Faces of Research” series by PostGenAI@Paris

As part of our Faces of Research series, we highlight the researchers who are driving innovation in artificial intelligence for the benefit of society. Today, we feature Carlos Cuevas Villarmín, whose work sits at the intersection of mathematics, AI, and medicine.

Research at the forefront of medical imaging

Carlos Cuevas Villarmín is developing artificial intelligence models designed to analyze medical images with high precision. His research focuses on identifying key signals—known as biomarkers—that can track the progression of patients with glioma, a form of brain cancer, undergoing novel treatments.

His work is conducted under the supervision of Isabelle Bloch and Mehdi Touat, within a multidisciplinary environment that brings together clinical expertise and advanced data science.

Clear clinical objectives

Carlos’s research is driven by two main goals:

• Improve early detection of disease progression, enabling clinicians to identify significant changes in patients’ conditions at an earlier stage.
• Estimate the probability of treatment success from the outset, supporting more informed and personalized clinical decision-making.

Through these advances, AI is becoming a powerful tool to assist clinicians and enhance patient care.

A focus on explainability and collaboration

Beyond model performance, Carlos places strong emphasis on explainability. Understanding how and why AI systems produce their results is crucial, particularly in medical contexts where transparency and trust are essential.

As he explains:
“I am particularly motivated by the search for explainable models and by working in a multidisciplinary environment where computer scientists and clinicians combine their expertise to achieve high clinical impact.”

Research with real-world impact

Carlos Cuevas Villarmín’s work exemplifies the potential of AI when applied to critical healthcare challenges. By combining mathematical rigor, technological innovation, and close collaboration with clinicians, his research contributes to improving patient outcomes in a meaningful way.