arrow left Back to Flight Tracking

Predictive Aviation Data and
The Power of Machine Learning

About this Webinar

With 15 years of aviation data and deep domain knowledge, FlightAware has created advanced machine learning models that can leverage what has happened in the past to predict what is going to happen in the future. FlightAware offers the most accurate predictive Estimated On/Landing Time and Estimated In/In Blocks Time and more. Join Caroline Rodewig and Julius Ramos to learn more about how customers achieve increased awareness, improved operational efficiency, and the assurance of a platform shared with all the largest players in the aviation industry.

What You'll Learn

  • Real-world examples of how better predictions can create operational efficiencies, which may yield cost-savings or produce revenue-generating opportunities
  • The data sources that go into our data processing platform
  • An introduction to how our machine-learning models work
  • Detailed charts showcasing how our predictive data is more accurate than data produced from legacy methods
  • Available data delivery options

The Speakers

Webinar-headshot-Caroline-Rodewig

Caroline Rodewig
Senior Software Engineer, FlightAware

Caroline Rodewig has been working as a Software Engineer at FlightAware for three years. As lead for the Predictive Technology Crew, she works to expand the scope and quality of FlightAware's predictive applications.

Webinar-headshot-Julius-Ramos

 

Julius Ramos
Aviation Sales Executive, FlightAware 

Julius Ramos has 12 years of aviation experience, primarily in the business aviation sector. This past year, he was recognized by the National Business Aviation Association as a “Top 40 Under 40”, young professionals that are making an impact in the industry. Even though Julius has been a member of FlightAware’s data integrations team for only one year, he is already discovering the breadth of use cases in which flight tracking data can be applied.

Webinar On-Demand:

Submit your contact information below to view the webinar

Duration: 60 minutes