I am a graduate student at Marquette University.

I have a keen interest in exploring all areas within the machine and deep learning. However, I have most experience in computer vision and graph neural networks. My current research focuses on vision+x models and their interpretability. At the moment I am exploring vision+x models used in computational pathology and how to understand their predictions.

Previously I was a lecturer in the Electrical, Electronic and Communication (EECE) department, MIST.

Technical Write-ups

I maintain several technical blogs where I write about topics in deep learning and machine learning.

• Main Blog: My main blog where I cover all sorts of topic including deep learning architectures, Pytorch, statistics, machine learning, etc.
• Linear Algebra Blog: My Linear Algebra blog where I keep my lecture notes regarding linear algera.

News

• [2024-12-15] My journal paper titled “Explainability-Based Adversarial Attack on Graphs Through Edge Perturbation” got accepted to Knowledge-Based Systems
• [2024-08-17] My journal paper titled “A Heterogeneous Graph-Based Multi-Task Learning for Fault Event Diagnosis in Smart Grid” got accepted to IEEE Transactions on Power Systems.
• [2024-07-30] My conference paper titled “A Graph Motif Adversarial Attack for Fault Detection in Power Distribution Systems” got accepted to the 2024 IEEE Global Communications Conference.
• [2024-03-01] My first journal paper titled “DCENSnet: A new deep convolutional ensemble network for skin cancer classification” got accepted to Biomedical Signal Processing and Control.
• [2023-09-20] My conference paper titled “Graph-based Multi-Task Learning for Fault Detection in Smart Grid” got accepted to MLSP 2023.
• [2023-01-01] I started my graduate student journey at Marquette University.

I have a habit of curating courses in deep learning and related resources. Check out this GitHub repo for that. I also have a habit of curating technical blog posts on deep learning-related topics. Check out this Github repo for that. I also have a repository where I curate other interesting stuff I find about deep learning, stats and math which includes interactive websites and publicly available books and e-books.