Crystallography(46), Machine Learning in Materials Science(31), Catalytic C–H Functionalization Methods(19), Radical Photochemical Reactions(19)

Publications172 total

Learning When to Stop: Adaptive Latent Reasoning via Reinforcement Learning
arXiv (Cornell University)·2025Open Access
Democratizing Reaction Kinetics through Machine Vision and Learning
2025
Connecting chemical and protein sequence space to predict biocatalytic reactions
Nature·2025· 9 citedOpen Access
Assessing goodness-of-fit for sparse categories using Rényi divergence
Journal of Statistical Planning and Inference·2025
Industrial Robot Motion Planning with GPUs: Integration of cuRobo for Extended DOF Systems
arXiv (Cornell University)·2025Open Access
Advances on MagLITe: deposition and photocollection efficiency
Journal of Instrumentation·2025Open Access
Spectral Manifold Harmonization for Graph Imbalanced Regression
arXiv (Cornell University)·2025Open Access
Rethinking chemical research in the age of large language models
Nature Computational Science·2025· 3 cited
Advancing molecular machine learning representations with stereoelectronics-infused molecular graphs
Nature Machine Intelligence·2025· 7 citedOpen Access
Dual-use capabilities of concern of biological AI models
PLoS Computational Biology·2025· 16 citedOpen Access
Transferable Machine Learning Interatomic Potential for Pd-Catalyzed Cross-Coupling Reactions
2025· 5 citedOpen Access
Vibrationally Assisted Tunneling through the Bread of a Proton Sandwich─Connections to Dynamic Matching
Journal of the American Chemical Society·2025· 5 cited
Vibrationally Assisted Tunneling through the Bread of a Proton Sandwich - Connections to Dynamic Matching
2024
Generation of connections between protein sequence space and chemical space to enable a predictive model for biocatalysis
2024· 3 citedOpen Access
Prioritizing High-Consequence Biological Capabilities in Evaluations of Artificial Intelligence Models
SSRN Electronic Journal·2024· 3 citedOpen Access
Autonomous chemical research with large language models
Nature·2023· 672 citedOpen Access
Applying Large Graph Neural Networks to Predict Transition Metal Complex Energies Using the tmQM_wB97MV Data Set
Journal of Chemical Information and Modeling·2023· 20 citedOpen Access
Applying Large Graph Neural Networks to Predict Transition Metal Complex Energies Using the tmQM_wB97MV Dataset
2023· 1 citedOpen Access
Applying Large Graph Neural Networks to Predict Transition Metal Complex Energies Using the tmQM_rev Dataset
2023· 2 citedOpen Access
Emergent autonomous scientific research capabilities of large language models
arXiv (Cornell University)·2023· 74 citedOpen Access
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Frequent Co-authors

Igor V. Alabugin(31), Alán Aspuru‐Guzik(13), Robert Pollice(10), Alexander O. Terent’ev(8), AkshatKumar Nigam(6), Pascal Friederich(6), G. I. Nikishin(6), Vera A. Vil’(5), Mario Krenn(4), Cyrille Lavigne(4), Kamalkishore Pati(4), Trevor Harris(4), Kenneth Hanson(4), Robert MacKnight(3), Tobias Gensch(3), Matthew S. Sigman(3), Christopher J. Evoniuk(3), Konstantin А. Lyssenko(3), Ivan A. Yaremenko(3), Peter S. Radulov(3)