Research

My research interests lie in the broad area of database systems, with primary focus on probabilistic databases, statistical relational learning and uncertain data management.

Publications

(DBLP, Google Scholar, ORCID, ACM, IEEE)

• Variational Inference for De Finetti Logic
  Sami Hadouaj, Ouael Ben Amara and Niccolò Meneghetti
  SIGMOD 2026, Vol 4, Issue 3, Article No. 237, pages 1-30 (pdf, acm, slides, pptx).

• A Bayesian Network Framework for Boost Converter Reliability Assessment and Component Correlation Analysis
  Mahdi Ghavaminejad, Van-Hai Bui, Mengqi Wang, Wencong Su, Niccolò Meneghetti, Duc Dung Le
  ECCE 2025 (IEEE Energy Conversion Conference Congress and Exposition), Philadelphia, PA, USA, 2025, pages 1-7 (ieee)

• An Approach to Enhancing Fairness in a Dynamically Growing Federated Learning Environments
  Sean Vucinich, Qiang Zhu and Niccolò Meneghetti
  IEEE BigComp 2025 (Proceedings of the 2025 IEEE International Conference on Big Data and Smart Computing), pages 244-251. (pdf, ieee)

• StarfishDB: A Query Execution Engine for Relational Probabilistic Programming
  Ouael Ben Amara, Sami Hadouaj and Niccolò Meneghetti
  SIGMOD 2024, Vol 2, no. 3, pages 1-31. (pdf, acm, reproducibility, code)

• Gamma Probabilistic Databases: Learning from Exchangeable Query-Answers
  Niccolò Meneghetti, Ouael Ben Amara
  EDBT 2022, Vol 25, pages 260–273. (pdf, yt)

• Learning From Query-Answers: A Scalable Approach to Belief Updating and Parameter Learning
  Niccolò Meneghetti, Oliver Kennedy and Wolfgang Gatterbauer
  TODS 2018, special issue on "Best of SIGMOD 2017 Papers",
  Volume 43 Issue 4, December 2018, Article No. 17, pages 1-41. (pdf, acm)

• Beta Probabilistic Databases: A Scalable Approach to Belief Updating and Parameter Learning
  Niccolò Meneghetti, Oliver Kennedy and Wolfgang Gatterbauer
  SIGMOD 2017, pages 573-586 (pdf, acm, yt)

• Output-sensitive Evaluation of Prioritized Skyline Queries
  Niccolò Meneghetti, Denis Mindolin, Paolo Ciaccia and Jan Chomicki
  SIGMOD 2015, pages 1955-1967. (pdf, acm)

• Lenses: An On-Demand Approach to ETL
  Y. Yang, N. Meneghetti, R. Fehling, Z.H. Liu and O. Kennedy
  VLDB 2015, Volume 8 Issue 12, August 2015, pages 1578-1589. (pdf, acm)

• Probabilistic Skylines
  Niccolò Meneghetti
  In Liu L., Özsu M. (eds) Encyclopedia of Database Systems (2016)
  Springer, New York, NY, pages 2845-2847. (doi)

• Skyline queries, front and back
  Jan Chomicki, Paolo Ciaccia and Niccolò Meneghetti
  SIGMOD Record Vol. 42, Issue 3, pages 6-18, 2013. (acm)

Reproducibility Reports

• Reproducibility Report for ACM SIGMOD 2025 Paper: ‘An Elephant Under the Microscope: Analyzing the Interaction of Optimizer Components in PostgreSQL’
  Niccolò Meneghetti, Kyle Deeds, and Rico Bergmann
  SIGMOD ARI 2025, pages 87-95 (report)

• Reproducibility Report for ACM SIGMOD 2024 Paper: ‘PreVision: An Out-of-Core Matrix Computation System with Optimal Buffer Replacement’
  Niccolò Meneghetti, Hein Meling, Kyoseung Koo, and Yoojin Choi
  SIGMOD ARI 2024, pages 34-43 (report)

• Reproducibility Report for ACM SIGMOD 2024 Paper: ‘StarfishDB: A Query Execution Engine for Relational Probabilistic Programming
  Alexander Krause, Georgiy Lebedev, Sami Hadouaj, Ouael Ben Amara, and Niccolò Meneghetti
  SIGMOD ARI 2024, pages 28-31 (report, code)

Talks

• StarfishDB: Probabilistic Programming Datalog in Action
  North East Database Day 2024 @ Boston University.
  (website, slides)

• Query-Driven Probabilistic Programming
  North East Database Day 2023 @ Northeastern University.
  (website, slides)

• Beta Probabilistic Databases: A Scalable Approach to Belief Updating and Parameter Learning
  Seminar on Scalable Management and Analysis of Big Data, DATA Lab @ Northeastern, Fall 2017
  (website)