Ajita Shree

Biography

I completed PhD at the Department of Computer Science and Engineering, Indian Institute of Technology Kanpur. My dissertation focused on deep generative models for single-cell and spatial transcriptomics datasets. During my doctoral research, I developed scDREAMER, a deep generative model for unsupervised, supervised, and atlas-level integration of single-cell transcriptomics datasets, across diverse integration challenges. In the latter part, I introduced spDDB, a comprehensive benchmarking study of state-of-the-art deconvolution and domain detection methods. This work included a novel evaluation framework for spatial transcriptomics, an extensive dataset repository spanning brain, cancer, and multiple organ tissues, as well as the development of a deep graph attention-based simulator for generating realistic simulated spatial datasets. Previously, I completed M.Tech in Computer Science and Engineering from Indian Institute of Technology Delhi. I also have industry experience at GE Global Research and GE Aviation, where I contributed to the development of large-scale machine learning systems for flight scheduling, focusing on engine failure forecasting for the international airline industry.

Research Interests

My current research focuses on computational method development leveraging probabilistic techniques for single-cell and spatial transcriptomics data, aimed at studying cell–cell communication within tissues

Professional Career

Education

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