Join the Staff Academy webinar on 7.10.2025 to learn about AI and teaching!

Speakers and their topics

Kimmo Kaskikallio, CTO Nordics, Director, EY Finland

• AI in working-life

Ulisses Moliterno de Camargo, PhD (University of Helsinki), is a Senior Lecturer in Information Technology at South-Eastern Finland University of Applied Sciences. In addition to his teaching responsibilities, he coordinates international studies within the IT engineering program. His research has focused on applied Artificial Intelligence, with a growing interest in future-proof educational practices and methodologies.

• The 10x Teacher: How AI Methods Multiply Our Teaching Impact
  • Just as AI has empowered software engineers to achieve “10x” productivity, it holds the same transformative potential for teaching. In this talk, I will explore concrete AI methods and techniques that educators can adopt to streamline preparation, personalize learning, and enhance student engagement. The goal is to show how teachers can become “10x teachers” not by working more, but by working smarter, with AI as a powerful partner in pedagogy.

Mariano Pierantozzi – Associate Professor of Applied Physics Ud’A

He is an Associate Professor of Applied Physics, with consolidated experience in the field of technical physics. His research activity is mainly devoted to the analysis and modeling of thermophysical and energy-related processes. Over the years, he has authored numerous scientific publications concerning the thermophysical properties of fluids, with particular focus on the accurate determination and modeling of quantities such as surface tension, viscosity, and thermal conductivity, as well as other properties relevant to engineering applications.

A significant part of his work has been dedicated to the application of machine learning techniques to the study of fluid properties. These approaches have been employed both to improve the predictive accuracy of classical models and to develop new methodologies for estimating thermophysical data in cases where experimental information is limited or unavailable. This line of research reflects an effort to combine traditional theoretical and numerical methods with data-driven approaches, in order to provide tools of practical utility for the scientific and engineering community.

In addition to his research, he has developed an interest in teaching. Although not a pedagogy specialist, he pays attention to the challenges that students may face when approaching technical subjects. In recent years, he has introduced the use of artificial intelligence tools in his lectures, with the aim of facilitating understanding and supporting students in learning the fundamental principles of physics.

Miriam D’ignazio – Ph.D.s in Science and Technology for Sustainable Development Ud’A

Miriam D’ignazio (M.Arch., B.Sc.) is a Ph.D.s. in Science and Technology for Sustainable Development. Her interdisciplinary background combines a Master’s degree in architecture and a Bachelor’s one in psychology, integrated by specialized training in Neuroscience Applied to Architectural Design (NAAD) at Iuav University of Venice and Neuroimaging: From Methods to Neuroscience Applications at University of Chieti-Pescara.

She studied at École nationale supérieure d’architecture de Normandie (ENSA), where she delved into urban sociology;Miriam then worked in Peru with the Municipality of Lima through a year-long international cooperation project with Architecture Sans Frontières International (ASF).

She currently works at the Building Physics and Energy Systems laboratory, where she investigates the relationship between allostatic load and built environmental factors within an interdisciplinary team of engineers, biologists, and psychologists.

• LEARNING by CREATING – Student-centered teaching with AI tools
  • The presentation describes a pedagogical experiment integrating AI tools into a Technical Physics course on convective heat transfer at the University of Chieti-Pescara. Students used AI independently to learn assigned subtopics and create diverse educational materials (videos, podcasts, infographics) to teach their peers, resulting in higher-quality work than expected and positive learning outcomes. The “learning by creating” approach with AI support enhanced student engagement, creativity, and understanding while transitioning the instructor from lecturer to learning facilitator.