My projects and work across different technologies and domains.
Built scalable banking exam platform with real-time analytics, achieving low-latency performance under peak traffic. Deployed on Vercel with Neon PostgreSQL and password-based authentication, increasing login success rate by 40%. Integrated Gemini AI to auto-generate 100+ questions and flashcards, reducing content creation effort by 3× and improving study efficiency by 35%.
Developed browser-based style transfer application using TensorFlow.js with 4 pre-trained models (56MB total). Optimized dual-style blending with warm-up strategies, reducing initial inference time from 3.2s to 850ms (73% improvement) and increasing user interaction by 30%.
Implemented Neural Style Transfer system in PyTorch using pre-trained VGG-19 with optimized content-style loss functions. Processed 100+ image pairs with 95% positive feedback, improving generation quality by 40% and achieving 30-second render time at 1024×1024 resolution.
Engineered high-performance matrix multiplication combining DeepMind's Algorithm and Winograd's Method, achieving 50% faster processing than standard implementations. Implemented Strassen-Winograd as base case, reducing computation time for 1000×1000 matrices from 3289ms to 791ms (76% improvement). Scaled to 4096×4096 matrices with sub-second latency without hardware acceleration.
Developed Siamese Network with 3-layer BiLSTM encoders for semantic code clone detection, achieving 97.2% accuracy on Google BigCloneBench dataset.
Built virtual 3×3 Rubik's Cube simulator with optimized data structures for real-time responsiveness. Implemented Korf's IDA* algorithm with BFS, DFS, and IDDFS strategies, achieving sub-3-second solve times for 8-move scrambles.
Design & Developed by Shivratan Choudhary
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