Researched human mobility and its impact on network traffic, planning, and deployment using large-scale mobility and traffic datasets from millions of users. Used Python multiprocessing and threading, and R multicore libraries, to analyze the data.

The work produced a doctoral thesis, 5 conference papers, 2 journal papers, and a synthetic traffic simulator.

Studied how network centrality can inform routing in wireless sensor networks. Proposed topological metrics, distributed algorithms to compute them, and tree-based routing using those metrics.

The work produced a master's thesis, 1 conference paper, and 1 journal paper.

Developed a wireless-sensor application for fire detection using real weather measurements, proposing a method to combine and encode the data.

Published 1 conference paper.

• Improved the robustness, scalability, and observability of Synthesia's AI video generation platform across task scheduling, rate limiting, retries, failure classification, diagnostics, and production incident follow-ups.
• Migrated core video generation work into dedicated services and workers for video preprocessing, rendering preparation, thumbnail/GIF generation, diagnostics, and GPU rendering experiments.
• Led scaling and cost-efficiency experiments that reduced compute usage by ~56% with minimal user impact, identifying an estimated ~$800K/year in infrastructure savings.

• Implemented kernel-module signature verification and failure reporting in Canonical Livepatch 's Go client, with corresponding server-side patch-state support.
• Developed and maintained scheduled Python data workflows on Kubernetes and Argo, including PostgreSQL view management, data snapshots, and operational diagnostics.

• Developed Go services integrating Salesforce with Ubuntu Advantage contract provisioning and renewals, optimizing PostgreSQL queries and external API usage.
• Introduced Gherkin/Godog acceptance tests covering product listing, purchases, trials, upgrades, and downgrades, integrated into CI.
• Refactored Python ETL tooling that synchronized Salesforce and other business data into PostgreSQL, introducing typed interfaces, strict static checking, retries, and operational monitoring.
• Implemented request tracing across HTTP services and asynchronous jobs, and expanded Prometheus-based monitoring.

Developed Java services for BlaBlaCar's Trip Search team, covering search, routing, and matching.

• Developed the meeting-point service, combining PostgreSQL/PostGIS spatial search, machine-learning ranking, Redis integration, and R-tree caching.
• Built a geospatial crawler and ingestion tools for a meeting-point dataset containing over one million collected place records across 14 countries.
• Benchmarked JVM inference engines and built a reusable XGBoost prediction library for Java services.
• Built a reusable Java geospatial library for country and timezone resolution, polyline handling, and geohashing.
• Improved trip-search indexing and feature ingestion with streamed database reads, pipelined Redis writes, and support for driver-selected routes.
• Extended routing services with cached Google Directions queries, alternative routes from Google and OSRM, and parallel requests with retries and timeouts.

• Developed machine-learning methods to predict video-streaming quality of experience from mobile-network performance metrics.
• Co-authored a paper published at IEEE ICC 2017.

Developed TIM Beta for Telecom Italia Mobile as part of a Ruby on Rails team.

Developed Future of Enterprises, a Python project to improve real-time collaboration among employees.

Led development of a social network in Ruby on Rails.