• Built python based plugins for Napari image viewing tool. The plugins enabled functionalities such as viewing and filtering multi-channel large spatial transcriptomics images, polygonal cropping of multi-slice images etc.

• Analyzed scRNA-seq data from multiple tumor datasets in order to identify cell type specific surface protein markers for cancer

Working at the Pfenning Lab analyzing scATAC-seq data from peripheral blood and bone marrow cells.

• Obtained cell type specific peaks using Seurat differential accessibility test and verified validity of obtained peaks using Centrimo motif analysis.

• Trained classification and regression convolutional neural networks to take in a genomic sequence and predict its expression in different blood cell types. This model is now being tested to predict and compare expression of Alzheimer specific SNPs against reference alleles.

Worked at the Lopez Lab analyzing different molecular fingerprints and machine learning models for predicting the HOMO and LUMO energy values of an organic molecule.

Built platforms for processing and management of large amounts of user data.