Tommaso Rescio

Led advanced technical support for enterprise security solutions, ensuring high reliability and performance for critical customer environments.

• Resolved complex network and infrastructure issues for enterprise customers by troubleshooting Cortex XSOAR deployments, leveraging systematic root cause analysis to ensure operational stability.
• Architected and developed resilient Python integrations with third-party security APIs, implementing Prometheus/Grafana observability and fault-tolerance patterns that reduced MTTR by 30% and maintained 99.9% service reliability across distributed security platforms.
• Engineered real-time observability dashboards with custom alerting thresholds, reducing incident investigation time by 25% and establishing robust SLO tracking for critical customer environments.

Provided expert-level technical support for Google Cloud Platform Networking products, resolving complex customer issues and driving platform reliability.

• Delivered expert-level technical support and troubleshooting for Google Cloud Platform (GCP) Networking products, resolving complex customer issues and consistently achieving a 95% customer satisfaction rate.
• Conducted in-depth root cause analysis to swiftly identify and resolve critical networking problems, significantly improving overall platform reliability and performance.
• Consulted internal stakeholders to effectively resolve complex technical challenges, driving key improvement initiatives and optimizing operational processes within Google Cloud.

Conducted advanced research in network security, developing innovative systems for threat detection and traffic analysis.

• Designed and implemented an advanced honeypot system, enhancing threat detection capabilities by 60% and significantly improving overall network security posture.
• Developed a real-time attack visualization dashboard using Python and Elasticsearch, providing critical insights into evolving threat landscapes for proactive defense.
• Engineered a robust network traffic analysis framework leveraging Deep Packet Inspection (DPI), enabling high-accuracy identification of advanced threats and anomalous behaviors across diverse protocols.

Awarded for outstanding academic achievement and contributions to network security research.

Research exploring novel methods for enhancing visibility into darknet activities through active probing techniques, published in a leading IEEE journal.

A comprehensive benchmark and comparison of Deep Packet Inspection (DPI) solutions, presented at an IEEE Security and Privacy Workshop.