Leon Doungala | AI Engineer Full Stack | Data Scientist | Researcher

About Me

I am Leon Doungala, an Engineer specialized in AI/ML and Data Science based in Milan, Italy. With a Master of Science in Computer Engineering (AI specialization) and a Master's in Data Science, I specialize in developing innovative engineering solutions at the intersection of artificial intelligence and practical business applications.

As an AI/ML Engineer at People Lab (March 2024-Present), I've developed AI solutions for healthcare and corporate environments. My work includes creating a RAG-based Clinical Semantic Search Engine that processes over 160,000 unstructured medical referrals, and an advanced ATS system supporting HR recruiters across multiple companies. These systems leverage LangChain, Flask, Scikit-learn, PyTorch, and OpenAI's LLM APIs to deliver actionable insights.

Previously, as a Software Developer and Data Scientist at the Italian Stock Exchange (Euronext Group) (2022-2024), I collaborated with teams developing financial software applications, optimizing SQL DataMarts, and automating AWS data ingestion workflows. I contributed to data science initiatives applying machine learning models for risk assessment and financial forecasting, working within agile teams to deliver high-impact solutions.

My expertise spans predictive and generative AI, with particular focus on Large Language Models, Retrieval-Augmented Generation, Transfer Learning, and Vector Databases. I'm committed to leveraging these technologies to create scalable, efficient, and impactful AI systems that address real-world challenges, particularly in healthcare and financial domains.

Leon Doungala at a MSc in computer Engineering thesis discussion

Education

September 2022 - March 2025

Master of Science in Computer Engineering and Automation, Artificial Intelligence

eCampus University, Como, Italy

Key Coursework

Advanced Machine Learning Algorithms
Deep Neural Networks & Generative Models
Computer Vision & Image Recognition
Natural Language Processing & Large Language Models

Thesis Project

"Artificial Intelligence and Machine Learning Techniques for Diabetes Prediction and Characterization" - Developing predictive models using ensemble learning methods to identify early diabetes markers and optimize personalized treatment pathways.

April 2021 - April 2022

Double Master in Data Science

Rome Business School, Rome, Italy

|

International University of Valencia, Spain

Key Coursework

Data Science & Analytics

Advanced Data Mining Techniques
Supervised & Unsupervised Machine Learning
Statistical Modeling & Inference
Big Data Processing & Infrastructure

Business & Management

Financial Analysis & Forecasting
Strategic Management & Decision Making
Decision Science & Operations Research
Project Management & Implementation

Academic Achievement

Graduated with honors, completing a cross-institutional research project on data-driven business optimization strategies implementing machine learning solutions for real-world business challenges.

September 2015 - September 2020

Bachelor of Engineering in Electronics and Computer Engineering

University of Ferrara, Ferrara, Italy

Key Coursework

Digital Systems Design & Programming
Software Engineering & Development Methodologies
Computer Architecture & Operating Systems
Signals Processing & Communication Systems

Thesis Project

"Design and Development of a Modern Cloud-Based Web Application in Java Enterprise Edition for Radio Streaming with Integrated Deep Learning Neural Networks" - Created an innovative streaming platform with artificial intelligence-powered content recommendation algorithms and personalized user experience.

Portfolio

End-to-end AI systems — from classical ML to production RAG pipelines. Healthcare AI, semantic search, autonomous agents, and full-stack applications.

Featured work includes a RAG-powered Clinical Search Engine processing 160K+ medical records, an AI-driven ATS system for intelligent CV matching, and my M.Sc. thesis on diabetes prediction using ensemble learning and generative AI — co-authored and published in IEEE Journal of Biomedical and Health Informatics (JBHI).

My stack spans Python, PyTorch, LangChain, OpenAI/Anthropic APIs, Flask, FastAPI, React, and cloud infrastructure on AWS and Azure. Every project follows the same principle: research-grade AI, engineered for real-world scale.

Explore Full Portfolio Book a Meeting

Virtual Healthcare AI Assistant

Conversational Healthcare Guidance

An AI-powered system providing medically sound guidance based on symptoms. Incorporates dynamic medical data retrieval, conversational flows, and automated medical knowledge access.

LangChain Flask OpenAI Anthropic

View Repository Explore Code Structure

ATS System interface showing CV matching

RAG-Powered ATS System

Intelligent CV Filtering & Job Matching

An AI ATS applicant tracking system that aligns candidates with job descriptions through advanced semantic search, supporting HR teams with precision matching and intelligent filtering.

RAG LangChain Azure Cosmos DB Semantic Search

View Repository Explore Code Structure

AI/ML for Diabetes Characterization

M.Sc. Thesis Project

Applied AI and ML techniques to diabetes prediction and characterization, developing predictive models and integrative dashboards with advanced analytics for healthcare decision support.

XGBoost Random Forest K-Means LangChain

View Repository Explore Code Structure

Human Resources Analytics

Employee Segmentation & Insights

Applied PCA and K-Means clustering for employee segmentation and HR data analytics, revealing actionable patterns in workforce dynamics and organizational behavior.

PCA K-Means Pandas Scikit-learn

View Project

Heart Disease Prediction

Medical Risk Assessment

Built predictive models to analyze heart disease risks using SVM and NLP techniques, providing a robust framework for early detection and intervention strategies.

SVM NLP Scikit-learn Data Visualization

View Project

Technical Skills

Python

Java

R

C++

SQL

AWS

Machine Learning

XGBoost Random Forests SVM Decision Trees Ensemble Learning K-Means PCA Scikit-learn

Data Processing

Pandas NumPy SQL AWS Glue Azure Cosmos DB MongoDB Matplotlib Seaborn

Deep Learning & Frameworks

TensorFlow PyTorch Keras CNNs / RNNs Transformers Computer Vision NLP / NLU Diffusion Models

AI Engineering & LLMs

Agentic AI Context Engineering RAG Pipelines LangChain / LangGraph OpenAI API Anthropic API Vector Databases Prompt Engineering Tool Use / MCP Fine-Tuning LLM Evaluation Multi-Agent Systems