Faculty profile
Benjamin Sanchez-Lengeling
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Read how they describe their research on their University of Toronto profile.
Latest papers
A semantic-based community model for high-fidelity tuning of olfactory mixture distances.
Proceedings of the National Academy of Sciences of the United States of America · 2026
Artificial intelligence for food innovation.
Nature food · 2026
Gradient-based optimization of complex nanoparticle heterostructures enabled by deep learning on heterogeneous graphs.
Nature computational science · 2026
3 publications.
A semantic-based community model for high-fidelity tuning of olfactory mixture distances.
Satarifard V, Sisson L, Han Y, Ilídio P, Hladiš M, Lalis M, Song X, Yang T, Yin W, Ravia A, Zheng CX, Andreoletti G, Albrecht J, Pellegrino R, Wang Z, Yang S, D'hondt R, Ghinis A, de Boer J, Nakano FK, Gharahighehi A, Vilar JMG, Saiz L, Dream Olfactory Mixtures Prediction Consortium, Sanchez-Lengeling B, Keller A, Vosshall LB, Fiorucci S, Tewari A, Topin J, Vens C, Björkman M, Kragic D, Sobel N, Christakis NA, Mainland JD, Meyer P
Artificial intelligence for food innovation.
Datta B, Buehler MJ, Chow Y, Gligorić K, Jurafsky D, Kaplan DL, Ledesma-Amaro R, Del Missier G, Neidhardt L, Pichara K, Sanchez-Lengeling B, Schlangen M, St Pierre SR, Tagkopoulos I, Thomas A, Watson N, Kuhl E
Gradient-based optimization of complex nanoparticle heterostructures enabled by deep learning on heterogeneous graphs.
Sivonxay E, Attia L, Spotte-Smith EWC, Sanchez-Lengeling B, Xia X, Barter D, Chan EM, Blau SM
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Profile data last refreshed on September 29, 2026 from the university directory, publication records and public research funding records.