I'm Davide

Software Engineer, Ph.D.

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About Me

Who Am I?

Hi I'm Davide Marcato,


Computing Group


Ph.D. in Information Engineering


Openlab Summer Student

Currently working on:

SPES Project

70MeV Cyclotron for Physics and Medical Applications
What can I do?

Technical Skills

Industrial Control Systems

EPICS, PLCs, Scada, Industrial Protocols: from low level drivers to the end user Graphical Interfaces.

Machine Learning

Pushing Big Data analysis and Deep Learning technologies for fault prevention and intelligent tuning of linear accelerators.

Software Development

Multipurpose coding and scripting with Python, Java, JavaScript, C, C++, CUDA, OpenCL, Spark, QT etc. Git versioning.

System Administration,
Cloud computing

Deep knowledge of Linux, proficient in Docker, Proxmox VE, Kubernetes, OpenStack, advanced networking.

Web Development

Experience in full-stack development using Sping Boot, Flask, React, Bootstrap, jQuery, NodeJs, REST, AJAX. DB design and management.

High Performance Computing

CUDA programming to accelerate scientific computations on highly parallel and distributed architectures (GRID).

My studies


2020-2023, University of Padova

Ph.D. in Information Engineering

Research topics:
Particle accelerators are used all around the world for fundamental physics research, medical diagnosis and industrial applications. These can be extremely complex machines, with thousands of sensors and actuators producing an enormous amount of data. By exploiting this data, it's possible to reach new levels of performance, improve the uptime of the accelerator and reduce the effort required to setup, control and maintain it. By discovering anomalies in the time-series of the process variables it is possible to predict the insurgence of fault conditions, or the breakage of a critical component, thus allowing to intervene in time to avoid it. The data can also help to model the beam interactions with the elements on the beam path, taking into account all the uncertainties, misalignments and errors of a traditional control system. This enables a finer control of the beam transport procedure, and higher quality beam output.

2017-2020, University of Padova

Master's Degree in Computer Engineering
Final Mark: 110 Cum Laude
  • Computer Networks
  • Database Management Systems
  • Data And Algorithms 2
  • Operating Systems
  • Big Data Computing
  • Computer Vision
  • Machine Learning
  • Distributed Systems
  • Web Applications
  • Operations Research 1
  • Strategic Management of Corporations
  • Autonomous Robotics

2013-2017, University of Padova

Bachelor's Degree in Information Engineering
Final Mark: 96/110
  • Algebra Lineare e Geometria
  • Analisi Matematica 1
  • Architettura degli Elaboratori
  • Fisica Generale 1
  • Fondamenti di Informatica
  • Analisi dei Dati
  • Analisi Matematica 2
  • Dati e Algoritmi 1
  • Elettrotecnica
  • Fisica Generale 2
  • Segnali e Sistemi
  • Controlli Automatici
  • Elettronica
  • Elettronica Digitale
  • Informatica Teorica
  • Sistemi e Modelli
  • Telecomunicazioni

2008-2013, I.I.S. A. Einstein, Piove di Sacco (PD)

Scientific High School Diploma
Final Mark: 95/100

Work Experience

INFN Technologist 2023-Present

Software development for Cloud computing platforms, focusing on the Identity and Access Management (IAM). Operation of cloud infrastructures based on OpenStack and Kubernetes, including INFN-Cloud and CloudVeneto.

INFN Research Fellow 2021-2023

Machine Learning for Particle Accelerators Control Systems. Technological research with focus on deep learning, anomaly detection and time series forecast. Applications in the fields of beam tranport optimization, predictive maintenance, root cause analysis and prognostics.

INFN Technician 2016-2021

Control System Software developer for particle accelerators. From hardware integration to high level procedures for slow control and data analysis.

CERN Openlab Summer Student July - August 2019

High Performance Computing with GPUs using CUDA for High Energy Phisics. Collaborating with the CMS experiment. More...

INFN Scholarship 2014-2016

Software development with EPICS. Upgrade of the ALPI RF control system.

Open Source Contributions



A Python library to create event driven finite state machines for EPICS

Explore on Github

A script to automatically download and install EPICS modules.

Explore on Github

AsynMotor compliant EPICS device support for Beckhoff KL2541 stepper motor driver.

Explore on Github
Gnome VLAN Switcher

A GNOME extension to activate and deactivate VLAN connections.

Explore on Github
Telegram EPICS Bot

Telegram bot to read EPICS control systems PVs and to be notified about alarms.

Explore on Github
INFN Jobs Bot

Telegram Bot who publishes INFN Jobs Offers.

Explore on Github
My Research


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