A smart fashion web app built with Python (Flask) that recommends personalized outfits based on user profiling and AI analysis. It includes features like real-time virtual try-on with OOTDiffusion, skin tone & demographic detection using DeepFace, and outfit recommendations powered by TensorFlow, Gemini API, and PyTorch.

NLP-powered personality analyzer that matches your writing style to iconic French thinkers and artists using semantic embeddings

An agentic LLM pipeline for high-fidelity literary translation, featuring automated stylistic profiling and context-aware chapter translation via Gemini API.

Reverse-engineer any author's writing style from samples, then write in their voice. 24-dimension forensic style analysis.

Analyzes and mirrors writing styles through an HTML interface with conversation examples.

End-to-end reproduction pipeline for the contempArt ECCV 2020 paper (VGG-19, Gram textures, archetypal analysis, social network)

StyleSense is a full-stack fashion personalisation prototype that uses AI and behavioural data to deliver uniquely tailored shopping experiences. In 30 seconds — via a 4-question style quiz — it builds a complete style vector for a user and uses that to rank products, suggest outfits, and provide personalised AI fashion advice in real time.

An AI-driven garment swing line planning and style analysis system built with Laravel that compares garment styles, generates similarity matrices, automates line loading sequences, and optimizes factory production efficiency by reducing machine changeover and improving workflow stability.

Analyze and profile writing styles in German and English text using local LLMs. Privacy-first, 100% local processing.

Translate books with Gemini API using an agentic NLP pipeline for high-fidelity literary translation and controlled LLM workflows