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Dr. Fei Chiang

Assistant Professor

Department of Computing and Software

Expertise:
database systems; data quality; data privacy; data analytics; information extraction; text mining.
Areas of Specialization:
Research Clusters:

Overview

Fei Chiang is an Assistant Professor in the Department of Computing and Software, Faculty of Engineering. Her research interests are broadly in the area of data management, with a focus on data quality, data analytics, data privacy, text mining, and information extraction. She has worked at IBM Global Services, in the Autonomic Computing Group at the IBM Toronto Lab, and in the Data Management, Exploration and Mining Group at Microsoft Research.  She received her M. Math from the University of Waterloo, and B.Sc and PhD degrees from the University of Toronto, all in Computer Science.  She is an IBM CAS Faculty Fellow, and a recipient of a 2018 Ontario Early Researcher Award.

Education

Hons. B.Sc. in Computer Science, Major in Mathematics, University of Toronto  

M. Math in Computer Science, University of Waterloo

Certificate in Teaching in Higher Education, University of Waterloo

PhD in Computer Science, University of Toronto

Biography

Fei Chiang is an Assistant Professor in the Department of Computing and Software, where her data management experience spans academic and industry roles, including serving as an inaugural Associate Director of McMaster's MacData Institute.  She leads the Data Science Research Group, focused on developing tools to facilitate data cleaning, improved data quality and fostering knowledge discovery.  Her research in discovering data quality rules, and developing data cleaning algorithms, has been published in top-tier venues.  She holds 4 patents for her work in self-managing databases, and is a Faculty Fellow at the IBM Centre for Advanced Studies, where she is the PI to develop data quality metrics for IBM Watson Analytics.  She has been invited as a featured speaker and panelist, and her work has been featured in McMaster Research News, and the SOSCIP 2017 Impact Report.   She is the recipient of a 2018 Ontario Early Researcher Award. 

Publications

Recent

(DBLP List of Publications)

    • F. Rahimi Asl, F. Chiang, W. He, R. Samavi. Privacy Aware Web Services with Data Obfuscation. In Workshop on Security and Privacy in the Cloud 2017.
    •  Y. Huang, F. Chiang, A. Maier, M. Petitclerc, Y. Saillet, D. Spisic, C. Zuzarte. Quantifying Duplication to Improve Data Quality". In Cascon 2017. 
    • S. Baskaran, A. Keller, F. Chiang, L. Golab, J. Szlichta. Efficient Discovery of Ontology Functional Dependencies.  In CIKM 2017. 
    • Y. Huang, F. Chiang, Refining Duplicate Detection for Improved Data Quality. In Meta-Data Quality Workshop 2017. 
    • D. Huang, F. Chiang, D. Gairola. PARC: Privacy-Aware Data Cleaning. In CIKM 2016 (demo track).
    • F. Chiang, S. Sitaramachandran. Unification of Data and Constraint Repairs. ACM Journal of Data and Information Quality (JDIQ) 2016.
    • 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
    • Fei Chiang, Siddharth Sitaramachandran. A Data Quality Framework for Customer Relationship Analytics. QUAT 2015 (in conjunction with WISE), pp. 366-378
    • 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 2014 (held in conjunction with PAKDD), 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.
    • R. Khedri, F. Chiang, K. Eddin Sabri. An Algebraic Approach Towards Data Cleaning.
      In Intl. Conf. on Emerging Ubiquitous Systems and Pervasive Networks (EUSPN '13) pp.50-59.

Patents

  • I. Elghandour, A. Aboulnaga, D. Zilio, F. Chiang, A. Balmin, K. Beyer, C. Zuzarte.
    XML Index Recommendation with Tight Optimizer Coupling. Filed Sept. 2007.
  • F. Chiang, B. Schiefer, S. Lightstone.
    Method and Model for Calculating the Default Database Memory Allocation, published Jan. 2006.
  • S. Lightstone, F. Chiang, I. Lew, I. Popivanov, M. Emmerton.
    Approximate Time Constrained Database Activation, published Jan. 2006.
  • F. Chiang, S. Lightstone, L. Cranston, D. Zilio.
    Method and Apparatus for Automatic Recommendation and Selection of Clustering Indexes, US Patent 7548903. Issued Jan. 2005.

Achievements

  • Ontario Early Researcher Award (2018)
  • Dean's Teaching Honour Roll (2017)
  • IBM Centre for Advanced Studies Faculty Fellow (2015-2019)