Lorenzo Bini

R&D Engineer at Quantib
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Contact Information
us****@****om
(386) 825-5501
Location
NL
Languages
  • Italian Native or bilingual proficiency
  • English Professional working proficiency
  • Spanish Elementary proficiency
  • Dutch Limited working proficiency

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Credentials

  • Soft skills for young professionals
    Lepaya
    Sep, 2022
    - Nov, 2024
  • AI for Medical Diagnosis
    DeepLearning.AI
    Oct, 2021
    - Nov, 2024
  • Generative Adversarial Networks (GANs) Specialization
    DeepLearning.AI
    Mar, 2021
    - Nov, 2024
  • Simulation Neuroscience
    Ecole polytechnique fédérale de Lausanne
    Aug, 2020
    - Nov, 2024
  • IELTS C1
    British Council
    Jul, 2019
    - Nov, 2024

Experience

  • Quantib
    • Netherlands
    • Medical Equipment Manufacturing
    • 1 - 100 Employee
    • R&D Engineer
      • Dec 2021 - Present

      Currently doing research and development to further improve Quantib® ND, an AI-powered medical software for automatic segmentation of brain structures and white matter hyperintensities, quantification of cerebral atrophy, and tracking of lesion development. Besides R&D, I am also the one in charge of managing the annotation projects and delivering the annotated data used to train the AI algorithms of Quantib ND. This includes outsourcing annotators, coordinating neuroradiologists for QA, and supervising the whole annotation process for cerebral MRI data.

  • Artinis Medical Systems
    • Netherlands
    • Biotechnology Research
    • 1 - 100 Employee
    • Deep Learning Researcher
      • Nov 2020 - Jul 2021

      A 9-months research internship at Artinis Medical Systems, the only company in Europe that designs and develops portable devices for Functional Near-Infrared Spectroscopy (fNIRS), an innovative optical neuroimaging technique to monitor neuronal activity by detecting changes in cerebral tissue oxygenation. I have worked on applying Generative Adversarial Networks (GANs) to fNIRS recordings to enhance their spatial resolution. The project was a first of its kind, pioneering attempt to overcome a common limitation of fNIRS devices, aiming to recover degraded, low-quality or missing signal with the help of state-of-the-art generative AI. The project was developed in Python and MATLAB. The libraries used include PyTorch, MNE and Fieldtrip. Experience gained in designing fNIRS optodes templates, in performing fNIRS measurements with Artinis Brite 24 and Artinis Oxymon, and EEG measurements with TMSi SAGA.

  • NTT DATA
    • Japan
    • IT Services and IT Consulting
    • 700 & Above Employee
    • Software Engineer
      • Mar 2019 - Aug 2019

      I was accountable for the development of tailored software solutions for multinational clients. I worked in team following the Agile (Scrum) development methodology.My responsibilities included: • Designing, developing and deploying software solutions and systems-integration strategies that would suit the client's needs. • Working closely with the client's major representatives during most of the development phases.• Leading and coordinating teams for the development of fully operational POCs and prototypes.• Attending meetings with the clients on behalf of the team.• Attending summits and events on behalf of the company. The most used development tools included the Microsoft O365 Suite, .NET Core, Web APIs, Microsoft Sharepoint and Microsoft Azure cloud services.Gained experience in C# development and cloud development.

    • Intern
      • Dec 2018 - Feb 2019

      I took part at the development of tailored software solutions based on Microsoft services, for multinational clients.I gained relevant experience in Agile software development with .NET Core and .NET Framework, Microsoft O365 Suite, cloud development on Azure web services.

  • Università degli Studi di Milano-Bicocca
    • Italy
    • Research Services
    • 700 & Above Employee
    • QA Automation Researcher
      • Mar 2018 - Sep 2018

      Curricular Internship at LTA Research Laboratory of University of Milano Bicocca. The project aimed to bring full automation to functional testing processes on interactive interfaces, both in terms of determining interaction paths and of selecting the most relevant ones to follow. Given a reinforcement learning algorithm for functional testing automation depicted by a non-deterministic execution methodology, I have contributed to designing and developing concrete solutions to go beyond some of the limits of such methodology. The core aim of the project was about having a global approach more focused on respecting business rules and on meeting testing purposes. Java was the main programming language in which the algorithm was written.

Education

  • Utrecht University
    Master's degree, Artificial Intelligence
    2019 - 2021
  • Università degli Studi di Milano-Bicocca
    Bachelor's degree, Computer Science
    2015 - 2018

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