Alberto Guggiola

• Led a strategic AI project supporting commercial growth, delivering actionable insights and recommendations to sales teams at the right time. • Managed and mentored a cross-functional AI team (Data Scientists, Data Analysts, ML Engineers, Data Engineers; 5+ people). • Successfully scaled deployments from 2 to 50 U.S. states, ensuring robustness, performance, and business adoption. • Drove the transition from build to run mode, establishing operational processes and long-term maintainability. • Acted as a key interface between Commercial Strategy & Transformation teams and technical stakeholders. • Tech stack: Python, dbt, Snowflake, Retool, Salesforce (SFA)

• Contributed to MyTraffic’s mission of accurately estimating road and pedestrian traffic to support retailers, cities, and real estate stakeholders. • Designed, tested, and validated advanced machine learning models to better exploit large-scale geographical and mobility data. • Worked in a product-oriented, agile environment, ensuring models delivered measurable business value. • Tech stack: Python, AWS, Clean Code practices, Agile development

• Member of the European research network NETADIS (Statistical Physics Approaches to Networks Across Disciplines). • Research focus: epidemic processes on networks, viral marketing, and optimal vaccination strategies. • Visiting researcher at King’s College London and ICTP Trieste.

Project on rare event statistics for random walks in complex networks.

Bioinformatics project about the inference of the olfactive system in the Drosophila

I developed my Master Degree Thesis in the field of the BioInformatics. In particular I studied new methods by which inferring three dimensional structures of proteins given just their linear sequences of amino acids.

I developped my Bachelor Thesis "Information spreading on dynamical contact networks”, in which I analysed which topological aspects contribute the most in determining the speedness of a diffusion on a network.