Alberto Santos Delgado

Position: Associate Professor at DTU Biosustain, Pioneer Center for AI
Categories: Health and Medical Science, Life Science
Location: Copenhagen, Frederiksberg, and vicinity (1000-2999)


I have a strong background in computer science, software engineering, and computational biology. Throughout my career, I have gained experience in both industry and academia, working in various roles and across different countries. Currently, I hold a leadership position at DTU Biosustain, where I head the data science platform and lead the Multi-omics Network Analytics research group (MoNA).

At MoNA, we leverage graph-based approaches to effectively structure, integrate, analyze, and interpret multi-omics data. Our primary focus is on tackling environmental and human health challenges. Specifically, our research focuses on understanding the mechanisms behind microbial community assembly and adaptation in response to abiotic factors, environmental degradation, and diseases. To accomplish this, we employ a multidisciplinary approach, integrating diverse data modalities such as metaomics and metabolomics data.


Throughout my career, I have had the privilege of working in diverse fields and holding various positions in both industry and academia. These experiences have provided me with valuable insights and knowledge that I believe can be of great value to young scientists who are starting their journeys. I have encountered different challenges, collaborated with diverse teams, and navigated different professional environments. Sharing these experiences with aspiring scientists can help them gain a broader perspective and prepare them for the road ahead.

Moreover, my roles in leadership positions have allowed me to develop a good understanding of what effective management requires. Sharing this experience can contribute to the professional development of mentees.

Further, I believe that participating in this program will also be a valuable learning experience for me.

Skills, expertise, and interests

  • Data science
  • Data analytics
  • Data mining
  • Big data
  • Bioinformatics
  • Health and medical science
  • Software engineering
  • Network science
  • Career planning or change
  • Leadership

Programming languages and software

  • Python
  • R