Portfolio

The CODE

Principles that guide every system I build.

Build With Intention

Every system must solve a real problem.

Eliminate Inefficiency

Optimize relentlessly. Remove what does not serve the system.

Discipline Over Motivation

Consistency matters more than temporary bursts of effort.

Precision In Execution

Clean architecture. Clear logic. No loose ends.

Relentless Evolution

Learn continuously. Refine constantly. Never stay stagnant.

Precision Builds

Systems engineered with structure and intent.

RL-Based L1 Cache Replacement Simulator

Designed a Python-based L1 cache simulator implementing a tabular Q-learning agent using stride, recency, and frequency features. Achieved up to 5% improvement over LRU in mixed workloads.

Python · NumPy · pandas · Reinforcement Learning

Fake News Detector – IEEE Accepted

Built an end-to-end NLP pipeline using TF-IDF and Random Forest achieving 85–94% accuracy. Developed and deployed a Flask-based inference API with multilingual preprocessing.

Python · Flask · scikit-learn · Transformers

AnnaDaatha – Food Donation Platform

Developed a full-stack food donation system with Flask backend and MongoDB database, enabling authentication, food listing, expiry tracking, and dashboard management.

Flask · MongoDB · Python · HTML · Tailwind

Tools of Precision

Technologies and systems I work with.

Programming

Python · C · C++ · JavaScript

Frameworks & Backend

Flask · Node.js · REST APIs · MongoDB

Machine Learning

scikit-learn · NumPy · pandas · TF-IDF · Transformers

Computer Science

Data Structures · Algorithms · Computer Architecture

The Drive

I am a B.Tech student in Electronics and Communication Engineering with a focused transition toward software engineering and machine learning systems. My work revolves around structured problem-solving, clean architecture, and continuous refinement.

Growing within a disciplined environment, I value consistency over intensity and systems over shortcuts. Whether building ML pipelines or full-stack applications, I approach every system with precision and intent.

My long-term objective is to engineer scalable systems that create measurable impact, combining strong computer science fundamentals with modern machine learning practices.