The air transportation industry plays a crucial role in our global society. It provides rapid, reliable, and efficient transportation over long distances, connecting cities, countries, and continents. This industry is vital for various sectors such as tourism, business, and international trade, enabling economic growth and cultural exchange. It’s a realm where innovation and agility meet, creating a growing environment that continually pushes the boundaries of what’s possible.
Guiding this journey of innovation is a visionary leader, Gabriel Mesquida Masana, whose expertise and dedication stand as pillars of progress within the domain of air mobility. Holding the esteemed position of Chief Product Owner of ATM Twin, Gabriel’s career path epitomizes a constant pursuit of excellence, marked by a deep-rooted commitment to embracing technology for the betterment of air transportation. His desire to explore the intersection of digital transformation and air mobility underscores a visionary approach that resonates throughout his endeavors.
Gabriel’s innovative work takes place at AIR Lab, powered by Thales and CAAS, creating innovation at the intersection of technology and air transportation. Thales AIR Lab is not just a firm; it is a hub of technological excellence and innovation in the field of air transportation. Within this collaborative ecosystem, Gabriel’s contributions resonate, driving forward the frontiers of air traffic management and paving the way for a future defined by unique possibilities and inventive achievements.
Let’s explore Gabriel’s pioneering journey in air transport:
Leading Innovation in Air Transportation
Gabriel’s journey began with a fascination for air transport. With a background in technological engineering, he has always been captivated by enabling technologies and their value for business. He has had the fortune to lead a variety of projects in several countries, gaining a comprehensive understanding of air transportation.
Embracing New Technologies in Air Mobility
Over time, Gabriel’s career has evolved towards new technologies and their application to air mobility, including cloud, open source, and artificial intelligence. His interest in Digital Twins was a logical progression. In a safety-critical environment like air traffic management, the ATM Twin accelerates innovation, enables prototyping, and provides access to previously unavailable data.
This data can now be utilized to gain deeper insights into the processes that guide the air traffic control business, to develop features for training machine learning models, or to review past situations leading to human learning.
Balancing Agile Methodologies with Long-Term Vision
Innovation, for Gabriel, requires thinking outside the box and aspiring to create something new. However, with technology, it’s easy to fall into the trap of the latest novelty. He believes it’s important to provide a vision—a set of principles—that can bring order to a complex and turbulent problem.
He strives to connect the dots and find a pattern that makes sense in the long term. This can be challenging to align with agile methodologies, which focus on short-term sprints that can last three or even two weeks. His focus is to clarify the vision for both external and internal stakeholders. He draws roadmaps.
Innovation through Integration
In the realm of integration and software, Gabriel believes that the best code is the one that doesn’t need to be written. He asserts that creativity should not be focused on creating elements that already exist. Instead, one should start with the state-of-the-art, innovative, and successful solutions that are changing the world.
The effort should then be focused on combining these existing elements into innovative system architectures that bring forth solutions that did not exist before. While there is a phase of technological effort, as innovations take shape, they must have an operational focus. They must solve problems within the domain.
Balancing Technology and Business
In Gabriel’s view, a good and innovative solution will exist at the intersection of what is technologically feasible and what provides value in the business domain. This requires the collaboration of very different expert profiles, and it necessitates that this collaboration be balanced.
If the tech experts dominate too much, there is a tendency to veer towards excessively complex solutions that do not solve problems. If it is only the domain, the result is slow and incremental change. People need to collaborate, face-to-face if possible, and find common ground.
Continuous Learning
In the field of technology, Gabriel believes that one must continuously learn. This learning should encompass both a theoretical stream of incoming knowledge and hands-on experience.
He acknowledges that theory may not be in vogue but insists that there’s no other way to understand technologies like machine learning or even to ensure the reliability of a system. These are mathematical problems. All the theory would be useless without its implementation. If one is far away from code, they don’t understand code.
The Role of ATM Twin
The ATM Twin is a key contributor to Gabriel’s work. By making the technical work reusable to some extent, it facilitates economies of scale in research and allows the focus to be on the business side of prototyping, data analysis, and learning. Otherwise, the technical effort required to transition from one experiment to another demands such a significant amount of technical and managerial effort that it detracts from adding business value.
Creating Value through Data-Centric Platforms
In the realm of Digital Twins, which is the realm of data-centric platforms and technology innovation, Gabriel believes that one needs to have a thorough understanding of both the state of the art of technology and its domain. This understanding enables one to find the intersection where value can quickly be produced by experimenting. His advice is to know both streams well and start with small experiments, with demos, that show that value can be created. Then, scale it up.
The Future of AI in Air Traffic Management
In the future, Gabriel will see a lot of artificial intelligence coming into the air traffic management domain. Tools like the ATM Twin are the only enablers, but there will be a need to work, especially to think a lot about extracting value from the data that is now available. The domain is very specialized, not attracting the interest and efforts invested in other domains such as language understanding or image generation.
Yet, those techniques being developed for them can potentially be applied in the air mobility domain. At the same time, technology has many limitations in a safety-critical environment. The key is to figure out a feasible path to follow. He sees himself as contributing to shaping that path.
