Hello, my name is
Pioneering the future with Generative AI and intelligent systems. As a GenAI Engineer and Data Scientist, I architect AI-driven solutions that transform complexity into innovation, powering next-generation applications and intelligent automation.
About Me
Hello! I'm Matteo Pasotti, a passionate GenAI Engineer and Data Scientist with a strong focus on cutting-edge artificial intelligence. My journey began with curiosity for neural networks and has evolved into pioneering Generative AI solutions for enterprise applications.
With a Bachelor's in Computer Science and a Master's in Data Science, I've built expertise spanning from traditional software development to advanced AI systems. Currently at Cluster Data Reply, I specialize in Azure-based GenAI solutions, while my previous role at Zucchetti involved leading R&D initiatives and digital transformation.
My approach to AI development is guided by three key principles:
When I'm not architecting AI systems, you'll find me at the gym, running, tending to my bonsai, or exploring the latest developments in machine learning. I thrive in collaborative environments where innovation meets practical application. Let's shape the future with Generative AI! 🚀
My Work
Enterprise-grade virtual assistant for pharmaceutical product information using advanced RAG architecture. Integrates FAISS vector database with OpenAI models to provide accurate, context-aware responses based exclusively on proprietary reference documents for pharmaceutical products.
Innovative GenAI application developed during OpenAI Hackathon that generates personalized elementary school lessons using advanced GPT models. Features multimodal output with text-to-speech integration for English, Math, and Science subjects, creating immersive learning experiences.
Advanced multi-modal bird species analysis system combining computer vision and audio processing. Implements deep learning for image classification, audio recognition, and similarity-based retrieval with interactive visualization tools for wildlife researchers and conservationists.
Comprehensive marketing analytics platform combining customer segmentation, churn prediction, sentiment analysis, and market basket analysis. Implements multiple machine learning models to provide actionable insights for data-driven marketing strategies.
Multi-approach SMS spam detection system implementing traditional ML, deep learning with LSTM, and transformer-based models with BERT. Features comprehensive text preprocessing, topic modeling, and achieves 99% accuracy through advanced model optimization techniques.
Comprehensive study of transformer-based models (BERT, RoBERTa, DistilBERT, ALBERT) for detecting sarcasm in social media content. Integrates advanced sentiment analysis using VADER and RoBERTa for enhanced contextual understanding and nuanced language detection.
Academic & Professional
To be submitted at Recent Advances of Natural Language Processing 2025
Issued: October 2025
Expiration Date: October 2026
Issued: July 2025
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Issued: July 2024
Issued: June 2022
2024
Participated in a data hackathon focused on advanced media analytics and entertainment data science solutions.
2024
Participated in a comprehensive data science challenge focused on football analytics, player performance optimization, and sports data insights.
February 2023
Developed innovative GenAI applications using cutting-edge OpenAI technologies and advanced prompt engineering techniques.
Developed advanced machine learning solutions using the KNIME Analytics Platform for complex data analysis challenges.
Academic Background
Specialized in advanced machine learning, deep learning, and AI applications
Thesis: "Watermarking Techniques in LLMs"
Conducted cutting-edge research on embedding and detecting invisible watermarks in AI-generated text, developing novel techniques to identify content created by large language models while maintaining text quality and robustness against adversarial attacks.
Focus on software development, algorithms, and AI fundamentals
Thesis: "Classification of Process Traces by Deep Learning"
Explored deep learning interpretability by analyzing neural network decision-making in process classification, developing techniques to decode the "black box" nature of neural networks and improve transparency in machine learning models.
Professional Journey
Pioneering Generative AI solutions using Azure ecosystem for enterprise clients. Specialized in developing cutting-edge AI evaluation systems, multi-agent architectures, and intelligent automation platforms.
Key technologies and responsibilities:
Led the company's digital transformation, spearheading the transition from traditional management software to modern web architectures. Pioneered AI integration as a competitive differentiator in enterprise software solutions.
Key achievements and responsibilities:
My Expertise
Get In Touch
If you have other requests or questions, don't hesitate to use the form or contact me through the channels below.
Voghera, Italy