This interview took place at the Deep Learning Summit, Boston 2017.
RE•WORK spoke with Sam to find out his opinions on the following questions:
- Tell us a bit about what you’re doing at Freebird.
- What inspired you to use deep learning in the travel industry?
- What has been one of the largest barriers that you’ve had to overcome during the development of Freebird?
- What other applications of deep learning are you most excited for?
- What do you think is the most interesting area of Deep Learning research today?
Sam is the CTO and co-founder of Freebird. As part of his role, Sam leads the data science team developing the data systems and predictive analytics that power the Freebird travel intelligence and rebooking solution. Freebird dynamically predicts the impact of flight disruptions and the expected rebooking costs, by leveraging a diverse range of data science, statistical analysis, and machine-learning techniques. Sam has extensive experience in the commercial application of machine-learning algorithms. Prior to this, Sam worked as a quantitative risk analyst in the currency markets and as a team lead automating a large-scale data classification problem for an energy intelligence company. Sam is a Duke University graduate and works on a grant with MIT’s Computational Cognitive Science group to extend decision theory using advancements in machine learning and artificial intelligence.