Marco Recenti holds a PhD in Biomedical Engineering (2023) from Reykjavik University, Iceland. His research specializes in Artificial Intelligence for healthcare, with applications in clinical evaluation, diagnostics, and precision oncology. His research focused on AI-driven feature management and predictive modeling with biomedical signals, medical imaging and multi-omics data.

He previously worked as a Postdoctoral Fellow at the Institute of Biomedical and Neural Engineering, Reykjavik University, where he taught Master’s courses in Digital Health, and supervised Master theses and internships.
In 2022, he was a Visiting Researcher at Chonnam National University, South Korea, working on AI methods for gait analysis. He previously earned a Master’s degree in ICT Engineering (2019) and a Bachelor’s degree in Telecommunication Engineering (2016) from the Polytechnic University of Turin, Italy.

Marco has authored more than 20 peer-reviewed publications, with contributions ranging from ensemble feature selection for multimodal healthcare data to imaging biomarkers for sarcopenia, diabetes, and hypertension prediction. He also contributed in the development of the BioVRSea protocol for motion sickness and postural control assessment creating one the largest available dataset in the field.
For his work on prediction of motion sickness through biosignals, he won the Best PhD Contribution Award at the IEEE METROXRAINE Conference in 2022.
He has experience in student mentoring, having supervised and co-supervised more than 15 Master’s students.
He is an Editorial Board Member of the journals BioMedical Engineering Online and Gait & Posture.

Currently, he is a Postdoctoral Fellow at Humanitas University, in the Computational Biology Lab under the supervision of Professor Charlotte Ng. His research focuses on Artificial Intelligence methods for precision oncology using multi-omics data.