Research & Projects

Innovative Solutions & Research Contributions

4th Position Award

Autoimmune Disease Machine Learning Challenge

Ongoing Research Competition @ Broad Institute

Oct 2024 – Present

Predicted gene expression in colon tissue using spatial transcriptomics and pathology images. Employed Vision Transformers for feature extraction, multi-head attention mechanisms, and encoder-decoder models for gene expression prediction. Used interpretable ML models (CatBoost, LightGBM, XGBoost) for dysplasia classification.

Technologies Used

Vision Transformers PyTorch CatBoost LightGBM XGBoost Deep Learning

Achievements

  • 4th position in Crunch 2 at Broad Institute
  • Gene expression prediction accuracy improved by 15%
  • Interpretable ML models for clinical decision support
PhD Research

Enhancing Spatial Resolution of Satellite Images

Remote Sensing & Super-resolution

Feb 2024 – Apr 2024

Addresses resolution trade-off in satellite imagery by enhancing Sentinel-2 (10m) images using PlanetScope (3m) data through adversarial networks. Deep learning-based super-resolution model reconstructs fine details and spatial resolution for remote sensing applications.

Technologies Used

GANs (Generative Adversarial Networks) TensorFlow Super-resolution Satellite Data Image Processing

Key Aspects

  • Novel GAN architecture for image enhancement
  • Multi-modal data fusion techniques
  • Applied to environmental monitoring
Master's Thesis

AI-based Diagnostic Solution for Dental Radiography

Medical Image Analysis & Deep Learning

Apr 2022 – Aug 2023

Focused on medical imaging for detection of deciduous teeth in intraoral periapical radiographs (IOPA). Developed Deep Learning models for IOPA analysis. Collaborated with PGIMER, Chandigarh for dataset acquisition. Co-authored a review paper on AI-driven preprocessing and segmentation techniques.

Technologies Used

Deep Learning Medical Image Segmentation CNN DICOM Python

Collaborations

Collaborated with PGIMER (Post Graduate Institute of Medical Education & Research), Chandigarh for clinical dataset and validation.

Publications

Co-authored a peer-reviewed paper published in Multimedia Tools and Applications (2024)

PhD Research

Derivations and Applications of Computer Science in Mathematics

Mathematical Foundations & ML

Oct 2024 – Nov 2024

Mathematical foundations in computer science focusing on Least Squares Methods, Ridge and Kernel Ridge Regression, Principal Component Analysis (PCA), Singular Value Decomposition (SVD), and their practical applications in machine learning.

Topics Covered

Linear Algebra Optimization PCA SVD Regression Statistical Methods

Key Learnings

  • Deep understanding of mathematical foundations
  • Ridge and kernel regression applications
  • Dimensionality reduction techniques

Project Overview

Total Projects

4

Awards

1

4th Position @ Broad Institute

Publications

2+

Peer-reviewed papers

Technologies

10+

AI/ML frameworks

View Publications Technical Skills