Opening the black-box decision-making process with prediction-local and model-global explanations

• BEST PAPER AWARD for the paper titled "iSTEP, An Integrated Self-Tunin g Engine for Predictive Maintenance in Industry 4.0" published in the 16th IEEE International Symposium on Parallel and Distributed Processing with Applications (ISPA 2018), held in Melbourne, Australia, 11-13 December 2018. (2019)
• BEST PAPER AWARD for the paper titled "Clustering-Based Assessment of Residential Consumers from Hourly-Metered Data" published in the "International Conference on Smart Energy Systems and Technologies", 10-12 September 2018, University of Sevilla, Sevilla, Spain (2019)

Master of Science

• Big data: architectures and data analytics. A.A. 2017/18, INGEGNERIA INFORMATICA (COMPUTER ENGINEERING). Collaboratore del corso
• Big data: architectures and data analytics. A.A. 2018/19, INGEGNERIA INFORMATICA (COMPUTER ENGINEERING). Collaboratore del corso
• Big data: architectures and data analytics. A.A. 2020/21, INGEGNERIA INFORMATICA (COMPUTER ENGINEERING). Collaboratore del corso
• Data science lab: process and methods. A.A. 2019/20, DATA SCIENCE AND ENGINEERING. Collaboratore del corso
• Data science lab: process and methods. A.A. 2020/21, DATA SCIENCE AND ENGINEERING. Collaboratore del corso

Bachelor of Science

• Introduction to databases. A.A. 2017/18, INGEGNERIA INFORMATICA (COMPUTER ENGINEERING). Collaboratore del corso
• Introduction to databases. A.A. 2018/19, INGEGNERIA INFORMATICA (COMPUTER ENGINEERING). Collaboratore del corso

• Cerquitelli, Tania; Ventura, Francesco; Apiletti, Daniele; Baralis, Elena; Macii, ... (2021)
  Enhancing manufacturing intelligence through an unsupervised data-driven methodology for cyclic industrial processes. In: EXPERT SYSTEMS WITH APPLICATIONS, vol. 182 (115269). ISSN 0957-4174
  Contributo su Rivista
• Ventura, Francesco (2021)
  Explaining black-box deep neural models' predictions, behaviors, and performances through the unsupervised mining of their inner knowledge. relatore: CERQUITELLI, TANIA; , 33. XXXIII Ciclo, P.: 141
  Doctoral Thesis
• Attanasio, Giuseppe; Giobergia, Flavio; Pasini, Andrea; Ventura, Francesco; Baralis, ... (2020)
  DSLE: A Smart Platform for Designing Data Science Competitions. In: 2020 IEEE 44th Annual Computers, Software, and Applications Conference (COMPSAC), Madrid (Spain), July 13-17, pp. 133-142. ISBN: 978-1-7281-7303-0
  Contributo in Atti di Convegno (Proceeding)
• Cerquitelli, T; Nikolakis, N; Bethaz, P; Panicucci, S; Ventura, F; Macii, E; Andolina, ... (2020)
  Enabling predictive analytics for smart manufacturing through an IIoT platform. In: 4th IFAC Workshop on Advanced Maintenance Engineering, Services and Technologies - AMEST 2020, Cambridge (UK), 10 September 2020through 11 September 2020, pp. 179-184. ISSN 2405-8963
  Contributo in Atti di Convegno (Proceeding)
• Panicucci, S.; Nikolakis, N.; Cerquitelli, T.; Ventura, F.; Proto, S.; Macii, E.; ... (2020)
  A cloud-to-edge approach to support predictive analytics in robotics industry. In: ELECTRONICS, vol. 9, pp. 492-513. ISSN 2079-9292
  Contributo su Rivista
• Ventura, Francesco; Proto, Stefano; Apiletti, Daniele; Cerquitelli, Tania; Panicucci, ... (2019)
  A new unsupervised predictive-model self-assessment approach that SCALEs. In: 2019 IEEE International Congress on Big Data, BigData Congress 2019, Milan, Italy, July 8-13, 2019, Milan, Italy, July 8-13, 2019, pp. 144-148. ISBN: 978-1-7281-2772-9
  Contributo in Atti di Convegno (Proceeding)
• Proto, Stefano; Ventura, Francesco; Apiletti, Daniele; Cerquitelli, Tania; Baralis, ... (2019)
  PREMISES, a scalable data-driven service to predict alarms in slowly-degrading multi-cycle industrial processes. In: 2019 IEEE International Congress on Big Data, BigData Congress 2019, Milan, Italy, July 8-13, 2019, Milan, Italy, July 8-13, 2019, pp. 139-143. ISBN: 978-1-7281-2772-9
  Contributo in Atti di Convegno (Proceeding)
• Ventura, Francesco; Cerquitelli, Tania (2019)
  What's in the box? Explaining the black-box model through an evaluation of its interpretable features. pp. 1-5
  Altro
• Cerquitelli, Tania; Proto, Stefano; Ventura, Francesco; Apiletti, Daniele; Baralis, ... (2019)
  Towards a real-time unsupervised estimation of predictive model degradation. In: BIRTE '19 International Workshop on Real-Time Business Intelligence and Analytics, Los Angeles, CA, USA, August 26, 2019. ISBN: 978-1-4503-7660-0
  Contributo in Atti di Convegno (Proceeding)
• Cerquitelli, Tania; Proto, Stefano; Ventura, Francesco; Apiletti, Daniele; Baralis, ... (2019)
  Automating concept-drift detection by self-evaluating predictive model degradation. pp. 1-5
  Altro
• Apiletti, Daniele; Barberis, Claudia; Cerquitelli, Tania; Macii, Alberto; Macii, Enrico; ... (2018)
  iSTEP, an Integrated Self-Tuning Engine for Predictive Maintenance in Industry 4.0. In: IEEE International Conference on Parallel & Distributed Processing with Applications, Melbourne, Australia, December 11-13, 2018, pp. 924-931. ISBN: 978-1-7281-1141-4
  Contributo in Atti di Convegno (Proceeding)
• Ventura, Francesco; Cerquitelli, Tania; Giacalone, Francesco (2018)
  Black-Box Model Explained Through an Assessment of Its Interpretable Features. In: New Trends in Databases and Information Systems, Budapest, Hungary, September, 2-5, 2018, pp. 138-149. ISBN: 978-3-030-00063-9
  Contributo in Atti di Convegno (Proceeding)
• Cerquitelli, Tania; Chicco, Gianfranco; DI CORSO, Evelina; Ventura, Francesco; ... (2018)
  Discovering electricity consumption over time for residential consumers through cluster analysis. In: 2018 International Conference on Development and Application Systems (DAS), Suceava (Romania), 24-26 May 2018, pp. 164-169. ISBN: 978-1-5386-1493-8
  Contributo in Atti di Convegno (Proceeding)
• Cerquitelli, Tania; Chicco, Gianfranco; Di Corso, Evelina; Ventura, Francesco; Giuseppe, ... (2018)
  Clustering-Based Assessment of Residential Consumers from Hourly-Metered Data. In: International Conference on Smart Energy System and Technologies - SEST 2018, Sevilla, Spain, September, 10-12, 2018
  Contributo in Atti di Convegno (Proceeding)
• Proto, Stefano; DI CORSO, Evelina; Ventura, Francesco; Cerquitelli, Tania (2018)
  Useful ToPIC: Self-tuning strategies to enhance Latent Dirichlet Allocation. In: BigData Congress 2018, San Francisco (USA), July 2-7, 2018, pp. 33-40. ISBN: 978-1-5386-7232-7
  Contributo in Atti di Convegno (Proceeding)
• Cerquitelli, T.; Di Corso, E.; Ventura, F.; Chiusano, S. (2017)
  Prompting the data transformation activities for cluster analysis on collections of documents. In: 25th Italian Symposium on Advanced Database Systems, SEBD 2017, Squillace Lido, Catanzaro, Italy, June 25th-29th, 2017,, Squillace Lido, Catanzaro, Italy, June 25th-29th, 2017, pp. 1-8
  Contributo in Atti di Convegno (Proceeding)
• Di Corso, Evelina; Ventura, Francesco; Cerquitelli, Tania (2017)
  All in a twitter: Self-tuning strategies for a deeper understanding of a crisis tweet collection. In: Big Data (Big Data), 2017 IEEE International Conference on, Boston (USA), 11-14 Dec. 2017, pp. 3722-3726. ISBN: 978-1-5386-2715-0
  Contributo in Atti di Convegno (Proceeding)
• Cerquitelli, Tania; DI CORSO, Evelina; Ventura, Francesco; Chiusano, SILVIA ANNA (2017)
  Data miners' little helper: data transformation activity cues for cluster analysis on document collections. In: Proceedings of the 7th International Conference on Web Intelligence, Mining and Semantics, Amantea, June 19-22, 2017, pp. 1-6. ISBN: 978-1-4503-5225-3
  Contributo in Atti di Convegno (Proceeding)
• DI CORSO, Evelina; Cerquitelli, Tania; Ventura, Francesco (2017)
  Self-tuning techniques for large scale cluster analysis on textual data collections. In: ACM SIGAPP Symposium On Applied Computing, Marrakesh, Morocco, April 3rd-7th, 2017, pp. 1-6
  Contributo in Atti di Convegno (Proceeding)