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.
Who Am I?
Hi I'm Davide Marcato,
- Software Engineer at INFN (Istituto Nazionale di Fisica Nucleare) - Laboratori Nazionali di Legnaro.
- Researcher in the field of Machine Learning applications to Industrial Control Systems.
- Information Engineering Ph.D. at DEI, Università degli Studi di Padova, Italy.
- Former Openlab Summer Student at CERN.
INFN - LNL
Computing Group
UNIPD
Ph.D. in Information Engineering
CERN
Openlab Summer Student
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).
Education
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 LaudeCurriculum:
- 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: 96/110Curriculum:
- 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: 95/100Work Experience
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.
Software
beckMotor
AsynMotor compliant EPICS device support for Beckhoff KL2541 stepper motor driver.
Gnome VLAN Switcher
A GNOME extension to activate and deactivate VLAN connections.
Telegram EPICS Bot
Telegram bot to read EPICS control systems PVs and to be notified about alarms.
Publications
W. Duckitt, J.K. Abraham, D. Marcato, and G. Savarese
React Automation Studio: Modern Scientific Control with the Web
in Proc. 19th Int. Conf. Accel. Large Exp. Phys. Control Syst. (ICALEPCS’23), Cape Town, South Africa, Oct. 2023. DOI: 10.18429/JACoW-ICALEPCS2023-FR2BCO01D. Marcato, D. Bortolato, V. Martinelli, G. Savarese, G. A. Susto
Time-Series Deep Learning Anomaly Detection for Particle Accelerators
IFAC-PapersOnLine, Volume 56, Issue 2, 2023, Pages 1566-1571, ISSN 2405-8963, DOI: 10.1016/j.ifacol.2023.10.1855D. Marcato et al.
Demonstration of Beam Emittance Optimization using Reinforcement Learning
in Proc. IPAC’23, Venice, Italy, May 2023, pp. 2881-2884. DOI: 10.18429/JACoW-IPAC2023-WEPA100D. Marcato et al.
Upgrade of the ALPI low and medium beta RF control system
in Proc. IPAC’23, Venice, Italy, May 2023, pp. 4205-4208. DOI: 10.18429/JACoW-IPAC2023-THPA104G. Savarese et al.
First installation of the upgraded vacuum control system for ALPI accelerator
in Proc. IPAC’23, Venice, Italy, May 2023, pp. 858-861. DOI: 10.18429/JACoW-IPAC2023-MOPL130L. Bellan et al.
New techniques for the LNL superconductive linac ALPI beam dynamics simulations and commissioning
in Proc. IPAC’23, Venice, Italy, May 2023, pp. 1307-1310. DOI: 10.18429/JACoW-IPAC2023-TUODA3E. Fagotti et al.
Upgrade of the heavy ion accelerator complex at INFN-LNL
in Proc. IPAC’23, Venice, Italy, May 2023, pp. 2198-2201. DOI: 10.18429/JACoW-IPAC2023-TUPM004A. Ruzzon et al.
Status of the commissioning of Beam Cooler for SPES project
in Proc. IPAC’23, Venice, Italy, May 2023, pp. 2245-2248. DOI: 10.18429/JACoW-IPAC2023-TUPM028L. de Ruvo et al.
Functional Architecture of SPES Safety System
in Proc. IPAC’23, Venice, Italy, May 2023, pp. 4733-4735. DOI: 10.18429/JACoW-IPAC2023-THPL114V. Martinelli, L. Bellan, D. Bortolato, M. Comunian, E. Fagotti, P. Francescon, A. Galatà, D. Marcato, G. Savarese
BOLINA, a Suite for High Level Beam Optimization: First Experimental Results on the Adige Injection Beamline of SPES
in Proc. IPAC'22, Bangkok, Thailand, Jun. 2022, pp. 933-936. DOI: 10.18429/JACoW-IPAC2022-TUPOST035G. Savarese, L. Antoniazzi, D. Bortolato, A. Conte, F. Gelain, D. Marcato, C. R. Roncolato
Vacuum Control System Upgrade for ALPI Accelerator
in Proc. IPAC'22, Bangkok, Thailand, Jun. 2022, pp. 744-746. DOI: 10.18429/JACoW-IPAC2022-MOPOMS045D. Marcato, G. Arena, M. Bellato, D. Bortolato, F. Gelain, G. Lilli, V. Martinelli, E. Munaron, M. Roetta, G. Savarese,
Pysmlib: A Python Finite State Machine Library for EPICS
Proceedings of the 18th International Conference on Accelerator and Large Experimental Physics Control Systems (ICALEPCS 2021) DOI: 10.18429/JACoW-ICALEPCS2021-TUBL05G. Savarese, G. Arena, D. Bortolato, F. Gelain, D. Marcato, V. Martinelli, E. Munaron, M. Roetta,
Design and Development of the new Diagnostic Control System for the SPES Project at INFN-LNL
Proceedings of the 18th International Conference on Accelerator and Large Experimental Physics Control Systems (ICALEPCS 2021) DOI: 10.18429/JACoW-ICALEPCS2021-TUPV016A. Galatà et al.,
First beams from the 1+ source of the ADIGE injector for the SPES Project
Journal of Physics: Conference Series, Volume 2244, 19th International Conference on Ion Sources - ICIS2021 09/2021 - Online. DOI: 10.1088/1742-6596/2244/1/012069D. Marcato, G. Arena, D. Bortolato, F. Gelain, V. Martinelli, E. Munaron, M. Roetta, G. Savarese, G. A. Susto,
Machine Learning-based Anomaly Detection for Particle Accelerators
2021 IEEE Conference on Control Technology and Applications (CCTA), 2021, pp. 240-246, DOI: 10.1109/CCTA48906.2021.9658806.T. Barbariol, F. Dalla Chiara, D. Marcato, G.A. Susto,
A review of Tree-based approaches for Anomaly Detection
Control Charts and Machine Learning for Anomaly Detection in Manufacturing. Springer Series in Reliability Engineering. Springer, 2021. DOI: 10.1007/978-3-030-83819-5_7M. Comunian et al.,
Status of the SPES Exotic Beam Facility
Journal of Physics: Conference Series, vol.1401, pp.012002, January 2020. DOI: 10.1088/1742-6596/1401/1/012002D. Marcato,
Explorations in Heterogeneous Computing
CERN Openlab Summer Student Reports, 2019A. Galatà et al.,
Towards the first beams from the ADIGE injector for the SPES Project
Journal of Physics: Conference Series, vol.1350, pp.012090, November 2019. DOI: 10.1088/1742-6596/1350/1/012090G. Bisoffi et al.,
Hardware Commissioning of the Refurbished ALPI Linac at INFN-LNL to Serve as SPES Exotic Beam Accelerator
Journal of Physics: Conference Series, vol.1350, pp.012091, November 2019. DOI: 10.1088/1742-6596/1350/1/012091G. Bisoffi et al.,
Progress in the realization and commissioning of the exotic beam facility SPES at INFN-LNL
Journal of Physics: Conference Series, vol.1067, pp.052017, September 2018. DOI: 10.1088/1742-6596/1067/5/052017A. Galatà et al.,
Progresses in the installation of the SPES-Charge Breeder beam line
Journal of Instrumentation, vol.13, no.12, pp.C12009-C12009, December 2018. DOI: 10.1088/1748-0221/13/12/c12009D. Pedretti, M. Bellato, D. Bortolato, C. Fanin, F. Gelain, R. Isocrate, D. Marcato, E. Munaron, S. Pavinato,
The new Beam Diagnostic Data Readout and Signal Processing System at LNL
IEEE Transactions on Nuclear Science, vol.65, no.4, pp.972-979, April 2018. DOI: 10.1109/TNS.2018.2808220D. Bortolato, S. Pavinato, M. Bellato, F. Gelain, R. Isocrate, D. Marcato, E. Munaron, D. Pedretti,
Upgrade of the LLRF Control System at LNL
in Proc. 16th Int. Conf. on Accelerator and Large Experimental Control Systems (ICALEPCS’17), Barcelona, 2017, DOI: 10.18429/JACoW-ICALEPCS2017-TUPHA117S. Pavinato, M. Betti, D. Bortolato, F. Gelain, D. Marcato, D. Pedretti, M. Bellato, R. Isocrate, M. Bertocco,
Development of a Digital LLRF Control System at LNL
in Proc. 28th Accelerator Conf. (LINAC’16), East Lansing, MI, USA, 2016, DOI: 10.18429/JACoW-LINAC2016-THPLR048D. Bortolato, S. Pavinato, D. Pedretti, M. Betti, F. Gelain, D. Marcato, M. Bellato, R. Isocrate, M. Bertocco,
New LLRF control system at LNL
2016 IEEE-NPSS Real Time Conference (RT), Padua, 2016, pp. 1-8, DOI: 10.1109/RTC.2016.7543105D. Pedretti, S. Pavinato, M. Betti, D. Bortolato, F. Gelain, D. Marcato, M. Bellato, R. Isocrate, M. Bertocco,
An I/O controller for real time distributed tasks in particle accelerators
2016 IEEE-NPSS Real Time Conference (RT), Padua, 2016, pp. 1-7, DOI: 10.1109/RTC.2016.7543108D. Pedretti, D. Bortolato, F. Gelain, M. Giacchini, D. Marcato, M. Montis, S. Pavinato, J. A. Vasquez, M. Bellato, R. Isocrate
Custom Hardware Platform Based on Intel Edison Module
in Proc. 15th Int. Conf. on Accelerator and Large Experimental Physics Control Systems (ICALEPCS’15), Melbourne, 2015, DOI: 10.18429/JACoW-ICALEPCS2015-WEM307Contacts
davide.marcato@lnl.infn.it
jobs@marcato.dev