CEDRIC MARCO DETCHART
PROFESOR/A AYUDANTE DOCTOR/A

• Department: ESTADÍSTICA, INFORMÁTICA Y MATEMÁTICAS
• Area: Ciencia de la Computación e Inteligencia Artificial
• e-mail: cedric.marcounavarra.es
• Phone number: [+34] 948 16 6052 (ext. 6052)
•   EDIFICIO LOS PINOS - DESPACHO 1006 - P.PRIMERA

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Cédric Marco Detchart holds a PhD from the Public University of Navarre, where he is currently an Assistant Professor in the Department of Statistics, Computer Science, and Mathematics. His research is conducted within the Artificial Intelligence and Approximate Reasoning Group (GIARA), focusing on uncertainty modeling, information fusion, and perception in computer vision.

He holds a Bachelor’s degree in Computer Science from the Public University of Navarre and a Master’s degree in Artificial Intelligence, Pattern Recognition, and Digital Imaging from the Polytechnic University of Valencia. During his PhD, he completed a research stay at the Center for Computational Sciences (C3) at the Federal University of Rio Grande do Sul (FURG) in Brazil, working on perception models based on information integration.

After completing his doctorate, he worked as a postdoctoral researcher at the Valencian Research Institute for Artificial Intelligence (VRAIN) at the Polytechnic University of Valencia, where he participated in applied artificial intelligence projects. His work focused on improving human-computer interaction, information fusion, and cognitive assistants using uncertainty models and perceptual comparison theories.

In the academic field, he has taught courses on programming, computer science, and simulation in both engineering and data science programs. His teaching approach integrates research into the classroom through project-based learning and real-world problem-solving. He has supervised multiple undergraduate and master’s theses on topics such as image segmentation, deep learning, and computer vision systems for decision-making.

His scientific output includes publications in high-impact indexed journals (Q1) and contributions to international conferences in artificial intelligence and image processing. He has participated in competitive research projects, collaborating with national and international institutions to develop advanced models for computational perception and uncertainty-based classification.

Beyond academia, he has worked on technology transfer, developing applied solutions for various sectors, including precision agriculture and human-machine interaction. He has also engaged in scientific outreach, contributing to discussions on the impact of artificial intelligence across different fields.

His research interests focus on the application of perceptual comparison theories in computer vision, with a particular emphasis on advancements in psychology and neuroscience, exploring new ways to enhance artificial perception and improve decision-making in complex environments.