The Binter-ULPGC Chair aims to bring AI and robotics closer to applied research

The University of Las Palmas of Gran Canaria (ULPGC) and Binter launched the Binter Chair of Applied Research in Artificial Intelligence and Robotics on February 18, 2026. This initiative is linked to the University Institute of Intelligent Systems and Numerical Applications in Engineering (SIANI), which serves as the academic anchor for the project. Scientific and strategic direction was entrusted to Professor Mario Hernández Tejera, a key figure in computing at the institution.

The proposal is structured as a collaboration framework designed to boost applied research, specialized training, and knowledge transfer to the business sector. The stated purpose is to contribute to the Canary Islands gaining capacity in the development and use of advanced technologies. This declaration expresses a long-term institutional goal, not an immediate confirmation that the region has already become a consolidated technology hub.

The distinction between intention and result is fundamental to understanding the actual scope of the news. Creating a cooperation structure does not equate to validating a technology nor deploying it in operations. The announcement describes the activities the chair seeks to promote, but it does not, in itself, provide results from specific projects, measurable impact indicators, or systems already implemented in Binter's aeronautical activities.

ULPGC provides the academic environment, research resources, and teaching base necessary for the project's development. SIANI, as a university institute, provides the specialization framework in intelligent systems where the chair is framed. Direction rests with Hernández Tejera, Professor of Computer Science and Artificial Intelligence, according to the official institutional communication regarding its launch.

Binter participates as a business partner in an initiative that seeks to promote innovative solutions to address specific organizational challenges. The chair offers a collaboration framework that aims to bring university and business capabilities closer together through joint projects and training programs in artificial intelligence and robotics.

The Knowledge Transfer Office of the ULPGC Canary Science and Technology Park Foundation managed the agreement that formalizes this alliance. This institutional channel is crucial because it is part of the collaboration structure between the university and the business sector, and it is directly linked to the purpose of transferring knowledge to the productive sector efficiently.

The announced framework contemplates undergraduate and master's final projects, doctoral theses, and applied research projects. This combination allows the chair to link university training with practical sector problems. Potentially, this can produce results of different scales: from individual academic works to research lines that require continuity and long-term funding.

In an intervention disseminated by the Canary Science and Technology Park Foundation in July 2026, Hernández Tejera described knowledge transfer and training connected to labor market needs as central objectives. Internships, academic works, and industrial doctoral theses were also mentioned as ways to favor direct contact between students, the university, and companies in the Canary ecosystem.

The same episode pointed to the organization of days with specialists, specific courses, and Binter Awards for the best final degree projects as planned activities. There is a possibility of expanding the recognition to master's and doctoral works in the future. These are announced activities, not a balance of calls already held: to assess their real scope, specific dates, participation rules, number of registrants, and published results are needed.

The initial communication indicates that the chair will foster applied research projects and facilitate experimentation environments to work with artificial intelligence and robotics. These activities are part of the announced academic framework to boost research and the generation of specialized knowledge in the archipelago.

In practical terms, there are several stages between a research line and an operational application. These include defining a problem, developing a method or prototype, testing it under controlled conditions, evaluating its safety and reliability, and deciding if it can be integrated into a real process. The launch of the chair certifies the collaboration framework; it does not certify that those stages have been completed for a specific technology.

Caution is particularly important in the aviation sector. Binter's participation does not mean that the projects have a direct destination in air operations. The initiative covers AI and robotics in general terms and also seeks to address challenges for other organizations. To associate a development with a specific aeronautical application, project details and a description of its validation and use would be required.

To follow the evolution of the chair, it is advisable to distinguish between activity and result. Days, courses, and awards would show that programming exists; academic works, funded projects, and publications would allow knowing what research is being developed; evaluated prototypes and documented business collaborations would provide information about the step towards application.

A useful reading can be organized around four key questions:

• What has been done: activities, calls, and effective dates, versus announced plans.
• What knowledge has been produced: academic works, publications, datasets, or technical results attributable to specific projects.
• How it has been tested: evaluation methods, test conditions, and limits recognized by the responsible teams.
• What has been transferred: agreements, tools, or processes adopted by an organization, with identifiable scope and date.

The intervention disseminated in July 2026 offers a clue about priorities: continuous training, the relationship between academic capabilities and business needs, internships, and university works. To measure the impact of these priorities, comparable data over time would be needed, such as the number and type of projects, student participation, academic results, and documented examples of transfer.

The initiative has a clear institutional focus—artificial intelligence, robotics, training, and transfer—and an identifiable structure: ULPGC, SIANI, Binter, and academic direction. This profile allows understanding what it intends to articulate and who participates, without turning communication objectives into proven results.

The initiative brings together ULPGC, SIANI, and Binter around artificial intelligence, robotics, training, and knowledge transfer. Its announced agenda combines applied research and business collaboration; planned activities include days, courses, and awards for final degree projects.

For students and professionals, the initiative may be relevant due to the training and collaboration opportunities its organizers have proposed. For companies or readers evaluating its technological impact, the reasonable decision is to pay attention to identifiable projects and results, not merely the creation of the structure: there will be seen if the collaboration moves from the academic agenda to evaluated and transferred solutions.