AI Developer with strong expertise in architecting intelligent systems and scalable AI applications using Python, Machine Learning, and Deep Learning frameworks. From data preprocessing → model development → API integration → deployment, I build complete production-ready AI solutions that transform complex datasets into strategic insights and automation-driven systems. Driven by innovation, system design thinking, and practical implementation.
Aspiring AI/ML Engineer and Full-Stack Developer with growing expertise in machine learning, data analytics, and system architecture. I specialize in building end-to-end intelligent solutions — from data preprocessing and model development to deployment and interactive dashboards. With a commitment to designing production-ready systems, I transform complex data into impactful, real-world applications.
ML, DL, NLP & RAG
Scalable web & data platforms
Strategic problem solving
Production AI solutions
A fast, cross-platform healthcare application prioritizing early disease detection. Built with Flutter and Node.js, it analyzes clinical metrics and patient history through an XGBoost machine learning model to provide real-time Coronary Heart Disease risk assessments and automated preventive advisories.
A masterfully crafted educational intelligence platform prioritizing administrative efficiency. Built with Python and Streamlit, it seamlessly processes 1,500+ student records, tracks attendance heatmaps, and detects at-risk students to provide instant, actionable academic insights—all powered by an embedded zero-config SQLite database.
A robust IoT safety platform prioritizing industrial worker protection. Built with Arduino (C/C++) and a cross-platform Flutter app, it utilizes multi-sensor telemetry to actively detect toxic gases, fire hazards, and potential collisions—providing instant, life-saving alerts and enterprise-scale oversight.
A Streamlit-based app that allows users to extract, vectorize, and query news articles using LangChain, FAISS, and Hugging Face. Find insightful answers using a QA model.
A browser‑based dashboard that ingests large CSV datasets (11,000+ rows) to deliver instant KPIs, interactive visualizations, and a machine‑learning‑inspired late‑delivery predictor. Built with vanilla JavaScript and Chart.js, it simulates XGBoost‑style risk scoring with 94% accuracy – no backend required.
A fast, browser-based navigation platform prioritizing driver safety. Built with Vanilla JS and Leaflet.js, it analyzes accident-prone zones, weather, and emergencies to provide instant, secure route guidance—all without requiring a backend.
NLP: T5-based text-to-text summarization; 80% compression.
Speech: Real-time STT engine optimized for accessibility.
Style: VGG19 pipeline utilizing Gram Matrices for artistic fusion.
Generative: GPT-2 fine-tuning with Top-K/P optimized creative generation.
System: Built an end-to-end AI platform from data to deployment.
ML Models: 92% accuracy CHD risk assessment via XGBoost.
Backend: Built a Node.js API bridging MongoDB and Flutter.
Frontend: Scaled a Flutter UI for real-time health visualization.
Completed a comprehensive 14-year academic tenure (K-12) at Brindavan Matriculation, culminating in graduation with a focus on Bio-Maths and Analytical Sciences.
Pursuing an intensive academic foundation in AI & Data Science. Focused on mastering core competencies of Machine Learning and Data Analytics to drive technical excellence.
Open for AI/ML Internships & Projects
sathxsh57@gmail.com
Open to Global Opportunities (Remote Friendly)