Hi, I'm Bruno Guzzo 👋

I am a Systems Engineer at AWS (Dublin), working within the Managed Operations team since April 2026.

I am passionate about Linux, Cloud, SWE, DevOps, AI/ML (NLP, Anomaly Detection, Time Series), and Finance. I use this profile to share personal projects and ideas; feel free to reach out for collaboration.

1. [In Progress] - Fin-FFB: A finance-specialized BERT-like embedding model designed to embed large documents on consumer-grade hardware. It leverages recent NLP advancements to implement a fat and shallow architecture, bypassing the context size limitations of common models like Mini-LM.
2. [Coming Soon] - Fin-PT: A financial pre-trained transformer model designed to apply GPT architectures to predict the next OHLC data point for a given ticker history.

1. Italian-LLaMA-Project: Fine-tuned the 8B LLaMAntino-3 model for Italian proficiency using 4-bit quantization and LoRA. Implemented a complete RAG chatbot system using LangChain and FAISS.
2. MSc Thesis: Semi-Supervised Anomaly Detection: A rigorous experimental analysis of undersampling techniques (e.g., ENN, NCR, and Tomek Links) to improve the performance and efficiency of Auto-Encoders for semi-supervised anomaly detection.
3. Transformer-GNN for Link Prediction: Designed and built a custom, deep Graph Neural Network (GNN) inspired by the Transformer architecture. Trained from scratch on a custom 7-million-node dataset (crawled from Wikipedia) for semantic link prediction.
4. Anomaly-Transformer-Analysis: A deep-dive implementation and comparative analysis of the "Anomaly Transformer" paper, benchmarking its novel Anomaly-Attention mechanism against standard self-attention for time-series anomaly detection.

• Email: brunoguzzo18@gmail.com
• LinkedIn: brunoguzzo
• Instagram: _brunoguzzo
• GitHub: bGuzzo
• Hugging Face: bguzzo2k
• Resume: Bruno Guzzo CV