Author

Agastya Mondal

University of California, BerkeleyORCID 0000-0002-3369-987XUnclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 1 Genetics· 1

Signature Assays, Organisms & Methods

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Research Focus:benchmarking· 2 Approach:deep learning· 1 Organism:human· 1 Approach:statistical model· 1

Frequent Co-Authors

Andrea L. SmidleriD· 1 shared David ZilbermaniD· 1 shared Héctor M. Sánchez C.iD· 1 shared John Macky MarshalliD· 1 shared Omar S. AkbariiD· 1 shared Patrick G. IlboudoiD· 1 shared Prashanth SelvarajiD· 1 shared Robyn R RabaniD· 1 shared

Activity by Year

2023-2025 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 29 mutual co-author links

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1 shared paperGenetics

Andrea L. SmidlerORCID

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2 papers

Recent·Most cited

BioinformaticsPLoS Computational BiologyPeer-reviewedJul 31, 2025

Multitask deep learning for the emulation and calibration of an agent-based malaria transmission model

Agastya Mondal, Rushil Anirudh, Prashanth Selvaraj

This paper develops a multitask deep learning emulator to calibrate an agent-based malaria transmission model using simulations and real-world data.

2 citations

deep learningbenchmarking

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GeneticsbioRxivPreprintJul 20, 2023

Cost-effectiveness of Precision Guided SIT for Control of Anopheles gambiae in the Upper River Region, The Gambia.

William A.C. Gendron, Robyn R Raban, Agastya Mondal…·Omar S. Akbari

This paper evaluates the cost-effectiveness of precision-guided sterile insect technique (pgSIT) for malaria control in The Gambia, finding it to be a cost-effective and economically beneficial approach.

2 citations

humanstatistical model

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