Computer Science Projects | Anuranan Bharadwaj

3D Interactive Airport Scene (Three.js)

Three.js WebGL JavaScript OrbitControls Raycasting

Engineered a fully interactive 3D airport environment from scratch using Three.js / WebGL — modeling a complete aircraft (fuselage, wings, engines, landing gear), hangar, fuel truck, baggage carts, and light poles with real-time cast and received shadows.
Architected a dual-camera system with seamless switching between orbit overview and WASD first-person navigation; layered in raycasting for click-driven interactions — toggling individual light poles and animating the hangar door open/close.
Designed a production-grade multi-light pipeline (directional, point, and spot lights with 2048×2048 shadow maps), a looping fuel truck animation, sine-wave beacon lighting, atmospheric fog, and tarmac/grass texture mapping for visual depth.

Python NumPy MNIST Backpropagation ReLU / Softmax

Engineered a complete two-layer feedforward neural network using NumPy only — deliberately avoiding ML frameworks to hand-derive and deeply understand every forward pass, gradient, and weight update from first principles.
Designed a 784 → 10 (ReLU) → 10 (Softmax) architecture and trained it on 42,000 MNIST digit images, holding out 1,000 samples for unbiased evaluation; manually implemented backpropagation, one-hot encoding, and gradient descent.
Achieved ~89% training accuracy in 500 iterations at α = 0.1, validating correctness of every numerical derivative and confirming the network learned meaningful digit representations from scratch.

Python Pandas Matplotlib RSI Bollinger Bands

Engineered a Python backtesting engine for simulating high-frequency trading strategies combining RSI momentum signals, Bollinger Band mean reversion, and configurable stop-loss/take-profit logic.
Ingested and processed millisecond-resolution tick data from CSVs, computing rolling statistics and trade signals across thousands of data points using Pandas.
Delivered quantitative performance insights via Sharpe ratio analysis, drawdown tracking, and parameter sweeps — visualized through multi-panel Matplotlib dashboards for rapid strategy evaluation.

JavaScript Firebase Firestore QR Code HTML / CSS

Architected a full-stack QR-based attendance platform enabling professors to generate dynamic, time-expiring QR codes for fraud-proof student check-ins — eliminating proxy attendance entirely.
Built the frontend in JavaScript / HTML / CSS and powered the backend with Firebase Cloud Functions and Firestore, delivering sub-second session validation and real-time dashboard updates for professors.
Reduced attendance logging to under 30 seconds per session with 100% submission accuracy, cutting manual entry time by 90% and giving instructors instant visibility into live class attendance.

Java OOP CLI

Architected a modular pharmaceutical inventory management system in Java, applying OOP principles — encapsulation, inheritance, and polymorphism — to cleanly separate stock, supplier, and transaction logic.
Automated multi-step financial calculations and inventory updates, cutting input errors by 15% and boosting processing speed by 25% over the manual workflow it replaced.
Delivered real-time stock tracking and restocking visibility, giving pharmacists instant insight into inventory levels and measurably streamlining day-to-day business operations.

C# .NET WPF

Engineered a WPF desktop application in C# / .NET that statically analyzes Java codebases and surfaces actionable complexity metrics — LOC, class counts, inheritance depth, and conditional branching.
Built a structured analysis pipeline that processes 10+ Java files in seconds, extracting and visualizing code quality indicators to drive informed refactoring decisions.
Reduced manual code review time by 25% and improved analysis accuracy to 90%, replacing error-prone line-by-line inspection with automated, reproducible metric reporting.