Profile
Aerospace Engineer, Data Scientist, and Software Engineer with 10+ years of experience applying machine learning and AI to solve complex engineering challenges. Ph.D. in Aerospace Engineering with a strong background in predictive modeling, stochastic processes, and advanced analytics. Proven track record leading cross-functional teams and delivering data-driven solutions in the aerospace and tech sectors, including roles at Aireon, Airbus, and Pace. Skilled in building scalable ML systems, driving strategic innovation, and translating data into actionable insights. Certified in Microsoft Azure Fundamentals. Multilingual and adaptable, with international experience across the US, Italy, Germany, and the UK.
Education
Ph.D. in Aerospace Engineering
2014 to 2017 at Politecnico di Torino, Turin, Italy
Master's in Aerospace Engineering
2010 to 2012 at Politecnico di Torino, Turin, Italy
Experience
Aireon LLC
McLean, USA (Remote)
Manager of Modeling & Analysis/Data Science
From July 2024 to present
- Led and managed a cross-functional team of data scientists, analysts, and engineers to deliver impactful data-driven insights and advanced modeling solutions supporting Aireon's global air traffic surveillance system
- Engaged regularly with customers to identify their needs and drive the requirement definition for new products and features
- Oversaw the development, implementation, and optimization of predictive models and algorithms for air traffic operations, flight tracking, and real-time data analysis, enhancing situational awareness and decision-making for air navigation service providers
- Collaborated closely with engineering, product, and operations teams to define business requirements and translate them into actionable analytical models and algorithms
- Drove the adoption of machine learning, deep learning, and statistical modeling techniques to improve forecasting, anomaly detection, and predictive analytics capabilities
Senior to Principal Data Scientist
From Sep 2020 to June 2024
- Technical Lead for Aireon INSIGHTS product family. Led prioritization, product architecture design, and development for the team
- Led several analytics projects from architecture design to prototyping and productization to serve several customers globally
- Developed near-Real-Time monitoring solution to track anomalous behavior of 737MAX fleet, approximately 700 planes. Solution informed FAA of potential risks during reintroduction of the fleet to service globally
- Interfaced with critical customers for gathering of requirements to guide solution design and development; informed on project status
- Mentored 5 junior team members
Universal Hydrogen Co.
USA (Remote)
Independent Contractor
Sep 2020
- Developed mathematical model and implemented solution for the optimization of hydrogen production and distribution network
- Gathered input datasets for example customer airlines and produced solution reports to drive definition of the hydrogen supply network based on potential customer operations
Airbus Defence and Space GmbH
Munich, Germany
Data Scientist
From May 2018 to Aug 2020
- Managed project for the development of predictive analytic products with external partner that led to a join development of cloud base trajectory prediction models to power ATFM platforms
- Developed and implemented live analytics on real-time ADS-B surveillance data to provide actionable insights to aviation stakeholders, with the purpose of increasing situational awareness and improving airspace efficiency, as we all designed and led the development of a hybrid real-time/historical app to provide customers with the ability to analyze the generated insights
- Responsible for the development of optimization products and technology scouting for advanced optimization capabilities that led to the development and implementation of mathematical models, population-based optimization, and quantum annealing algorithms for optimization of airport operations to ensure fast disruption recovery
- Participated in the ideation and evaluation process of business ideas within the Future Applications business incubator, as we as promoted interfacing among internal stakeholders for joint development of product roadmap
Pace Revenue Management
London, UK
Data Scientist
From Feb 2017 to Apr 2018
- Developed bespoke statistical models and utilized control-theory to solve the demand forecast and optimize prices within the hospitality industry. Algorithm developed increased sales by 30% and revenue by 20% YoY for Pace's most active client
- Collaborated closely with Technology and Product teams for support and code productization
- Developed Data Science testing infrastructure consisting of a request generator, Monte Carlo-based simulator, and a light dashboard mimicking production (based on Dash) resulting in faster ability to develop, test, and release new algorithms more reliably
Georgia Institute of Technology, Air Transportation Laboratory
Atlanta, GA, USA
Intern
From Sep 2015 to Aug 2016
- Developed mathematical models and algorithms for optimization of airport taxi operations
- Supervised student team during development of project “Just in Time - Concept for Improved Airport Operations”; received 3rd place at 2016 Airport Cooperative Research Program (ACRP) University Design Competition in Airport Operations & Maintenance Challenge
Certifications
Skills
- AI/ML
- Data Science
- Team Leadership
- Storytelling
- Architecture Design
- Customer Engagement
- Python
- SQL
- Scala
- Docker
- Kubernetes
- Azure
- Statistical Modeling
- Time Series Analysis
- Forecasting
- Anomaly Detection
- Predictive Analytics
- Deep Learning
- Data Visualization
- Optimization
Projects, Ph.D. Research
- Developed a Flight Management System for the realization of 4D trajectories with low impact on current airplane avionic systems, consisting of a 4D trajectory optimization algorithm and interface between the trajectory optimization algorithm and existing airplane autopilots
- Developed simulator and control strategy for a wind turbine with variable blade twist for maximization of energy production, within the VENTURAS project. Deployed the control system on BeagleBone board and designed test campaign for technological demonstrator
- Designed a management system for a fleet of unmanned pushback tractors for airport taxi operations, implementing strategic scheduling techniques to assign optimal trajectories of taxi operations for arriving and departing aircraft in the subsequent hour. Overall goal was to minimize tractor consumption and reduce the environmental impact of airport ground handling, resulting in cost savings of 40-80% of the current cost to operate airplanes on the ground, depending on airport size.