Work experience
===============

Junior research fellow
-----------------------

.. grid::

    .. grid-item-card::

        - Jan 2021 - June 2020
        - **Main topics**: 
            - Anomaly detection applied to high-frequency time series data
            - Semantic segmentation of medical images
        - **Supervisor**: `Simone Calderara <https://aimagelab.ing.unimore.it/imagelab/person.asp?idpersona=38>`_
        - `AImageLab <https://aimagelab.ing.unimore.it/>`_ -- University of Modena and Reggio Emilia, Modena, Italy

From January 1, 2021, to June 30, 2020, I worked as a research fellow at the AImageLab laboratory of the University of Modena and Reggio Emilia. During this time, I gained knowledge in group work and deepened my understanding of Artificial Intelligence and Deep Learning techniques. During this time, I collaborated with the company `IMA <https://ima.it/en/ima-group/>`_ through the `Seneca project for Industry 4.0 <https://aimagelab.ing.unimore.it/imagelab/project.asp?idprogetto=94>`_, particularly focusing on anomaly detection techniques in high-frequency time series. 

Furthermore, I collaborated with the startup `Farm4Trade <https://www.farm4trade.com/>`_ to develop `ADAL <https://www.f4tlab.com/adal>`_: an automated systems for recognizing respiratory diseases in animals during slaughter through techniques of Semantic Segmentation. This resulted in a publication at the `MDPI's Animal journal <https://doi.org/10.3390/ani11113290>`_ (see :ref:`research <papers>`).

.. admonition:: Keywords

    :bdg-primary:`Anomaly detection` :bdg-primary:`Time series` :bdg-primary:`Deep learning` :bdg-primary:`Semantic segmentation` :bdg-primary:`Medical imaging`

Freelance full-stack developer
-------------------------------

.. grid::

    .. grid-item-card::

        - Jan 2017 - Dec 2018
        - Design and implementation of a web application for the management of the company's structures (*shelters*).
        - `Club Alpino Italiano <https://www.cai.it/>`_ -- *remote*.

The system utilized a *NoSQL* database powered by `MongoDB <https://www.mongodb.com/>`_, a choice made to accommodate the project's need for extreme flexibility. The backend was developed using *Node.js*, along with the `Express.js <https://expressjs.com/>`_ library for creating and managing APIs, while the front-end interface was built using the `Angular <https://angular.io/>`_ framework. The work conducted in collaboration with the Italian Alpine Club has been compiled and documented for the undergraduate thesis and is available in a fully Open Source format.

.. admonition:: Keywords

    :bdg-primary:`Full-stack development` :bdg-primary:`Web application` :bdg-primary:`NoSQL` :bdg-primary:`MongoDB` :bdg-primary:`Node.js` :bdg-primary:`Express.js` :bdg-primary:`Angular`