Selected Publications

  • N. Li, D. Arnold, R. Barty, J. Blake, D. Down, F. Chiang, T. Courtney, M. Waito, R. Trifunove, N. Heddle. “From Demand Forecasting to Inventory Ordering Decisions for Red Blood Cells Through Integrating Machine Learning, Statistical Modeling and Inventory Optimization”. Transfusion, 2021.  (To appear) 
  • L. Noronha, F. Chiang. “Discovering Temporal Graph Functional Dependencies.”  To appear in CIKM 2021 (short paper).
  • N.Li, D. Down, F. Chiang, N. Heddle.  “A Decision integration strategy for short-term demand forecasting and ordering for red blood cell components.”  Operations Research for Health Care.  2021.
  • M. Milani, Y. Huang, F. Chiang. “Preserving Diversity in Anonymized Data”.  EDBT 2021, pp. 511-516.
  • Y. Huang, M. Milani, F. Chiang. “Privacy-Aware Data Cleaning-as-a-Service”.  Information Systems Vol. 94, 2020.
  • Z. Zheng, T. Quach, Z. Jin, M. Milani, F. Chiang. “CurrentClean: Interactive Change Exploration and Cleaning of Stale Data”.  CIKM 2019, pp. 2917-2920.
  • H. Ma, M. Alipour Langouri, Y. Wu, F. Chiang, J. Pi.  “Ontology-based Entity Matching in Attributed Graphs”.  VLDB 2019, pp. 1195 – 1207.
  • M. Milani, Z. Zheng, F. Chiang “CurrentClean: Spatio-temporal Cleaning of Stale Data.”  ICDE 2019, pp. 172-183.
  • Y. Huang, M. Milani, F. Chiang.  “PACAS: Privacy-Aware, Data Cleaning-as-a-Service”. IEEE International Conference on Big Data, pp. 1023-1030, 2018.
  • M. Langouri, F. Chiang.  “KeyMiner: Discovering Keys for Graphs”.  In VLDB workshop on Advances in Mining Large-Scale Time Dependent Graphs, 2018.
  • M. Langouri, Z. Zheng, F. Chiang, L. Golab, J. Szlichta.  “Contextual Data Cleaning”.  In ICDE workshop on Context in Analytics, 2018.
  • F. Chiang, D. Gairola.  “InfoClean: Protecting Sensitive Information in Data Cleaning”.  In ACM Journal of Data and Information Quality. Vol. 9(4), 2018, pp. 1-26
  • Z. Zheng, M. Alipour Langouri, Z. Qu, I. Currie, F. Chiang, L. Golab, J. Szlichta.  “FastOFD: Contextual Data Cleaning with Ontology Functional Dependencies”.  In EDBT pp. 694-697, 2018 (demo track).
  • S. Baskaran, A. Keller, F. Chiang, J. Szlichta, L. Golab. “Efficient Discovery of Ontology Functional Dependencies”. In CIKM, pp. 1847-1856, 2017.
  • Y. Huang, F. Chiang. “Refining Duplicate Detection for Improved Data Quality”. Meta-Data
    Quality Workshop, 10 pages, 2017.
  • F. Rahimi Asl, F. Chiang, W. He, R. Samavi. “Privacy Aware Web Services with Data Obfuscation”.
    Workshop on Security and Privacy in the Cloud (SPC),  pp. 458-466, 2017.
  • Y. Huang, F. Chiang, A. Maier, M. Petitclerc, Y. Saillet, D. Spisic, C. Zuzarte. “Quantifying
    Duplication to Improve Data Quality”. In ACM CASCON Conference, pp. 272-278, 2017.
  • F. Chiang, S. Sitaramachandran. Unification of Data and Constraint Repairs. ACM Journal of Data and Information Quality (JDIQ) 2016, pp. 1-26.
  • D. Huang, F. Chiang, D. Gairola. PARC: Privacy-Aware Data Cleaning”. In CIKM 2016, pp. 2433-2436. (demo track)
  • Fei Chiang, Periklis Andritsos, Renée J. Miller. Data Driven Discovery of Attribute Dictionaries. Trans. Computational Collective Intelligence 21 (2016), pp. 69-96.
  • Nataliya Prokoshyna, Jaroslaw Szlichta, Fei Chiang, Renée J. Miller, Divesh Srivastava. Combining Quantitative and Logical Data Cleaning. PVLDB 9(4) (2015), pp. 300-311.
  • Yu Huang, Fei Chiang. Towards a Unified Framework for Data Cleaning and Data Privacy. QUAT 2015 (in conjunction with WISE), pp. 359-365.
  • J. Segeren, D. Gairola, F. Chiang. CONDOR: A System for CONstraint DiscOvery and Repair. In CIKM 2014 (demo track) pp. 2087-2089.
  • V. Maccio, F. Chiang, D. Down. Models for Distributed, Large Scale Data Cleaning. Workshop on Scalable Data Analytics (held in conjunction with PAKDD), 2014, pp. 369-380.
  • F. Chiang, Y. Wang. Repairing Integrity Rules for Improved Data Quality. In International Journal of Information Quality (IJIQ) 2014, Vol. 3, No. 4, pp. 273-297.
  • M. Volkovs, F. Chiang, J. Szlichta, R.J. Miller. Continuous Data Cleaning. In ICDE 2014, pp. 244-255.