Benjamín Sánchez-Lengeling

Google (United States) — United States

Materials Science · Physical Sciences

26h-index9.0kcitations66works9.62yr avg
OpenAlex↗ORCID↗Google Scholar↗Lab page↗

Accepting Students?

No reports yet. Know if this professor is taking students?

Research Topics

Machine Learning in Materials Science(32), Computational Drug Discovery Methods(25), Olfactory and Sensory Function Studies(9), Advanced Chemical Sensor Technologies(9), Protein Structure and Dynamics(8)

Publications66 total

High-Fidelity Tuning of Olfactory Mixture Distances in the Perceptual Space of Smell Through a Community Effort
2025· 1 citedOpen Access
Gradient-based optimization of complex nanoparticle heterostructures enabled by deep learning on heterogeneous graphs
Nature Computational Science·2025· 2 cited
Does this smell the same? Learning representations of olfactory mixtures using inductive biases
Machine Learning Science and Technology·2025· 1 citedOpen Access
Ranking over regression for Bayesian optimization and molecule selection
APL Machine Learning·2025· 2 citedOpen Access
Graph Data Modeling: Molecules, Proteins, & Chemical Processes
ACS in focus·2025· 1 citedOpen Access
Inverse Design of Complex Nanoparticle Heterostructures via Deep Learning on Heterogeneous Graphs
2025· 1 citedOpen Access
CheMixHub: Datasets and Benchmarks for Chemical Mixture Property Prediction
arXiv (Cornell University)·2025Open Access
Advancing molecular machine learning representations with stereoelectronics-infused molecular graphs
Nature Machine Intelligence·2025· 7 citedOpen Access
From Molecules to Mixtures: Learning Representations of Olfactory Mixture Similarity using Inductive Biases
arXiv (Cornell University)·2025Open Access
A deep learning and digital archaeology approach for mosquito repellent discovery
Chemical Senses·2025· 1 citedOpen Access
Ranking over Regression for Bayesian Optimization and Molecule Selection
arXiv (Cornell University)·2024· 2 citedOpen Access
Delocalized, asynchronous, closed-loop discovery of organic laser emitters
Science·2024· 113 citedOpen Access
Delocalized, Asynchronous, Closed-Loop Discovery of Organic Laser Emitters
Zenodo (CERN European Organization for Nuclear Research)·2024Open Access
Perspective on AI for accelerated materials design at the AI4Mat-2023 workshop at NeurIPS 2023
Digital Discovery·2024· 5 citedOpen Access
Delocalized, Asynchronous, Closed-Loop Discovery of Organic Laser Emitters
2023· 16 citedOpen Access
Delocalized, Asynchronous, Closed-Loop Discovery of Organic Laser Emitters
2023Open Access
A principal odor map unifies diverse tasks in olfactory perception
Science·2023· 171 citedOpen Access
Author response for "Calibration and generalizability of probabilistic models on low-data chemical datasets with DIONYSUS"
2023
Metabolic activity organizes olfactory representations
eLife·2023· 20 citedOpen Access
Author response: Metabolic activity organizes olfactory representations
2023Open Access
page 1 of 4Next →

Frequent Co-authors

Alán Aspuru‐Guzik(40), Jennifer N. Wei(9), Alexander B. Wiltschko(7), Adrián Jinich(7), Richard C. Gerkin(6), Brian K. Lee(6), Haniu Ren(6), Zhenpeng Yao(5), Wesley Wei Qian(5), Εlad Noor(5), N. Scott Bobbitt(4), Benjamin J. Bucior(4), Sai Govind Hari Kumar(4), Tom K. Woo(4), Omar K. Farha(4), Randall Q. Snurr(4), Carlos Outeiral(4), Gabriel L. Guimaraes(4), Riley J. Hickman(4), Gary Tom(4)