In this session, we present how AI-driven methods are being applied at armasuisse science and technology to perform systematic technology monitoring of emerging and potentially disruptive technologies relevant to national security.

Using large language models (LLMs) and other AI techniques, we analyze vast volumes of global scientific and technical data (e.g., OpenAlex, arxiv, and patents) to identify early signals of innovation. This includes detecting trends in cyber capabilities, dual-use technologies, and developments that may impact defense strategies. Our approach not only enhances situational awareness for decision-makers but also contributes to anticipatory threat modeling in the face of rapid technological evolution. The presentation will highlight concrete use cases, challenges in trustworthy AI adoption, and interactive visualizations that support analysts in navigating complex and evolving tech landscapes.

About the speakers

Dr. Julian Jang-Jaccard

Scientific Project Manager at armasuisse

Dr. Julian Jang-Jaccard is a Scientific Project Manager of the Cyber-Defense (CYD) Campus at armasuisse, the Swiss Federal Office for Defense Procurement. She serves as the Science Lead of the Technology Monitoring team, where she is responsible for coordinating relevant scientific activities to monitor technological and scientific developments relevant to Swiss defense operations. Prior to armasuiss, she was an Associate Professor and Head of the Cybersecurity Laboratory at Massey University, New Zealand, and a pioneering member of the Cybersecurity Research team at Commonwealth Scientific and Industrial Research Organization (CSIRO), Australia. She has published over 100 papers in prestigious venues, including IEEE and ACM, and received numerous multimillion-dollar research awards while collaborating with top ICT companies and universities worldwide. Julian holds M.Sc. and Ph.D. degrees from The University of Sydney, Australia, in 2002 and 2007, respectively.
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Paul Bagourd

Graduate Intern at Cyber Defense Campus (Armasuisse S&T)

Paul Bagourd is an EPFL-trained applied mathematician with a background in Artificial Intelligence and Quantum technologies. At CYD Campus that he joined in May 2025, he develops Graph Neural Networks methods to map and forecast the evolution of emergent technologies such as quantum technologies. More generally, he enjoys exploring the forefront of scientific advancements to contribute meaningfully to our evolving world!
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Tomas Joaquin Anderegg

Master Student at EPFL

Tomas, a second year Robotics student at EPFL with a strong curiosity for exploring new ideas and technologies. Before entering engineering, I spent several years studying languages, which helped me develop a broad, open-minded perspective and a passion for learning. My spontaneous and adventurous nature drives me to constantly seek new challenges, both academic and personal. Through my studies, I discovered the fascinating world of Machine Learning and Deep Learning, where I’m eager to combine analytical thinking with creativity to build intelligent systems that can interact meaningfully with the world around me.
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Session

Leveraging AI for Strategic Technology Monitoring in the Defense Sector

About the speakers