AI and Machine Learning Projects

I am Achyuth Kumar Baddela, a Master's student in Applied Artificial Intelligence at Luleå University of Technology, Stockholm.
With over 10 years of professional experience in software testing and automation, I am now focused on applying my engineering background to machine learning, predictive analytics, and MLOps development.

My prior experience includes roles at SEB, Deloitte Consulting, and Infosys Technologies, where I specialized in automation frameworks, quality engineering, and enterprise software delivery across life sciences, retail, and financial domains.

---

Profile Summary

• Strong background in software engineering, testing automation, and CI/CD pipelines
• Currently expanding expertise into machine learning, data analysis, and model deployment
• Skilled in applying structured problem-solving and quality assurance practices to data-driven development
• Interested in AI applications in finance, automation, and real-world predictive systems

---

Technical Skills

Programming: Python, Java, SQL
AI & Machine Learning: Scikit-Learn, XGBoost, TensorFlow, Keras, Google Gemini (LLM)
Data & Vector Handling: Pandas, NumPy, Matplotlib, Seaborn, ChromaDB (Vector DB)
Automation & Orchestration: n8n, Selenium, Jenkins, API Testing
API & MLOps: FastAPI, Docker, SQLAlchemy, MLflow
OCR & Document Processing: Tesseract, PyPDF
Version Control: Git, GitHub
Methodologies: Agile, Scrum, V-Model, Waterfall

---

Focus Areas

• Predictive analytics and data-driven decision systems
• Model development and optimization using real-world datasets
• AI application development and deployment automation
• End-to-end ML workflows: data → model → monitoring

---

Featured AI Projects

1. ComplianceIntelligence

AI-Powered AML & Sanctions Intelligence System

• Tech Stack: FastAPI, Google Gemini 2.0, ChromaDB, SQLAlchemy, Tesseract OCR.
• Key Features:
  • Automated ingestion and hashing for regulatory documents.
  • Semantic retrieval (RAG) for goal-oriented compliance queries.
  • Delta Analysis: Automatically compares document versions to surface risk shifts.
  • "Mock Mode" for LLM-free development and testing.

2. WorkflowAutomation

Intelligent Email Analysis & Routing System

• Tech Stack: FastAPI, Google Gemini, n8n, Docker, SQLite.
• Key Features:
  • Real-time Gmail integration via OAuth 2.0.
  • LLM-based sentiment analysis, priority scoring, and team routing.
  • Automated workflow orchestration using self-hosted n8n.
  • Dockerized for production-ready deployment.

3. Defect Prediction

Predictive Quality Engineering for Software Modules

• Tech Stack: Python, Scikit-Learn, XGBoost, Pandas.
• Key Features:
  • Machine learning pipeline for identifying defective code modules.
  • Comparative analysis of Logistic Regression, Random Forest, and XGBoost.
  • Focus on structural (LOC) and cognitive (Halstead) complexity metrics.
  • NASA Metrics Data Program (MDP) dataset evaluation.

---

Contact

LinkedIn: https://www.linkedin.com/in/baddelaachyuth/
Email: baddela3@gmail.com
Location: Stockholm, Sweden