Eva Cernadas García

Eva Cernadas García is an Associate Professor at the Escola Técnica Superior de Enxeñaría of the University of Santiago de Compostela (USC), where she conducts research at the intersection of machine learning, computer vision, and practical applications in medicine, food technology, and marine resource management. Her academic position is firmly established within the Computer Science department, where she has developed significant expertise in image segmentation, texture analysis, and shape recognition.

Dr. Cernadas' research interests span multiple domains of artificial intelligence with a strong emphasis on practical implementations. She specializes in developing computer vision algorithms for medical diagnostics, including software tools like CystAnalyser for polycystic kidney disease detection, STERapp for stereological analysis, and PDApp for dental eruption prediction. Her work extends to food technology applications such as MarblingPredictor for ham quality assessment and Govocitos for fish fecundity estimation. Notably, she integrates gender perspective into her technical work, having been awarded by USC in 2021 for introducing gender perspective in machine learning teaching.

Analysis of her recent publications reveals a strong focus on applying machine learning techniques to solve real-world problems across diverse fields. Her work demonstrates consistent innovation in developing efficient algorithms for classification and regression tasks, with increasing attention to gender issues in STEM education. The publications show progression from fundamental algorithm development to practical implementations in medical diagnostics, mental health assessment, and sustainable resource management.

• Awarded by the University of Santiago de Compostela for the introduction of the gender perspective in machine learning teaching in 2021

Dr. Cernadas actively promotes gender equality in STEM through various initiatives including designing workshops for primary education in the program 'Unha enxeñeira ou cientifica en cada cole', early childhood education programs, and promoting the 'INFORMATIZATE' video contest for non-university students. Her research includes significant grant-funded projects related to service robots, intelligent control scenarios, and development of new technologies for studying reproductive ecology in fishery. She collaborates extensively with researchers across multiple disciplines, particularly with Manuel Fernández-Delgado, with whom she has co-authored numerous publications.

Her laboratory work focuses on developing practical software tools that bridge the gap between theoretical machine learning algorithms and real-world applications. The CITIUS research center at USC appears to be her primary research base, where she contributes to projects involving image analysis, pattern recognition, and development of user-friendly interfaces for domain experts in medicine and biology.