Chamari I. Kithulgoda

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Research Fellow - Data Scientist, Centre for Social Data Analytics (CSDA), School of Economics

Phone: +64 9 921 9999 – ext: 5097



  • 2019 PhD in Computer and Information Sciences, Auckland University of Technology (AUT), New Zealand.
  • 2012 MSc in Financial Mathematics, University of Moratuwa, Sri Lanka.
  • 2007 BSc (Special) (First Class Honours) in Statistics & Computer Science, University of Kelaniya, Sri Lanka.

Memberships and Affiliations:


  • Jan 2019- Present, Research Fellow - Data Scientist, CSDA, AUT, New Zealand.
  • Dec 2014 – Dec 2018, Doctoral Candidate, SECMS, AUT, New Zealand.
  • Oct 2017- Sept 2018, Computing Lecturer, CIBT, Auckland Campus, New Zealand.
  • Apr 2017 – Dec 2017, Research Officer, SECMS, AUT, New Zealand.
  • July 2016 – Dec 2017, Teaching Assistant, SECMS, AUT, New Zealand.
  • Aug 2008 – Nov 2014, Lecturer, University of Ruhuna, Sri Lanka.
  • May 2007 – Apr 2008, Tutor and Assistant Lecturer, University of Kelaniya, Sri Lanka.

Teaching Areas:

  • Data Mining and Machine Learning
  • Database Design and Administration
  • Application Developments
  • Object Oriented Programming
  • Data Structures and Algorithms
  • IT Project Management
  • Statistical Data Analysis

Research Areas:

  • Predictive Risk Modelling
  • Fairness in Machine Learning
  • Concept Drifting Data Stream Mining
  • Ensemble methods for machine learning challenges

Research Summary:

Chamari has over 10 years’ experience of working on data science, computer science, operational research, and statistics related research projects in universities, including several years as a full-time lecturer.

At CSDA, Chamari is working on predictive risk modelling research projects which aim to predict the risks associated with homelessness or likelihood of being a victim of a child maltreatment event. She is the lead Data Scientist of Allegheny County’s Homeless and Mental Health Housing Service Prioritization research projects. Chamari has contributed to Douglas County child welfare decision aid by assuring the quality of data to be modelled, performing external validation, and exploring alternative state-of-art ensemble decision models.

Furthermore, Chamari is interested in enhancing the throughput of high speed, concept drifting data stream classifiers without sacrificing its accuracy. In her PhD, she proposes a novel stage learning framework that senses the context of data to determine the level of volatility in the stream. In addition, Chamari introduces an innovative decision tree forest driven incremental Fourier classifier ensemble for classification in evolving data streams.

In her previous research engagements, she worked with facility location optimisation problems, and an e-Business collaboration modelling. During her tenure as a computer Science lecturer in Sri Lanka and New Zeeland, Chamari has worked as the primary supervisor for several undergraduate projects.

Current Research Projects:

  • Allegheny County Homelessness Housing Prioritization
  • Allegheny County Mental Health Housing Prioritization
  • Context-based Fairness in Machine Learning
  • Douglas County Child Welfare Decision Aid
  • Classification in High Speed Concept Drifting Data Streams
  • Trade-off between accuracy and throughput of ensemble classifiers


  1. Kithulgoda, C.I., Kulick, E., Horn, A., Dalton, E., Joyce, S. & Vaithianathan, R. (2019). Implementing a Predictive Risk Model to Prioritize Homeless Services: The Allegheny Homelessness Tool. Poster presented at the Data for Good Exchange 5th annual Bloomberg conference, New York, USA.
  2. Kithulgoda, C.I. (2019). A Staged Approach to Classification in High Speed Concept Drifting Data Streams, Doctoral thesis, Auckland University of Technology, Auckland, New Zealand.
  3. Kithulgoda, C. I. & Pears, R. (2019). A Context Sensitive Framework for Mining Concept Drifting Data Streams. In E. Lughofer & M.S. Mouchaweh (Eds.), Predictive Maintenance.
  4. Vaithianathan R, Dinh H, Kalisher A, Kithulgoda CI, Kulick E, Mayur M, Ning A, Prado DB (2019). Implementing a Child Welfare Decision Aide in Douglas County.
  5. Kithulgoda, C.I., Pears, R. & Naeem, M.A. (2018). The Incremental Fourier Classifier: Leveraging the Discrete Fourier Transform for Classifying High Speed Data Streams. Journal of Expert Systems with Applications, 97, 1– 17.
  6. Kithulgoda, C. I. & Pears, R. (2016, July). Staged Online Learning: A New Approach to Classification in High Speed Data Streams. Paper presented at the IEEE 2016 International Joint Conference on Neural Networks (IJCNN), Vancouver, BC, Canada.
  7. Kithulgoda, C. I. (2015, August). Data Stream System Classification Framework for Concept Recurring Situation. Abstract presented at the Postgraduate Research Symposium of Auckland University of Technology, Auckland, New Zealand.
  8. Kumarapathirana, K.P.S.D. & Kithulgoda, C.I. (2014), Intrusion Detection of Web Sites with Data Mining Techniques - A Survey. Proceedings of the Ruhuna International Science and Technology Conference.
  9. Kithulgoda, C.I. & Jayasundara, D.D.M. (2013) Optimizing the warehouse location and distributor allocation: A case study of the LPG distribution in Sri Lanka. Proceedings of the 2nd International Conference on Management and Economics 2013, pp.413-423
  10. Dias, G.R.U., Rathnayake, A.N.S., Karunarathna, E.M.C.M.B. & Kithulgoda, C.I. (2013), Perfect robotic salesperson developed using android app with GPS tracking, Invention & Innovation Exhibition, Faculty of Science, University of Ruhuna, Sri Lanka.
  11. Kithulgoda, C.I. & Jayaweera, P.P.M. (2012) Meeting Development Challenges by Introducing Global ICT Standards to Agricultural Industry in Sri Lanka, Proceedings of the1st International Research Conference on Humanities and Social Sciences.
  12. Kithulgoda, C.I. (2011) Collaboration Modelling Framework and Trading Portal for Agricultural Products, Master's thesis, University of Moratuwa, Sri Lanka.
  13. Kithulgoda, C.I. (2007) Locating Distribution Warehouses for Shell Gas Lanka Limited, Bachelor's thesis, University of Kelaniya, Sri Lanka.


  • 2014 – School of Engineering, Computer and Mathematical Sciences full PhD Scholarship as the top listed awardee, Auckland University of Technology, New Zealand
  • 2014 – Commonwealth Postgraduate Scholarships for MSc, University of York, United Kingdom (not proceeded due to PhD scholarship)
  • 2013 – Winners of the Information Technology Category at the Invention and Innovation Exhibition held at the Faculty of Science, University of Ruhuna, Sri Lanka.
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