Our mission
Machine Learning for Infection and Disease (MLID) group (aka Yakimovich group) aims to develop the latest Machine Learning and Computer Science methods to facilitate our understanding of Infection Biology and Disease Biology.
Latest preprints
Wyrzykowska, Maria, et al. “A Benchmark for Virus Infection Reporter Virtual Staining in Fluorescence and Brightfield Microscopy.” bioRxiv (2024).
De, Trina, Vardan Andriasyan, and Artur Yakimovich. “PyPlaque: an Open-source Python Package for Phenotypic Analysis of Virus Plaque Assays.” bioRxiv (2024).
Li, Rui, et al. “Denoising, Deblurring, and optical Deconvolution for cryo-ET and light microscopy with a physics-informed deep neural network DeBCR.” bioRxiv (2024).
della Maggiora, Gabriel, et al. “Single Exposure Quantitative Phase Imaging with a Conventional Microscope using Diffusion Models.” arXiv preprint arXiv:2406.04388 (2024).
Li, Rui, Gabriel della Maggiora, Vardan Andriasyan, Anthony Petkidis, Artsemi Yushkevich, Mikhail Kudryashev, and Artur Yakimovich. “Microscopy image reconstruction with physics-informed denoising diffusion probabilistic model.” arXiv preprint arXiv:2306.02929 (2023).
Latest papers
Li, Rui, Mikhail Kudryashev, and Artur Yakimovich. “Solving the inverse problem of microscopy deconvolution with a residual Beylkin-Coifman-Rokhlin neural network.” ECCV (2024).
Della Maggiora, Gabriel, et al. “Conditional Variational Diffusion Models.” The Twelfth International Conference on Learning Representations. 2023.
Sharma, Vaibhav, and Artur Yakimovich. “A deep learning dataset for sample preparation artefacts detection in multispectral high-content microscopy.” Scientific Data (2024).
Liou, Natasha, et al. “A clinical microscopy dataset to develop a deep learning diagnostic test for urinary tract infection.” Scientific Data (2024).
Li, Rui, Mikhail Kudryashev, and Artur Yakimovich. “A weak-labelling and deep learning approach for in-focus object segmentation in 3D widefield microscopy.” Scientific Reports (2023).
Sharma, Vaibhav, and Artur Yakimovich. “Phenotype-preserving metric design for high-content image reconstruction by generative inpainting.” Emerging Topics in Artificial Intelligence (ETAI) 2023. Vol. 12655. SPIE (2023).
Li, Rui, et al. “Open-Source Biomedical Image Analysis Models: A Meta-Analysis and Continuous Survey.” Frontiers in Bioinformatics (2022): 76.
Galimov, Evgeniy, and Artur Yakimovich. “A tandem segmentation-classification approach for the localization of morphological predictors of C. elegans lifespan and motility.” Aging (Albany NY) 14.4 (2022): 1665.
