AI/ML | IEEE Ideathon Winner 2024 | Linux & System Enthusiast

I’m all about blending AI with real-world impact from medical imaging and federated learning to AI-driven judiciary apps and system-level OS tuning. Whether it’s training CNNs for explainability, working at Linux kernels, or exploring federated architectures, I love building solutions that are scalable, ethical, and future-ready.

• Federated Learning with Adaptive Optimization – Personalized FL achieving 97.92% client accuracy.
• PathMNIST-XAI: Explainable CNN for Medical Imaging - Lightweight Explainable CNN for PathMNIST medical imaging, achieving 91%+ accuracy with Integrated Gradients, SQLite attribution storage, and scalable PyTorch deployment.
• Recipe Management Website - A Flask + MySQL web app to create, manage, and share recipes with image uploads, allergen tracking, and vegetarian/non-vegetarian categorization.
• Public Pulse – AI-powered judiciary app for transparency & trust in automated decisions.
• GoodLife Foundation – Visitor & Donation Tracker - GoodLife Foundation Admin Portal is a lightweight Flask + SQLite3 web app for small NGOs and orphanages to securely record visitor details and track donations in one place.
• Face Anonymization – YOLOv8 model trained for detecting face which is useful for blurring faces in images to protect privacy, which possess threat and privacy concerns of individuals.

• Stop Memorizing Loss Functions in ML - Here’s How to Actually Understand Them - This article breaks down the most important loss functions in machine learning. Instead of dumping formulas, I’ll show you where each one belongs, a mnemonic to remember it, and insider commentary you won’t usually find in textbooks.
• How Federated Learning Solves the Accuracy Gap in Heterogeneous Data - I explored Federated Learning (FL) to address a common challenge: improving model performance across clients with heterogeneous data without sharing raw datasets.

• IEEE CommBattle Ideathon Winner (2024) – Built AI-driven judiciary prototype and won a crash prize.
• C-DAC Intern – Kernel tuning for BOSS OS to improve latency & CPU scheduling.
• International Delegate (Malaysia) – Tech diplomacy + global exposure.

Languages → Python, C, C++, SQL, Bash
AI/ML → PyTorch, TensorFlow, Scikit-learn, OpenCV, Captum, NumPy, Matplotlib
Systems & OS → Linux (Kernel, Shell Scripting, Memory Mgmt), SQLite, Git
Web & Fullstack → Flask, Django, HTML/CSS/Bootstrap

• Federated Learning & adaptive AI for fairness
• **AI for Healthcare & Judiciary **
• Open Source & HPC AI integration

LeetCode Stats

🔹 LinkedIn
🔹 LeetCode
🔹 Medium

“Its all about one nice sip of tea and a tiny commit everyday.”