AI undergraduate at Mahindra University interested in Machine Learning, Optimization, and predictive modeling. Passionate about understanding the mathematical foundations of intelligent systems and translating theoretical concepts into practical AI solutions.
App Developer Intern
MahaDevesthanam
- Co-developing a puja booking platform (Django + React Native) connecting devotees, priests, and temples — 2-person MVP team under faculty supervision.
- Independently built login, registration, and profile dashboard views end-to-end; collaborating on feature allocation and delivery with a peer developer.
Software Developer Intern
Vasstr (inikru.com)
- Assisted in developing frontend and backend features for a Django-based SaaS platform under the guidance of senior developers, gaining hands-on experience with production workflows and collaborative development.
- Contributed to an existing production codebase by navigating its architecture, fixing issues, and supporting feature development in a collaborative team environment.
Developed an ML-based stock trading simulator using Scikit-learn, Django REST Framework, React, and TypeScript. Implemented stock signal prediction using Random Forest and other classification models, a custom backtesting engine, and a Linear Programming-based portfolio allocator using SciPy to distribute capital under budget constraints.
Developed a Discord-style communication platform using Django REST Framework and PostgreSQL, featuring a server-channel-message hierarchy, JWT authentication, invite-based onboarding, and role-based access control for owners, administrators, and members. Designed REST API endpoints and relational database models to support server management and multi-type messaging.
Built an end-to-end SMS spam classification system using Python, NLTK, and Scikit-learn. Implemented text preprocessing and TF-IDF feature extraction, compared Logistic Regression, Support Vector Machines, and Naive Bayes, and achieved a best macro F1-score of 0.96 with Logistic Regression. Deployed the trained model through a Streamlit application for inference.
Developed a command-line expense tracker in C using dynamic memory allocation and custom singly linked lists. Implemented expense management operations, category-based filtering, memory cleanup, and automated expense settlement calculations without external dependencies.
Bachelor's of Technology in AI
Mahindra University · 9.21 / 10
Intermediate (12th)
Resonance · 94.4%
10th
P. Obul Reddy Public School · 88%
DeepLearning.AI
October 2026Hackerrank
February 2026
Attendee · Oct 24, 2026