About Me

Nilay is a Ph.D. graduate from Tufts University with a focus in Biomedical Engineering. Under the direction of Professor Irene Georgakoudi, Nilay's research was focused on application of machine learning to denoise low-SNR biomedical time-series and image datasets. His principal project has focused on label-free detection of rare circulating tumor cell clusters in whole blood using machine learning-based

classification algorithms. His secondary project was focused on denoising low-SNR clinical cervical biopsy images to improve image acquisition speed of a clinical probe for cervical pre-cancer detection. His future interest is in application of ML and DL for image super-resolution and denoising.
Learn more about my work below!

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ML-based, Label-free detection of circulating tumor cell clusters in whole blood

Keywords: MATLAB, Flow Cytometry, Machine Learning, Python, PyTorch, Time-series Data, Peak Analysis, Breast Cancer

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Denoising label-free, two-photon microscopy images using DL

Keywords: Two-Photon Microscopy, Metabolics, Cervical Pre-Cancer, Computer Vision, Python, TensorFlow, MATLAB, U-Net, Generatve Adversarial Network, Residual Channel Attention Network, ResNet, Image Denoising

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