Ding Ning holds a PhD from Kangwon National University, South Korea. Her research focuses on modeling learning and behavioral mechanisms in human–AI collaborative contexts. From an interdisciplinary perspective integrating educational science and design research, she examines cognitive appraisal, motivational formation, and behavioral regulation processes in generative AI environments, aiming to explain how technology influences learning and work adaptation through multi-path models.

Methodologically, she employs mixed methods combining Structural Equation Modeling, fuzzy-set Qualitative Comparative Analysis, and grounded theory, with the goal of transforming complex learning and behavioral processes into interpretable mechanism-based models. In recent years, her research topics have included AI-assisted learning, technology adoption and resistance, cognitive load, and meaning construction. Related work has been published in journals such as Scientific Reports, Acta Psychologica, Frontiers in Psychology, and Sustainability, and she also serves as a reviewer for multiple international academic journals.

Dr. Leandro Rubén Andrini is an Associate Professor of Mathematics at the Faculty of Exact Sciences, National University of La Plata (UNLP), Argentina, and an Associate Researcher at the National Scientific and Technical Research Council (CONICET). He earned his PhD in Exact Sciences (Physics) from UNLP, where his doctoral research focused on transition metal oxides using advanced X-ray absorption spectroscopy techniques.

His academic career integrates mathematics, physics, and chemistry, with a strong emphasis on interdisciplinary research. Dr. Andrini has conducted extensive research in physicochemistry, synchrotron radiation spectroscopy (XANES/EXAFS), nanostructured materials, and computational spectroscopy. His current work at the La Plata Mathematics Center (CMaLP) centers on mathematical modeling of signals and images obtained through synchrotron radiation techniques, particularly within the framework of inverse problems, nonlinear optimization, Fourier transforms, and wavelet-based analysis.

Beyond his research in materials science and spectroscopy, Dr. Andrini maintains a deep and sustained interest in mathematics education and didactics. From an onto-epistemological perspective, he studies how mathematics functions as a modeling language for other scientific disciplines. His pedagogical work explores the role of mathematical models in interdisciplinary contexts, including biology, chemistry, engineering, and applied sciences. He is currently further strengthening this line of inquiry through advanced studies in education in exact and natural sciences.

Dr. Andrini has more than two decades of university teaching experience at undergraduate and postgraduate levels. He has taught courses in Calculus of Several Variables, Complex Analysis, Linear Algebra, Mathematical Analysis, and interdisciplinary mathematics for engineering programs. He has also coordinated and delivered postgraduate courses in Science, Technology and Society, advanced X-ray techniques, image science, and mathematics for scientific applications.

He has authored numerous peer-reviewed publications in international journals and has participated in collaborative research projects both nationally and internationally, including research stays in France (CNRS – Institut Néel).

Dr. Andrini’s work bridges rigorous mathematical theory, computational modeling, and real-world scientific applications, making him particularly well-positioned to contribute to interdisciplinary initiatives at the intersection of mathematics, science, and education.