Computer Science graduate shipping AI-powered automation, REST APIs and full-stack products — two internships deep, with a track record of pipelines that replace manual work with reporting people actually trust.
Scroll↓Two internships across enterprise automation and dealer-facing AI tooling — building the parts that quietly keep reports, releases and reviews on time.
Personal builds — RAG systems, agri-tech ML, fintech risk engines and embedded prototypes made outside the day job.
AI-powered smart study companion turning PDFs, DOCX and TXT files into an interactive learning assistant, with semantic search over FAISS and Sentence Transformers for context-aware Q&A.
Integrated Groq LLaMA-3.1-8B for summarization, quiz and flashcard generation, plus a HuggingFace TTS podcast generator for conversational audio summaries.
Agricultural advisory platform predicting soil health and recommending crops/fertilizers with LightGBM at 82% accuracy, alongside an EfficientNet crop-disease classifier at 88% validation accuracy.
Backend on FastAPI and Supabase; responsive frontend in React and Node.js; ensemble-learning yield prediction model.
Portfolio management system with an ML-driven stock risk assessment engine over historical market indicators and an NLP sentiment pipeline for financial news.
Real-time market data via the yFinance API for dynamic portfolio tracking, on a FastAPI + React stack.
A run of embedded prototypes: ESP32 smart irrigation, ESP8266 smart parking, an Arduino firefighting robot and a glove-based gesture controller.
Hands-on sensor-to-firmware work that grounds the software with real hardware constraints.
Tools reached for daily, grouped by where they sit in the build.
Formal education plus the certifications picked up along the way.
