📍 Belagavi, Karnataka  |  🎓 KSCST-Selected  |  📄 IRJMETS-Published

I'm a Python Full-Stack Developer specializing in Django, currently working as a Python Full-Stack Developer Intern at Prodhee Technologies (Dhee Coding Lab), Bengaluru. I build scalable, data-driven web applications and have hands-on experience taking a project from idea → deployment.

Alongside full-stack development, I built and published research on a CNN-LSTM deepfake detection system, selected for a state-level student research programme (KSCST) and published in IRJMETS.

• 🔭 Currently working on scalable Django APIs and backend performance optimization
• 🌱 Deepening my expertise in DRF (Django REST Framework) and system design
• 🎯 Seeking Python/Django backend or full-stack roles
• ⚡ Fun fact: I've cut backend query latency by 15%+ on two separate production projects

Python Full-Stack Developer Intern — Prodhee Technologies (Dhee Coding Lab), Bengaluru Feb 2026 – Present

• Built and delivered 5+ full-stack features using Django (MVT), Python, SQL, HTML5, CSS3, and Bootstrap in sprint-based development cycles
• Improved backend data retrieval efficiency by 15% by optimizing Django ORM queries and refactoring CRUD workflows

Python OpenCV CNN-LSTM ResNeXt SQL

DeepShield AI is an intelligent deepfake video detection platform powered by an optimized Django backend. The system coordinates an automated OpenCV preprocessing framework with a hybrid deep learning model (ResNeXt + LSTM) to identify audio-visual inconsistencies and deepfake manipulations in seconds.

• 78% Classification Accuracy: Integrated a CNN-LSTM deepfake detection model into the core web application, validating real-time inference on 1,200+ samples to achieve 78% accuracy over a 66% single-model baseline.
• 30% Data Preparation Speedup: Created an automated OpenCV pipeline for video processing, face detection, and structural face cropping, dropping overall setup times from 14 hours down to 10 hours.
• 15% Retrieval Latency Reduction: Structured a normalized database layer and tuned 8+ Django ORM QuerySet queries via analytical indexing, reducing database access latency from 200 ms to 170 ms.
• Team & Architecture Leadership: Led the end-to-end backend engineering for a 4-member research team, securing the multi-threaded video upload pipeline and exposing robust inference APIs to the frontend.

• State Recognition: Selected for the prestigious KSCST 49th Series Student Project Program (2025-26).
• Research Publication: Co-authored the peer-reviewed paper "DEEPSHIELD AI: Deepfake Detection Using CNN-LSTM Architecture" published in IRJMETS (2025).
• First Place Award: Won 1st Prize at the College Technical Project Exhibition out of 15+ competing engineering project groups.

• Backend Framework: Django (MVT), Django REST Framework, SQLite / MySQL
• Computer Vision & Data Prep: OpenCV, Face Detection Algorithms, Python Data Utilities
• Core Deep Learning Layer: PyTorch, ResNeXt (Spatial Extraction), LSTM (Temporal Sequencing)

• Cut dataset preparation time by 30% (14 hrs → 10 hrs for 1,200 samples) by building an automated OpenCV face-detection and cropping pipeline

• 🏆 1st Prize, College Project Exhibition (15+ entries)  |  ✅ Selected, KSCST 49th Series  |  📄 Published in IRJMETS 2025

• 🔗 Repo

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Django Python REST API SQLite HTML5 CSS3 Bootstrap

Lost & Found Tracker is a full-stack Django web application that streamlines campus lost-and-found operations through secure item reporting, intelligent search, and efficient backend data management. The system provides authenticated CRUD workflows, optimized database access, and RESTful APIs to support fast and reliable item tracking.

• 15% Faster Data Retrieval: Optimized 8+ Django ORM queries and implemented database indexing, reducing average query latency from 200 ms to 170 ms through systematic debugging and performance tuning.
• Backend Architecture: Designed a normalized SQLite database schema and engineered secure CRUD workflows for managing lost and found items across the application.
• REST API Integration: Developed backend modules and REST API endpoints for item reporting, search, and status tracking using modular object-oriented design principles.
• Production Deployment: Successfully deployed the application on PythonAnywhere, demonstrating end-to-end development, deployment, and maintenance of a Django web application.

• Secure CRUD operations for reporting and managing lost and found items.
• Advanced search and filtering for quick item discovery.
• Item status tracking to monitor reported, matched, and returned items.
• Responsive Bootstrap-based user interface integrated with Django templates.

• Backend Framework: Django (MVT), Django ORM, REST API Development
• Database: SQLite (Normalized Schema with Indexed Queries)
• Frontend: HTML5, CSS3, Bootstrap
• Programming Language: Python

• Reduced average database retrieval latency by 15% (200 ms → 170 ms) through ORM query optimization and indexing.
• Built modular backend components implementing secure CRUD workflows and RESTful APIs for item management.
• 🚀 Successfully deployed on PythonAnywhere
• 🔗 Live Demo  |  Repo

Oracle SQL Database Design Data Analytics

• Designed a relational schema (users, categories, expenses, budgets) to model real-world expense tracking and monthly budget limits per category
• Wrote analytical Oracle SQL queries using joins, aggregations, subqueries, and ranking logic to surface category-wise spend, budget-vs-actual comparisons, overspending detection, and top-spender rankings
• Uncovered spending-behavior insights (e.g. consistent overspending in Travel & Shopping vs. stable Rent) purely through SQL-driven analysis
• 🔗 Repo

Django Python HTML5 CSS3 JavaScript SQLite Bootstrap

• Built a full-stack Django holiday planning and booking platform covering destinations, hotels, transport, packages, and bookings
• Implemented a multi-service search experience (flights, hotels, trains, buses, cabs, packages) with live filtering, sorting, and an interactive trip checklist progress bar
• Added user auth (signup/login/remember-me) with private booking history, plus a custom management command to auto-seed demo data for quick setup
• 🔗 Repo

Django Python HTML5 CSS3 SQLite

• Built a Django email-simulation platform on the MVT architecture, replicating core webmail functionality
• Implemented a custom user model (instead of Django's default) for greater flexibility in authentication and future scaling
• Delivered inbox/sent message views and full send-receive messaging logic with a clean, modular app structure
• 🔗 Repo

HTML5 CSS3

• Designed a gym-themed static landing page from scratch to practice core frontend fundamentals
• Built a navigation bar, hero section, and a membership registration form with custom styling, hover effects, and layout techniques
• 🔗 Repo

• 🎮 Rock-Paper-Scissors — JavaScript game with live demo

  

• ⭕ Tic-Tac-Toe — Classic game implementation

• ✅ Selected for KSCST 49th Series Student Project Programme (2025–26) — a competitive state-level engineering research initiative — for the DEEPSHIELD AI project
• 📄 Co-authored: "DEEPSHIELD AI: Deepfake Detection Using CNN-LSTM Architecture" — International Research Journal of Modernization in Engineering, Technology and Science (IRJMETS), 2025
• 🥇 Awarded 1st Prize at College Project Exhibition for DEEPSHIELD AI, selected among 15+ technical project entries

• Google UX Design Professional Certificate — Coursera
• Responsive Web Design Certification — freeCodeCamp

Bachelor of Engineering (B.E.) in Artificial Intelligence & Data Science Angadi Institute of Technology and Management, Belagavi, Karnataka 2022 – 2026 | CGPA: 7.9 / 10