# Aakash S S - AI & Machine Learning Engineer

> Official AI, Machine Learning Engineer, and Data Scientist portfolio for Aakash S S. Specializing in Deep Learning, Computer Vision, MLOps, NLP/RAG architectures, and predictive analytics.

## Quick Facts
- **Name**: Aakash S S
- **Role**: AI & Machine Learning Engineer / Data Scientist
- **Location**: Chennai, Tamil Nadu, India
- **Education**: B.Tech in Computer Science and Engineering (Artificial Intelligence & Data Science) at Vel Tech University (CGPA: 7.97)
- **Status**: Open to full-time AI/ML Engineering roles, Data Science opportunities, and research collaborations
- **Website**: https://aakash1552005.github.io/
- **GitHub**: https://github.com/aakash1552005
- **LinkedIn**: https://www.linkedin.com/in/aakash-s-s-88b91a301
- **Email**: aakash1552005@gmail.com
- **Phone**: +91 88259 09003

## Core Technical Competencies
- **Machine Learning & Deep Learning**: TensorFlow, Keras, PyTorch, Scikit-learn, XGBoost, LightGBM, Random Forest, CNNs, ResNet, MobileNet, LSTMs, Neural Networks, Transfer Learning
- **Computer Vision**: OpenCV, Object Detection, Image Classification, Semantic Segmentation, Real-time Camera Inference
- **NLP & Generative AI**: Retrieval-Augmented Generation (RAG), LangChain, Hugging Face Transformers, Tokenization, LLM Fine-Tuning
- **MLOps & Cloud**: Docker, Kubernetes, FastAPI, Flask, MLflow, CI/CD, Git, GitHub Actions, Linux
- **Data Engineering & Analytics**: Python, Pandas, NumPy, SQL (PostgreSQL, MySQL), Power BI, DAX, Seaborn, Matplotlib

## Featured Projects & Benchmarks
- **Telco Customer Churn MLOps Platform**: Production-ready MLOps system featuring **0.847 ROC-AUC**, recall improved from **48% → 80%** through threshold tuning, automated CI/CD, MLflow experiment tracking, Docker/Kubernetes deployment, and drift-aware retraining.
- **TN Government AI Scheme Assistant (TNGov-AI-Assistant)**: Bilingual (English/Tamil) RAG assistant for citizen welfare scheme discovery achieving **86/86 validation tests passed** and **100% pass rate on a 50-query benchmark** using Groq LLaMA 3.3, ChromaDB, and FastAPI.
- **AI-Based Smart Garbage Segregation Bin**: Edge computer vision and IoT system delivering real-time **5-category waste classification** with sensor-based fallback logic using Arduino, ESP32-CAM, Flask, and TensorFlow.
- **Autonomous Data Analyst (ADA)**: Enterprise-grade multi-agent tabular intelligence and AutoML system orchestrating **7 specialized autonomous agents**, delivering **100% verified numerical grounding**, zero arbitrary code execution, automated executive PDF/PPTX reports in under 25s, and a **590-test suite passing at 100%**. Live Cloud Demo: https://autonomous--data--analyst.streamlit.app/ | Repository: https://github.com/aakash1552005/Autonomous-Data-Analyst

## Professional Experience
- **AI & Embedded Systems Intern** at **AICTE** (May 2026 – Jul 2026): Designed AI-powered software and embedded solutions: built a 5-category waste segregation classifier (97.76% validation accuracy) via MobileNetV2 with ESP32-CAM and sensor fallback, and engineered a cloud predictive AI platform (Next.js, Supabase, Vercel) tracking child malnutrition risk.
- **Data Scientist Intern** at **RINEX Technologies, Bangalore** (Sep 2025 – Nov 2025): Developed end-to-end data preprocessing, EDA, feature engineering, predictive models, and model evaluation on business datasets; translated insights into Power BI and DAX dashboards.

## Certifications
- **Infosys Springboard** — Exploring Data Visualization (Feb 2026)
- **RINEX (Google for Education Partner)** — Artificial Intelligence (Nov 2025)
- **RapidMiner (Altair)** — Data Engineering Master Certification (Nov 2025)
- **Deloitte** — Data Analytics Job Simulation (Sep 2025)
- **Tata Group** — Data Visualisation: Empowering Business with Effective Insights (Sep 2025)
- **Infosys Springboard** — AWS Solutions Architect: Security & Data Privacy (Apr 2025)
- **NVIDIA** — Introduction to Networking (Apr 2025)

## Primary Documents & Endpoints
- Portfolio Website: https://aakash1552005.github.io/
- Resume PDF: https://aakash1552005.github.io/Aakash_SS_Resume.pdf
- Full LLM Context: https://aakash1552005.github.io/llms-full.txt
- Sitemap: https://aakash1552005.github.io/sitemap.xml