Publications

Predicting Molecular Properties with Graph Neural Networks

Benjamin Sánchez-Lengeling, Other Author

Nature Machine Intelligence · 2026

We introduce a machine learning framework for predicting molecular properties across chemical mixtures using graph neural networks.

molecular-ai chemical-mixtures #graph-neural-networks #interpretability

Paper → Code → Data →

A Framework for Bayesian Optimization in Mixture Spaces

Paola Driza, Benjamin Sanchez-Lengeling

· 2026

Details →

Bridging Sequence and Kinetics: Utilizing Multi-scale Representations for Genome-Scale Metabolic Models

Rana Barghout, Lya Serrano, Zhiqing Xu, Benjamin Sanchez, Radhakrishnan Mahadevan

· 2026

Details →

CheMixHub: Datasets and benchmarks for chemical mixture property prediction

Ella Rajaonson, Mahyar Rajabi Kochi, Luis Mejia Mendoza, Mohamad Moosavi, Benjamin Sanchez-Lengeling

· 2026

Details →

Gradient-based optimization of complex nanoparticle heterostructures enabled by deep learning on heterogeneous graphs

Eric Sivonxay, Lucas Attia, Evan Spotte-Smith, Benjamin Sanchez-Lengeling, Xiaojing Xia, Daniel Barter, Emory Chan, Samuel Blau

· 2026

Details →

kinGEMs: A Robust and Scalable Framework for Resource-Constraint Models through Stochastic Tuning of Deep Learning-Predicted Kinetic Parameters

Rana Barghout, Lya Chiñas Serrano, Benjamin Sanchez-Lengeling, Radhakrishnan Mahadevan

· 2026

Details →

Machine Learning for Sequence-to-Function Approaches

Rana Barghout, Maxim Kirby, Austin Zheng, Lya Chinas, Marjan Mohammadi, Zhiqing Xu, Benjamin Sanchez-Lengeling, Radhakrishnan Mahadevan

· 2026

Details →

TasteBench: multimodal benchmark for sensory prediction, from molecules to sustainable foods

Anna Thomas, Sohum Patnaik, Caroline Cotto, Benjamin Sanchez-Lengeling

· 2026

Details →

TubercuProbe: A Cross-Attention Graph-Sequence Model for Cross-Species Chemoproteomic Discovery in Mycobacterium tuberculosis

Abhiram Chalamalasetty, Adesh Mishra, Fleur Ferguson, Benjamin Sanchez-Lengeling, José Barraza-Chavez, Adrian Jinich

· 2026

Details →

A deep learning and digital archaeology approach for mosquito repellent discovery

Jennifer Wei, Carlos Ruiz, Marnix Vlot, Benjamin Sanchez-Lengeling, Brian Lee, Luuk Berning, Martijn Vos, Rob Henderson, Wesley Qian, Jacob Sanders, others

· 2025

Details →

Advancing molecular machine learning representations with stereoelectronics-infused molecular graphs

Daniil Boiko, Thiago Reschützegger, Benjamin Sanchez-Lengeling, Samuel Blau, Gabe Gomes

· 2025

Details →

Artificial Intelligence for Food Innovation

Bianca Datta, Markus Buehler, Yvonne Chow, Kristina Gligoric, Dan Jurafsky, David Kaplan, Rodrigo Ledesma-Amaro, Giorgia Del Missier, Lisa Neidhardt, Karim Pichara, others

· 2025

Details →

Does this smell the same? Learning representations of olfactory mixtures using inductive biases

Gary Tom, Cher Tian Ser, Ella Rajaonson, Stanley Lo, Hyun Suk Park, Brian Lee, Benjamin Sanchez-Lengeling

· 2025

Details →

Graph Data Modeling: Molecules, Proteins, & Chemical Processes

José Barraza-Chavez, Rana Barghout, Ricardo Almada-Monter, Adrian Jinich, Radhakrishnan Mahadevan, Benjamin Sanchez-Lengeling

· 2025

Details →

High-Fidelity Tuning of Olfactory Mixture Distances in the Perceptual Space of Smell Through a Community Effort

Vahid Satarifard, Laura Sisson, Yikun Han, Pedro Ilídio, Matej Hladiš, Maxence Lalis, Xuebo Song, Wenjie Yin, Aharon Ravia, CiCi Zheng, others

· 2025

Details →

Kingems: Bridging Sequence and Kinetics for Enzyme-Constrained Genome-Scale Models

Rana Barghout, Lya Serrano, Zhiqing Xu, Benjamin Sanchez-Lengeling, Radhakrishnan Mahadevan

· 2025

Details →

Ranking over regression for bayesian optimization and molecule selection

Gary Tom, Stanley Lo, Samantha Corapi, Alan Aspuru-Guzik, Benjamin Sanchez-Lengeling

· 2025

Details →

Delocalized, asynchronous, closed-loop discovery of organic laser emitters

Felix Strieth-Kalthoff, Han Hao, Vandana Rathore, Joshua Derasp, Théophile Gaudin, Nicholas Angello, Martin Seifrid, Ekaterina Trushina, Mason Guy, Junliang Liu, others

· 2024

Details →

Machine-learned models for sensory property prediction

Alexander Wiltschko, Wei Qian, Jennifer Wei, Benjamin Sanchez-Lengeling, Brian Lee, Yiliu Wang

· 2024

Details →

Perspective on ai for accelerated materials design at the ai4mat-2023 workshop at neurips 2023

Santiago Miret, NM Krishnan, Benjamin Sanchez-Lengeling, Marta Skreta, Vineeth Venugopal, Jennifer Wei

· 2024

Details →