Research areas and methodologies

The Computing Systems and Bioinformatics Research Unit (CoSBi Lab) ofUniversità Campus Bio-Medico di Roma began its research activities in 2004 which immediately concerned the use of Artificial Intelligence techniques with particular attention to applications in the biomedical field.
Currently the research activity concerns various methodological aspects of computer science.
The main areas of interest are: multimodal (deep) learning, generative approaches, eXplainable AI, resilience of AI algorithms, federated learning, (deep) reinforcement learning, and computer vision. These topics find application in industrial, civil and biomedical sectors. Among them, the areas of greatest impact are connected health, the development of 5P medical tools in oncology, with particular attention to lung, breast and prostate cancer, but also in the sector of viral infections, the application of generative models for virtual scanninging and for insurance applications, NLP techniques for the analysis of medical records, time series analysis of biomedical and industrial signals, the application of federated learning in medicine, the prediction of energy production in energy communities, the precision agriculture, social media analysis, the development of intrinsically explainable and transparent models to facilitate their adoption in daily life, digital twin tools for path planninging in robotic surgery, and the analysis of large 3D images.

The unit separatesingue also in the development of data processing systems optimized for low latency processing on embedded devices and FPGAs, used on a single nodeingolo or networked in the creation, through data fusion techniques, of integrated and intelligent systems in the application fields of health, industrial and environmental monitoring. Networks, IoT and distributed systems, including DLT, represent an application field covered by the unit with industrial and research developments, linked to activities with external partners and participation in start-ups. Furthermore,

The Research Unit also includes expertise in control and estimation theory for stochastic, distributed, multi-agent and delay systems. Applications concern sensor networks, optimal resource management in energy communities and modeling in the biomedical field (artificial pancreas and study of the dynamics of drug absorption).

Currently the research group is made up of 8 members, some of whom have contributed to the organization of international events such as: IEEE CBMS 2012, 2014, 2016, 2018, 2019, 2023, IEEE IDT 2022, IEEE ICCI*CC 2019, 2020, EMBC since 2012 to today, 2021 Special Track of IEEE CBMS 2008, 2009, 2010, 2011, 2013, 2018, 2019, International Contest @ ICPR 2012, Compasac SIS-SS 2017, 2018, 2019, 2023, Metrol 2019-2022 Special Session of Memea 2023. The members of the Unit are also active as guest editors of prestigious international journals in the sector (Pattern Recognition, Artificial Intelligence in Medicine, etc).

Members of the Laboratory also won the international competition “All against COVID-2021: Screen” in 19ing X-ray Images for COVID-19 Infection”, organized by IEEE, and in 2022 the international competition "Covid CXR International Hackathon", organized by ELLIS at Dubai Expo 2022.

Collaborations with other research centres

  • Philips Research, Eindhoven, Netherlands.
  • Department of Academic Respiratory Medicine, Center for Cardiovascular and Metabolic Research, Hull York Medical School, Castle Hill Hospital, UK.
  • Henan University, China
  • Eindhoven University of Technology, Department of Computer Science
  • Umea University
  • Catholic University of the Sacred Heart, Institute of Physics
  • University of Naples Federico II, Dep. of IngElectrical and Information Technology engineering
  • Institute of Cognitive Sciences and Technologies (ISTC-CNR)
  • Computational Linguistics (ILC-CNR)
  • Institute for Computing Applications – CNR, Rome;
  • Italian Diagnostic Center - Bracco Corporate
  • Bracco Imageing SPA
  • Generali Italy
  • Generali Business Solutions SCPA
  • Zespri Group Limited
  • ELIS Innovation Hub srl
  • OpenFiber
  • Hewlett Packard Enterprise (HPE)
  • University of L'Aquila, Dep. of Ingengineering and information sciences and mathematics.
  • La Sapienza University of Rome
  • Institute of Systems Analysis and Informatics "Antonio Ruberti", CNR
  • Scientific Department of the Military Polyclinic of Rome
  • Zilina University, Slovakia
  • Leeds Beckett University, UK
  • Rey Juan Carlos University, Spain
  • Universidad Politécnica de Madrid, Spain
  • Shenzhen University, China
  • Fondazione Bruno Kessler
  • Italian Institute of Technology (IIT)
  • Vita-Salute San Raffaele University
  • Humanity University
  • COT Orthopedic Traumatological Care Spa
  • ENAV SpA
  • FS Technology SpA
  • Teleconsys SpA
  • Eustema SpA
  • University of Cassino and Southern Lazio, Department of IngElectrical and Information Engineering “Maurizio Scarano”
  • National Body of Fire
  • Procter & Gamble
  • Electronics Group
  • Engineering SPA
  • Oulu University
  • Accenture SpA
  • Campus Bio-Medico Polyclinic Foundation
  • University of L'Aquila.
  • Institute of Systems Analysis and Informatics "Antonio Ruberti", CNR
  • Scientific Department of the Military Polyclinic of Rome
  • University of Padua,
  • Rome Technopole Foundation
  • Thales Alenia Space
  • University of Tor Vergata
  • University of Roma Tre
  • Luiss Guido Carlo
  • Institute of Cognitive Sciences and Technologies, CNR
  • Institute of LingComputational uistics (ILC) “Antonio Zampolli" of the National Research Council (CNR), ItalianNLP Lab
  • CLCG, University of Groningen


  • "Device for subcutaneous administration", WO2023062596A1, Authors: E. Cordelli; S. Manfrini; V. Piemonte; R. Sicily; P. Soda; D. Tuccinardi
  • "System for the early detection and reporting of the onset of acute events in patients suffering from chronic obstructive pulmonary disease", PCT/IT2015/000146. The patent is filed in United States of America (US20180153480A1), Europe (EP3304365A1), China (CN107690687A), Brazil (BR112017026004A2), Japan (JP2018519983A). Authors: Antonelli Incalzi R, Barbara FM, Bussu AM, Capasso G, Iannello G, Merone M, Onofri L, Pedone C, Soda P


Processing Systems and Bioinformatics Laboratory

The Processing Systems and Bioinformatics Laboratory covers an area of ​​approximately 90 m2 on the -1 floor of PRABB. It has computational computing machines for the development of machine and deep learn algorithms and applicationsing. The Laboratory is equipping itself with a workstation for research in the AI ​​field with performance in the PetaFLOPS range thanks to 4 NVIDIA A100 Tensor Core 80 GB GPUs and 4 NVIDIA A40 48GB GPUs. Also included is an Intel Xeon E5-2697 v2 2.70Ghz 12Core, 192 GB RAM, NVIDIA TESLA K20c 5GB and NVIDIA Quadro K5000 4G workstation, and an INTEL 5450GB.