Advancing Aviation with Data-Driven Solutions
Consulting
R&D
Innovation
We help aviation stakeholders to optimize their operation and improve safety by leveraging data, artificial intelligence and machine learning.
Services
As a team of experts in various fields, we offer a diverse range of services aimed at optimizing and enhancing your operations while maintaining a high level of safety. Explore the services we provide below. Feel free to reach out to us for any inquiries or to discuss how we can assist you with these services. Your success is our priority.
Data, Machine Learning & AI
Optimizing or automating some parts of your operation
We can support you to understand your requirements, set up your data pipelines, and developing your models. From pattern recognition to forecasting, we are here to help you.
Collision Risk Modelling
Improving the safety of your operation
With our mid-air Collision Risk Models, we can perform a quantitative analysis of your air traffic procedures and routes, review and validate assessments of third parties or help you monitor your risks.
Analytics & Statistical Modelling
Supporting your data-driven decision process
We can support you with the data analysis to understand your operations better and with model development to predict events, demand or capacity and turn this predictions into actionable insights.
About
We have put together a special combination of machine learning, artificial intelligence to improve your operations.
We are engineers and scientists who share a common passion for aviation and data. We believe that the synergy between data and domain expertise is key for the future of aviation.
SkAI Data Services was created with the goal of helping aviation stakeholders to solve real-world problems leveraging their data.
Founders
Raphael Monstein
Raphael Monstein has a bachelor’s degree in Aviation, a master’s degree in Engineering (Business and Production Engineering) as well as a master’s degree in Data Sciences. He has been working for the ZHAW - Centre for Aviation, first as a scientific research assistant and then as a scientific research associate, for more than 10 years.
His research focus is inflight simulation and flight mechanics. He has also been working on collision risk modelling for the last five years.
Raphael enjoys solving complex technical challenges with methods from a range of different fields, from statistical modelling to mathematical optimization and more.
Benoit Figuet
Benoit holds a Master's degree in Engineering from the Grenoble Institute of Technology. He launched his career at the French Ministry of Defense - DGA. In 2016, Benoit joined the ZHAW - Centre for Aviation, serving as a scientific research associate. His research focuses on data-driven collision risk modeling and the application of machine learning for trajectory prediction. He has successfully managed multiple projects and currently leads the Sesar - Enhanced Runway Delivery solution.
Benoit lends his expertise as an advisor to the Swiss member of the ICAO Separation and Airspace Safety Panel (SASP), and is also a member of the Mathematics Sub Group.
Fascinated by the application of Data Science, Machine Learning, and Artificial Intelligence in solving real-world problems, Benoit is aspiring to advance the aviation system with SkAI Data Services.
Advisors
Xavier Olive, ONERA
Xavier also teaches artificial intelligence and advanced programming in Python to graduate students.
He is the main author of the open-source traffic Python library, and of the book Programmation Python avancée with Dunod editions.
Xavier Olive graduated from Supaero, Université de Toulouse, France and holds a PhD from Kyoto University, Japan. He is currently a research scientist at ONERA, passionate about aviation, maps and data. His research interests include Data Science, Machine Learning and Decision Science applied to aviation, with a particular focus on optimisation, anomaly and pattern detection applied to air traffic management, operations, predictive maintenance, safety analyses and risk assessment.
Dr. Steven Barry, Airservices Australia
He is Rapporteur of the Mathematics Sub Group within the ICAO Separation and Airspace Safety Panel (SASP) where he has been a driving force behind new oceanic separation standards using space-based ADS-B now being used in the North Atlantic.
Steve Barry got his degree at Adelaide University and a PhD from University of New South Wales both in Applied Mathematics.
After a postdoctoral fellowship at the University of Toronto (Mechanical Engineering) he spent 12 years researching and teaching at UNSW (Canberra), focusing on engineering applied mathematics. Steve has spent the last 10 years at Airservices Australia and leads a team developing methods for analysing and monitoring risk using aircraft trajectory data.
Trusted by
Featured Projects
Quadabra
A tool to analyze historical trajectory data, detect conflicting pairs of aircraft automatically, and quantitatively assess the probability of a mid-air collision.
Quantitative Collision Risk Model for Zurich Airport
The airspace around Zurich airport is in the process of being redesigned. We have developed a quantitative collision risk model to support the design of a safe and efficient airspace.
Live GPS Spoofing Tracker Map
Using ADS-B data from the OpenSky Network, the Live GPS Spoofing Tracker Map displays global GPS attack locations in near real-time. The tracker was featured in Wired Magazine.