I am currently working as a Research Fellow at the Australian National University (ANU), where my research is partially funded by the University of Edinburgh for my contribution to the Scottish Historic Population Platform (SHiPP) project [1] as part of my employment. I obtained my PhD degree from the ANU in 2022, where the focus of my doctoral research work was on proposing Effective Record Linkage Techniques for Complex Population Data [2]. Record linkage is the task of identifying records in a dataset which relate to the same entity. It is an important step in cleaning datasets (for duplicate removal) and extensively used for tasks such as population reconstruction. In the absence of unique identifiers per records, a record linkage method must be used to identify whether two records relate to the same entity. This task is particularly complicated where population datasets (data about people) are concerned, due to the many mistakes introduced to them at the time of data entry and transcription, errors and variations in names, and the imbalance in name distributions (many people sharing common names and few very uncommon names), etc. My focus is on developing effective record linkage techniques using which high quality population record linkage can be achieved. For a comprehensive list of my publications, please see my Google Scholar profile [3].

[1] https://www.scadr.ac.uk/our-research/scottish-historic-population-platform-shipp/population-data-linkage-scale

[2] https://openresearch-repository.anu.edu.au/handle/1885/264165

[3] https://scholar.google.com.au/citations?user=bQwdgp0AAAAJ&hl=en

Education:

• PhD from the Australian National University (2022)
• BSc. (Hons) Computer Science with first class from University of Colombo School of Computing, Sri Lanka (2016).

Work Experience:

• Research Fellow at the Australian National University (Nov 2022 – Present)
• Senior Research Officer at the Australian National University (Nov 2021 – Nov 2022)
• Tutor at the Australian National University (Mar 2019 - Jun 2022)
• Software Engineer at WSO2 (Jan 2016 - Jan 2018)
• Software Engineering Intern, Google Summer of Code (Jun 2020 - Aug 2020)
• Business Analyst Intern, Epic Lanka Pvt Ltd (Aug 2014 - Jan 2015)

Awards, Scholarships & Grants

• Researching the Scottish Historical Population Platform (SHiPP)  - Grant funding of 330,004 AUD  from Economic and Social Research Council (2022)
• ANU PhD Scholarship (International) (2018)
• ANU HDR Merit Scholarship (2018)

Publications:

• Locality Sensitive Hashing with Temporal and Spatial Constraints for Efficient Population Record Linkage, Charini Nanayakkara and Peter Christen, The International Conference on Information and Knowledge Management (CIKM), Atlanta, Georgia, USA (2022)
• Efficient Population Record Linkage With Temporal and Spatial Constraints, Charini Nanayakkara and Peter Christen, The International Population Data Linkage Network conference (IPDLN), Edinburgh, UK (2022)
• Unsupervised Graph-Based Entity Resolution for Accurate and Efficient Family Pedigree Search, Nishadi Kirielle, Charini Nanayakkara, Peter Christen, Chris Dibben, Lee Williamson, Eilidh Garrett, and Clair Manson, The International Conference on Extending Database Technology (EDBT), Edinburgh, UK (2022)
• Active Learning Based Similarity Filtering for Efficient and Effective Record Linkage, Charini Nanayakkara, Peter Christen, and Thilina Ranbaduge,  Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), Delhi (2021)
• An Anonymiser Tool for Sensitive Graph Data, Charini Nanayakkara, Peter Christen, and Thilina Ranbaduge, International Workshop on Entity Retrieval and Learning (EYRE) co-located with CIKM, Galway, Ireland (2020)
• Evaluation measure for group-based record linkage, Charini Nanayakkara, Peter Christen, Thilina Ranbaduge, and Eilidh Garrett, The International Journal of Population Data Science (IJPDS), Vol. 4, No. 1, (Nov 2019), DOI: https://doi.org/10.23889/ijpds.v4i1.1127
• Robust temporal graph clustering for group record linkage, Charini Nanayakkara, Peter Christen, and Thilina Ranbaduge, Springer PAKDD 2019, Macau, China, DOI: https://doi.org/10.1007/978-3-030-16145-3_41
• Temporal graph-based clustering for historical record linkage, Charini Nanayakkara, Peter Christen, and Thilina Ranbaduge, 14th International Workshop on Mining and Learning with Graphs (MLG) Workshop, held at ACM SIGKDD 2018, London, UK. Available: https://arxiv.org/pdf/1807.02262.pdf
• Identification of Musically Induced Emotion: A Machine Learning Based Approach, Charini Nanayakkara and Amitha Caldera, 3rd International Conference on Data Mining, Internet Computing, and Big Data, Konya, Turkey 2016
• Music Emotion Recognition with Audio and Lyrics Features, Charini Nanayakkara and Amitha Caldera, International Journal of Digital Information and Wireless Communications (IJDIWC), Vol. 6, No. 4, 260-273 (Oct 2016)