Author

Saeed Karimimehr

Institute for Research in Fundamental Sciences

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Neuroscience· 3

Signature Assays, Organisms & Methods

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Research Focus:benchmarking· 2 Assay:electronic health records· 2 Approach:statistical model· 2 Research Focus:clustering· 1 Approach:experimental assay· 1 Approach:machine learning (classical)· 1 Organism:non-human primate· 1

Frequent Co-Authors

Reza LashgariiD· 2 shared Achilleas GhinisiD· 1 shared Adomas Malaiska· 1 shared Aharon RaviaiD· 1 shared Alexei A. KoulakoviD· 1 shared Alfonso MonacoiD· 1 shared Ali GhazizadehiD· 1 shared Alireza GharahighehiiD· 1 shared

Activity by Year

2018-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 29 mutual co-author links

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2 shared papersNeuroscience

Reza LashgariORCID

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Author profile →

3 papers

Recent·Most cited

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, Tiffany Yang, Wenjie Yin, Aharon Ravia, Xingyu Zheng, Gaia Andreoletti, Jacob W. Albrecht, Robert Pellegrino, Wang Ze-hua, , Alexei A. Koulakov

The paper presents an ensemble model that improves predictions of perceptual similarity between odor mixtures using a curated dataset and collaborative challenge results.

Proceedings of the National Academy of Sciences · Aug 4, 2026Peer-reviewedNeuroscience

Microscopic and mesoscopic effects of reward uncertainty in monkey fronto-parietal areas

Bahareh Taghizadeh, Nicholas C. Foley, Saeed Karimimehr, Michael Cohanpour, Mulugeta Semework, Sameer Anil Sheth, Reza Lashgari, Jacqueline P. Gottlieb

This study investigates how reward uncertainty affects neural activity in monkey fronto-parietal areas, showing distinct cellular and network-level responses.

bioRxiv · Dec 17, 2019 · PreprintNeuroscience

A fully automated spike sorting algorithm using t-distributed neighbor embedding and density based clustering

Mohammad Hossein Nadian, Saeed Karimimehr, Jafar Doostmohammadi, Ali Ghazizadeh, Reza Lashgari

This paper introduces a fully automated spike sorting algorithm combining t-SNE and DBSCAN, optimized with GA, which outperforms existing methods and human experts in accuracy and efficiency for large-scale neural recordings.

bioRxiv · Sep 26, 2018 · PreprintNeuroscience