Smart platforms for science

Project goal

The project goal is to design a platform that can analyse data collected from user interactions and can process this information in order to provide recommendations and other insights, thus helping improve the performance and relevance of user searches or learning objectives.

R&D topic
Applications in other disciplines
Project coordinator(s)
Alberto Di Meglio
Team members
Taghi Aliyev
Collaborator liaison(s)
Marco Manca (SCImPULSE), Mario Falchi (King’s College London)


Project background

Data-analysis systems often collect and process very different types of data. This includes not only the information explicitly entered by users (“I’m looking for…”), but also metadata about how the user interacts with the system and how their behaviour changes over time based on the results they get. Using techniques such as natural language processing (NLP) and smart chatbots, it is possible to achieve improved interaction between humans and machines, potentially providing personalised insights based on both general population trends and individual requests. Such a system would then be able to recommend further searches, actions, or links that may have not occurred to the user.

Such an approach could, for example, be used to design better self-help systems, automated first-level medical services, more contextual and objective-aware search results, or educational platforms that are able to suggest learning paths that address specific student needs.

This project is being carried out in the context of CERN's strategy for knowledge transfer to medical applications, led by CERN's Knowledge Transfer group.

Recent progress

The concept of the Smart Platforms project emerged in 2019 as a spin-off of the application of NLP techniques to genomic analysis in the GeneROOT project.

In 2019, a few initial discussions about possible applications were started in collaboration with educational institutes and public administrations, with the goal of developing the concept of smart chatbots that are able to improve human-machine interaction. As the project moved into the proof-of-concept phase, it became clear that the need to understand issues related to data-privacy and information sharing are still a critical roadblock for systems like this. The project was therefore merged into the CERN Living Lab, through which such concerns can be better addressed.

Next steps

The project has been merged into the CERN Living Lab as part of a general initiative to understand the implications of processing personal data and the related ethical constraints.


    A. Manafli, T. Aliyev: Natural Language Processing for Science. Information Retrieval and Question Answering. Summer Student Report, 2018.


    A. Di Meglio, Introduction to Multi-disciplinary Platforms for Science, (24 January). Presented at CERN openlab Technical Workshop, CERN, Geneva, 2019.
    T. Aliyev, Smart Data Analytics Platform for Science (1 November). Presented at i2b2 tranSMART Academic Users Group Meeting, Geneva, 2018.
    T. Aliyev, AI in Science and Healthcare: Known Unknowns and potential in Azerbaijan (December). Presented at Bakutel Azerbaijan Tech Talks Session, Baku, 2018.