Inigo Prada Luengo

Inigo Prada Luengo is a Guest Researcher at the Department of Computer Science, University of Copenhagen, specializing in Machine Learning and Bioinformatics. His research integrates deep learning with genomics, particularly in the study of circular DNA, cancer informatics, and personalized medicine. He is affiliated with the SCIENCE AI Centre and collaborates extensively across Europe and beyond.

Education:

• Ph.D. in Biology (2020), University of Copenhagen – Thesis: "Origin and impact of circular DNA on the eukaryotic genomes"

Research Interests:

Inigo's work lies at the intersection of machine learning and genomic science. His primary focus is on understanding the role of extrachromosomal circular DNA in human health and disease. He applies deep generative models to enable N-of-one genomics, allowing personalized gene expression analysis without control samples. His recent projects include AI-driven frameworks for rare cancer prognosis and synthetic data generation for hematological research.

He also contributes to computational method development, including tools for detecting circular DNA at single-nucleotide resolution and understanding its impact on genomic stability and aging in model organisms like yeast.

Scientific Contributions & Trends:

Inigo's publications reflect a strong trajectory in computational genomics and AI in biomedicine. His work has consistently appeared in high-impact journals such as Genome Biology, Nucleic Acids Research, and JCO Clinical Cancer Informatics. A clear trend is the integration of AI frameworks into clinical and biological data, with emphasis on rare diseases, cancer genomics, and personalized treatment strategies.

Collaborations & Networks:

He collaborates with leading institutions across Europe, including Italy, Spain, and Germany, and works closely with Professor Anders Krogh and Birgitte Regenberg at the University of Copenhagen. His affiliations span both the Department of Computer Science and the Faculty of Science, reflecting his interdisciplinary expertise.

Labs & Teams:

Inigo is associated with the Machine Learning Section at DIKU and the SCIENCE AI Centre. These environments provide access to advanced computational resources and foster collaborations in AI-driven life sciences research.