Worked on a GNN-based accident detection system for a smart traffic solution for the Govt. of Odisha, cutting emergency response times by over 60%. Also designed an EHR application handling 100,000+ daily records and improved record retrieval by 42%.

Developed conformal prediction methods to enhance uncertainty quantification in pathological cell classification workflows, improving model interpretability and robustness. Also designed a sampling-based feature bias mitigation technique to address data-driven biases in cervical cytology classification, improving model fairness and reliability.

Built a sapling detection algorithm that detects over 300 tree species, for savannah and mangrove restoration projects. Also finetuned a Llama2-13b model for a summarization platform with custom review tags for grey literature of regeneration practices on ASReview Lab.

Worked on a Contrastive Self-Supervised Learning (CSSL) approach for macromolecular structure classification from cryo-ET data with limited labels. Also contributed to an unsupervised multi-task learning framework for 3D subtomogram image alignment, clustering, and segmentation in cryo-ET environment.

Participated in the 2023 Neuromatch Academy Summer School on Computational Neuroscience. Designed regression models for future motion state prediction using time series analysis on ECoG data.

Partcipated in the 3rd Edition Summer School on Deep Learning for Medical Imaging (DLMI-22). Evaluated various weakly supervised segmentation techniques for cardiac diseases diagnosis.

Worked on building the 'Indian Brain Segmentation Dataset'- a sub-cortical structure segmentation database for young population. Also contributed to a multi-scale attention architecture for COVID-19 detection from Chest-X Rays.