Dinusha Vatsalan


Dinusha Vatsalan

Research Scientist,
Information Security and Privacy Group
Software and Computational Systems Program
Data61-CSIRO

Contact

email: first{dot}last{@}data61{dot}csiro{dot}au
phone: +61 2 9490 5734


News

Short Bio

Dr. Dinusha Vatsalan is a Research Scientist at Data61-CSIRO, Australia, and an Honorary Lecturer in the Research School of Computer Science at the Australian National University. Her research interests are mainly in privacy preserving techniques, including privacy in data matching and mining, privacy in social media, privacy preserving counting in stream data analytics, privacy risk evaluation and prediction, health informatics, and population informatics.

Education:

Work Experience:

  • Research Scientist – Information Security and Privacy group, Software and Computational Systems Research Program, Data61-CSIRO, Sydney, Australia, April 2017 – Present
  • Honorary Lecturer – Research School of Computer Science, Australian National University, Canberra, Australia, May 2017 – Present.
  • Research Fellow (Level B) – Research School of Computer Science, Australian National University, Canberra, Australia, Oct 2014 – Apr 2017.
  • Research Assistant – Research School of Computer Science, Australian National University, Canberra, Australia, Feb 2012 – May 2012; and Sep 2013 – Nov 2013.
  • Tutor – Research School of Computer Science, Australian National University, Canberra, Australia, Feb 2013 – Jun 2013.
  • Instructor – School of Computing, University of Colombo, Sri Lanka, Nov 2009 – Nov 2010.
  • Trainee Software Engineer – Aeturnum (Pvt) Ltd, Sri Lanka, Feb 2008 – Aug 2008.

Awards & Grants:

  • Ruby Payne-Scott Award – Awarded by CSIRO, 2019
  • Women in Science Career Award – Awarded by Software & Computational Systems Awards, Data61, CSIRO, 2018
  • Early Career Researcher Travel Award – Funded by the Australian National University, 2016.
  • Data Linkage and Anonymisation Programme participant –  Funded by the Isaac Newton Institute for Mathematical Sciences, Cambridge, UK, 2016.
  • Investigator and mentor for the project Privacy-preserving medical data linkage – Awarded by Google Summer of Code 2016.
  • Co-investigator for the project Advancing data integration: Privacy and semantics for record linkage – Awarded by the Australia-Germany Joint Research Cooperation Scheme, 2015-2016.
  • Endeavour Postgraduate Research Award – Awarded by the Australian Government, DEEWR, 2011.
  • Recognition of Women in Data Mining Citation – Awarded by AusDM 2011 Conference, 2011.
  • NBQSA Silver Award – National Best Quality Software Awards, ViduSuwa eHealth Project, eHealth Track, 2010.
  • Manthan Award South Asia – South Asia’s Best e-Content Award, ViduSuwa eHealth Project, eHealth Track, 2009.
  • eSwabhimani Award – National Best e-Content Award, ViduSuwa eHealth Project, eHealth and Environment Category, 2009.
  • eIndia 2009 Speaker Award – Awarded by the eIndia Conferece, eHealth Track, 2009.

Professional Services:

  • Expert Panel Member – PhD Doctor Forum, Information Processing in Sensor Networks (ISPN) 2020
  • PhD thesis examiner – Privacy Protection of Online Social Media Users from Malicious Data Miners, Charles Sturt University, 2020
  • Phd thesis examiner – Data Science for Class Imbalanced and Cost-Sensitive Data and its Application to Software Defect Prediction, Charles Sturt University, 2018
  • Master of Research thesis examiner – An Empirical Investigation of Privacy via Obfuscation in Social Networks, Nicholas Reynolds, Macquaire University, 2018
  • PhD thesis examiner – Data mining and privacy: Modeling Sensitive Data with Differential Privacy, Charles Sturt University, 2017
  • Expert evaluator – Prestige Marie Curie Postdoctoral Fellowship Programme, 2017
  • Lecturer – ANU online course: Master of Applied Data Analytics – Data Wrangling (COMP8430) , 2017
  • PhD supervisor – Dr. Thilina Ranbaduge, A Scalable Blocking Framework for Multidatabase Privacy-preserving Record Linkage, ANU, 2014-2017; Mr. Yichen Hu, Temporal record linkage, ANU, 2016-present; Ms. Marwa Hassan, Protection of Data Privacy based Artificial Intelligence in Cyber-Physical Systems, UNSW Canberra, CSIRO-Data61, 2019 – present; Ms. Maryam Shahpasand, Adversarial Attacks in Malware Detection, Macquarie University, 2018 – present
  • Masters supervisor – Mr. Yuebin (Alex) Zhao, Predicting number of patient admissions in the emergency department using machine learning techniques, ANU Research School of Medical Science, 2016-2017; Mr. Chong Feng, Improve Record Linkage Using Active Learning Techniques, ANU, 2016; Mr. Narayan Mani, Identify Households with Similar Hierarchies, ANU, 2015;
  • Research Project Supervisor – Andrew Rajchert, University of Sydney, Data61 Undergraduate Vacation Scholar, 2019-2020
  • Mentor – Mr. Mathuvarman Mounasamy, Private Medical Data Comparison Functions for Similar Patient Matching: textual data matching, Google Summer of Code, 2016
  • Reviewer – IEEE Access 2020; IEEE Communications Letters 2020, Science Advances 2020; Journal of Biomedical Informatics 2019; International Journal of Population Data Science (IJPDS) 2018; Very Large DataBases (VLDB) Journal 2018; Elsevier Journal of Information Systems 2017; Elsevier Journal of Biomedical Informatics (JBI) 2018, 2017, 2016, ACM Journal of Data and Information Quality (JDIQ) 2017; Elsevier Journal of Computers and Security 2017; Transactions on Knowledge and Data Engineering (TKDE) 2015, 2016; Journal of Knowledge and Information Systems 2015, 2016; Journal of BioMed Central (BMC) Medical Research Methodology 2015; Journal of Algorithms 2015
  • External Reviewer – IEEE Local Computer Networks (LCN) Conference 2017; IEEE ICDM 2015; Springer PAKDD 2014, 2015; ACM Knowledge Discovery and Data mining (KDD) 2015; and Journal of Privacy and Confidentiality (CMU) 2015.
  • Co-organizer – International Workshop on Population Informatics for Big Data (PopInfo) 2015 co-located with the ACM KDD Conference.
  • Organizing Committee Member – AusDM 2013, Canberra; ICTer 2010 conferences
  • Program Committee Member – Springer Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD) 2019-2020; PhD Forum Panel Member of the ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN) 2020; WSDM Conference Workshop on PrivateNLP 2020; Springer International Symposium on Algorithmic Aspects of Cloud Computing (AlgoCloud) 2018; IEEE International Conference on Data Mining Workshop on Data Integration and Applications (DINA) 2014 – 2019; AusDM Conference 2014 -2019.

Projects

  • Privacy Preserving Linkage Enhancements with the Department of Social Science, Australia
    • Funded by the Platform for Open Data (PfOD) 2019-2020
    • Involved as a researcher and conducted research and development in the topics of fairness-aware privacy-preserving record linkage (PPRL), improving scalability of PPRL, and Information leakage in linkage schema optimization
  • Fake news identification in Social Media
    • In collaboration with LaTrobe University, Australia
    • Involved in conducting research in cyber security and usable security
  • Privacy-preserving Data Encoding and Matching using Probabilistic methods (PriDEMatch)
    • Leading the research project on developing privacy preserving data encoding and matching techniques using probabilistic methods for different types of data
    • Developed privacy-preserving matching techniques for different applications – privacy-preserving similar entity matching, privacy-preserving record linkage, privacy-preserving data aggregation, privacy-preserving machine learning, and privacy-preserving data analytics
  • Privacy-preserving Medical data Linkage (PriMedLink)
    • Involved as an investigator and mentor for the PriMedLink project that aims to research and develop novel algorithms for privacy-preserving linking of medical data for health analytics (such as similar patient matching, clinical trials, and customized treatment)
    • Open source software development funded by Google Summer of Code 2016
  • Multi-Party Privacy-Preserving Record Linkage (MP-PPRL)
    • Developed several novel software algorithms for privacy-preserving record linkage of multiple large databases using data mining techniques and privacy-preserving techniques
    • Funded by the ARC Discovery Project grant DP130101801
  • Privacy-Preserving Record Linkage (PPRL)
    • Conducted extensive research on PPRL techniques and developed novel software algorithms addressing the current gaps in PPRL
    • Funded by the Australian government (DEEWR) – Endeavour postgraduate research award
  • A flexible and extensible personal data generator and corruptor
    • Involved in the development, testing, and manual writing of a synthetic personal data and temporal data generator for Fujitsu Laboratories, Japan using the Python programing language; and a web-based GUI GeCo using Python, HTML, PHP, JS, AJAX, and JSON
  • ViduSuwa: A Mobile Telemedicine Solution for Patients in Emerging Countries
    • Involved in the eHealth research project, ViduSuwa, on mobile technologies for enhancing eHealth solutions using Electronic Medical Record (EMR) and M-Communication systems implemented using J2EE and J2ME
    • Conducted research on mobile technologies for enhancing eHealth solutions and published research outcomes in conference proceedings and a journal article
    • Funded by the Information and Communication Technology Agency (ICTA) Sri Lanka

Publications

Journal articles:

  1. P4Mobi: A Probabilistic Privacy-Preserving Framework for Publishing Mobility Datasets, Qing Yang, Yiran Shen, Dinusha Vatsalan, Jianpei Zhang, Mohamed Ali Kaafar, and Wen Hu, IEEE Transactions on Vehicular Technology, 2020
  2. Incremental clustering techniques for multi-party Privacy-Preserving Record Linkage, Dinusha Vatsalan, Peter Christen, and Erhard Rahm, Elsevier Data and Knowledge Engineering, 2020
  3. Sequence Data Matching and Beyond: New Privacy-preserving Primitives based on Bloom Filters, Wanli Xue, Dinusha Vatsalan, Wen Hu, Aruna Seneviratne, IEEE Transactions on Information Forensics and Security, 2020
  4. Secure Multi-party Summation Protocols: Are They Secure Enough Under Collusion? Thilina Ranbaduge, Dinusha Vatsalan, Peter Christen. Transactions of Data Privacy, 2019
  5. A Privacy-Preserving Framework based Blockchain and Deep Learning for Protecting Smart Power Networks. Marwa Hassan, Benjamin Turnbull, Nour Moustafa, Dinusha Vatsalan, and Raymond Choo. IEEE Transactions on Industrial Informatics, 2019
  6. Precise and Fast Cryptanalysis for Bloom Filter Based Privacy-Preserving Record Linkage. Peter Christen, Thilina Ranbaduge, Dinusha Vatsalan, and Rainer Schnell. Transactions on Knowledge and Data Engineering (IEEE), 2018.
  7. DLforum – A multidisciplinary online discussion forum for data linkage researchers and practitioners. Peter Christen, Thilina Ranbaduge, and Dinusha Vatsalan. International Journal of Population Data Science (IJPDS), volume 3, issue 1, February 2018.
  8. Automatic Discovery of Abnormal Values in Large Textual Databases. Peter Christen, Ross Gayler, Khoi-Nguyen Tran, Jeffrey Fisher and Dinusha Vatsalan. Journal of Data and Information Quality (ACM), volume 7, issue 1-2, April 2016. Article available online at dx.doi.org/10.1145/2889311
  9. Privacy-preserving matching of similar patients. Dinusha Vatsalan and Peter Christen. Journal of Biomedical Informatics (Elsevier), volume 59, February 2016, Pages 285-298. Article available online at doi:10.1016/j.jbi.2015.12.004.
  10. An Evaluation Framework for Privacy-Preserving Record Linkage. Dinusha Vatsalan, Peter Christen, Christine M. O’Keefe, and Vassillios S. Verykios. Journal of Privacy and Confidentiality (CMU), 6(1), 2014
  11. Challenges for privacy preservation in data integration. Peter Christen, Dinusha Vatsalan, and Vassilios S. Verykios. Journal of Data and Information Quality (ACM), volume 5, issue 1-2, September 2014. Article available online at http://dl.acm.org/citation.cfm?id=2629604.
  12. A taxonomy of privacy-preserving record linkage techniques. Dinusha Vatsalan, Peter Christen, and Vassilios S. Verykios. In Journal of Information Systems (Elsevier), volume 38, issue 6, September 2013, Pages 946-969. Article available online at http://dx.doi.org/10.1016/j.is.2012.11.005. (One of the most cited Information Systems articles – http://www.journals.elsevier.com/information-systems/most-cited-articles)
  13. eClinics Integration Techniques for Clinical Information Systems Moving in to a National Network. Dinusha Vatsalan, Shiromi Arunatilake, Keith Chapman, Saatviga Sudhahar, Chamal Abeywardhana. In Sri Lanka Journal of Bio-Medical Informatics, volume 2, issue 4, June 2012, Pages 130-143. Article available online at http://dx.doi.org/10.4038/sljbmi.v2i4.2257.

Book chapters:

  1. Privacy-Preserving Record Linkage. Dinusha Vatsalan, Dimitrios Karapiperis, and Vassilios Verykios. Invited book chapter in Springer Encyclopedia of Big Data Technologies, 2018
  2. Privacy-Preserving Record Linkage for Big Data: Current Approaches and Research Challenges. Dinusha Vatsalan, Ziad Sehili, Peter Christen, and Erhard Rahm. Book chapter in Big Data Handbook, Springer, 2016.
  3. Advanced Record Linkage Methods and Privacy Aspects for Population Reconstruction – A Survey and Case Studies. Peter Christen, Dinusha Vatsalan, and Zhichun Fu. Invited book chapter in Population Reconstruction. Gerrit Bloothooft, Peter Christen, Kees Mandemakers, and Marijn Schraagen (editors). Springer, August 2015.

Conference proceedings:

  1. Hyper-Parameter Optimization for Privacy-Preserving Record Linkage. Joyce Yu, Jakub Nabaglo, Dinusha Vatsalan, Wilko Henecka, and Brian Thorne. Data Integration and Applications (DINA) Workshop, ECML/PKDD Conference, September 2020.
  2. Fairness-Aware Privacy-Preserving Record Linkage. Dinusha Vatsalan, Joyce Yu, Wilko Henecka, and Brian Thorne. Data Privacy Management, European Sympoisum on Research in Computer Security (ESORICS) 2020.
  3. P-Signature-based Blocking to Improve the Scalability of Privacy-Preserving Record Linkage. Dinusha Vatsalan, Joyce Yu, Brian Thorne, and Wilko Henecka. Data Privacy Management, European Sympoisum on Research in Computer Security (ESORICS) 2020.
  4. Repairing of Record Linkage: Turning Errors into Insight. Quyen Bui-Nguyen, Qing Wang, Jingyu Shao, and Dinusha Vatsalan. International Conference on Extending Database Technology (EDBT), Lisbon, Portugal, March 2019.
  5. Adversarial Attacks on Mobile Malware Detection. Maryam Shahpasand, Len Hamey, Dinusha Vatsalan, and Jason Xue. SANER AI4Mobile workshop, Hangzhou, China, February 2019.
  6. An Overview of Big Data Issues in Privacy-Preserving Record Linkage. Dinusha Vatsalan, Dimitrios Karapiperis and Aris Gkoulalas-Divanis. International Symposium on Algorithmic Aspects of Cloud Computing (AlgoCloud), Helsinki, Finland, August 2018.
  7. Incognito: A Method for Obfuscating Web Data. Rahat Masood, Dinusha Vatsalan, Muhammad Ikram, and Mohamed Ali Kaafar. WWW, Lyon, France, April 2018.
  8. A Scalable and Efficient Subgroup Blocking Scheme for Multi-database Record Linkage. Thilina Ranbaduge, Dinusha Vatsalan, and Peter Christen, PAKDD, Melbourne, Australia, May 2018
  9. Efficient Cryptanalysis of Bloom Filters for Privacy-Preserving Record Linkage. Peter Christen, Rainer Schnell, Dinusha Vatsalan, and Thilina Ranbaduge. Proceedings of Springer PAKDD, Jeju Island, South Korea, May 2017.
  10. Improving Temporal Record Linkage using Regression Classification. Yichen Hu, Qing Wang, Dinusha Vatsalan, and Peter Christen. Proceedings of Springer PAKDD, Jeju Island, South Korea, May 2017.
  11. Evaluation of advanced techniques for multi-party privacy-preserving record linkage on real-world health databases. Thilina Ranbaduge, Dinusha Vatsalan, Sean Randall, and Peter Christen. Proceedings of the International Population Data Linkage Conference, Swansea, Wales, August 2016. Abstract available online at http://www.ipdlnconference2016.org/Programme/Abstract/89
  12. Scalable privacy-preserving linking of multiple databases using counting Bloom filters. Dinusha Vatsalan, Peter Christen, and Erhard Rahm. Proceedings of the ICDMW on Privacy and Discrimination in Data Mining (PDDM), Barcelona, Spain, December 2016. An extended version of the article is available in arXiv proceedings.
  13. Regression classification for improved temporal record linkage. Yichen Hu, Qing Wang, Dinusha Vatsalan, and Peter Christen. Proceedings of the AusDM, Canberra, December 2016.
  14. Scalable Block Scheduling for Efficient Multi-Database Record Linkage. Thilina Ranbaduge, Dinusha Vatsalan, and Peter Christen. Proceedings of the IEEE International Conference on Data Mining (ICDM’16), Barcelona, Spain, December 2016.
  15. Efficient Record Linkage Using a Compact Hamming Space. Dimitrios Karapiperis, Dinusha Vatsalan, Vassilios Verykios, and Peter Christen. Proceedings of the 19th International Conference on Extending Database Technology (EDBT’16), Bordeaux, France, March 2016. Paper (pdf, 1.9MB) available online in Open Proceedings.
  16. Hashing-based Distributed Multi-party Blocking for Privacy-preserving Record Linkage. Thilina Ranbaduge, Dinusha Vatsalan, Peter Christen, and Vassilios Verykios. Proceedings of the 20th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD’16), Auckland, New Zealand, April 2016. Paper (pdf, 532 KB) available online from Springer Link.
  17. MERLIN – A Tool for Multi-party Privacy-preserving Record Linkage. Thilina Ranbaduge, Dinusha Vatsalan, and Peter Christen. Proceedings of the IEEE International Conference on Data Mining (ICDM’15), Atlantic City, November 2015 (Demo paper).
  18. Efficient Entity Resolution with Adaptive and Interactive Training Data Selection. Peter Christen, Dinusha Vatsalan, and Qing Wang. Proceedings of the IEEE International Conference on Data Mining (ICDM’15), Atlantic City, November 2015 (Short paper).
  19. Efficient Interactive Training Selection for Large-scale Entity Resolution. Qing Wang, Dinusha Vatsalan, and Peter Christen. Proceedings of the 19th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD’15), Ho Chi Minh City, Vietnam, May 2015 (Full paper). Paper (pdf, 471 KB) available online from Springer Link.
  20. Clustering-based Scalable Indexing for Multi-party Privacy-preserving Record Linkage. Thilina Ranbaduge, Dinusha Vatsalan, and Peter Christen. Proceedings of the 19th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD’15), Ho Chi Minh City, Vietnam, May 2015 (Full paper). Paper (pdf, 382 KB) available online from Springer Link.
  21. Large-Scale Multi-party Counting Set Intersection Using a Space Efficient Global Synopsis. Dimitrios Karapiperis, Dinusha Vatsalan, Vassilios S. Verykios, and Peter Christen. Proceedings of the 20th International Conference on Database Systems for Advanced Applications (DASFAA’13), Hanoi, Vietnam, April 2015 (Full Paper). Paper available online from Springer Link.
  22. Scalable Privacy-Preserving Record Linkage for Multiple Databases. Dinusha Vatsalan and Peter Christen. Proceedings of the 23rd ACM International Conference on Information and Knowledge Management (CIKM’13), Shanghai, China, November 2014 (Poster paper). Paper (pdf, 460 KB) available online from ACM Digital Library Link. An extended version of the article is available in arXiv proceedings.
  23. Tree Based Scalable Indexing for Multi-Party Privacy-Preserving Record Linkage. Thilina Ranbaduge, Peter Christen, Dinusha Vatsalan. Proceedings of the 12th Australasian Data Mining Conference, Brisbane, Australia, November 2014 (Full paper). Paper (pdf, 754 KB) available online.
  24. Efficient two-party private blocking based on sorted nearest neighborhood clustering. Dinusha Vatsalan, Peter Christen, and Vassilios S. Verykios. Proceedings of the 22nd ACM International Conference on Information and Knowledge Management (CIKM’13), San Francisco, United States, October 2013 (Full paper). Paper (pdf, 5.5 MB) available online from ACM Digital Library Link.
  25. Flexible and extensible generation and corruption of personal data. Peter Christen and Dinusha Vatsalan. Proceedings of the 22nd ACM International Conference on Information and Knowledge Management (CIKM’13), San Francisco, United States, October 2013 (Poster paper). Paper (pdf, 394 KB) available online from ACM Digital Library Link.
  26. GeCo: an online personal data generator and corruptor. Khoi-Nguyen Tran, Dinusha Vatsalan, and Peter Christen. Proceedings of the 22nd ACM International Conference on Information and Knowledge Management (CIKM’13), San Francisco, United States, October 2013 (Demo paper). Paper (pdf, 592 KB) available online from ACM Digital Library Link.
  27. Sorted Nearest Neighborhood Clustering for Efficient Private Blocking. Dinusha Vatsalan and Peter Christen. Proceedings of the 17th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD’13), Gold Coast, Australia, April 2013 (Full paper). Paper (pdf, 456 KB) available online from Springer Link.
  28. An Iterative Two-Party Protocol for Scalable Privacy-Preserving Record Linkage. Dinusha Vatsalan and Peter Christen. Proceedings of the 10th Australasian Data Mining Conference (AusDM’12), Sydney, December 2012 (Full paper). Paper (pdf, 682 KB) available online from Conferences in Research and Practice in Information Technology (CRPIT), vol. 134.
  29. An Efficient Two-Party Protocol for Approximate Matching in Private Record Linkage. Dinusha Vatsalan, Peter Christen and Vassilios Verykios. Proceedings of the 9th Australasian Data Mining Conference (AusDM’11), Ballarat, December 2011 (Full paper). Paper (pdf, 880 KB) available online from Conferences in Research and Practice in Information Technology (CRPIT), vol. 121.
  30. Mobile technologies for enhancing eHealth solutions in developing countries. Dinusha Vatsalan, Shiromi Arunatileka, Keith Chapman, Gihan Senaviratne, Saatviga Sudahar, Dulindra Wijetileka, Yvonne Wickramasinghe. Proceedings of the 2nd International Conference on eHealth, Telemedicine and Social Medicine (eTelemed 2010), Sint Maarten, Netherlands Antilles (Full paper). Paper (pdf, 571 KB) available online from IEEE Xplore.
  31. Enhancing e-Health using m-Communication in Developing Countries. Dinusha Vatsalan, Shiromi Arunatileka, Keith Chapman, Gihan Senaviratne, Saatviga Sudahar, Dulindra Wijetileka, Yvonne Wickramasinghe. Proceedings of the 5th eIndia Conference 2009, Hyderabad, India (Full paper). Paper available online from elets online.
  32. Enhancing Rural Healthcare in Emerging Countries through an eHealth Solution. Saatviga Sudahar, Dinusha Vatsalan, Dulindra Wijetileka, Yvonne Wickramasinghe, Shiromi Arunatileka, Keith Chapman, Gihan Senaviratne. In proceedings of IEEE Xplore in conjunction with the Second International Conference on eHealth, Telemedicine, and Social Medicine (eTelemed 2010), St. Maarten, Netherlands Antilles, Feb 10 – 16, 2010.
  33. BudhuDas: An eHealth Business Model for emerging countries. Yvonne Wickramasinghe, Dulindra Wijetileka, Dinusha Vatsalan, Saatviga Sudahar, Shiromi Arunatileka, Gihan Senaviratne, Kenneth Thilakarathna, Keith Chapman, Prathibha Mahanamahewa. In proceedings of IEEE Xplore in conjunction with IST-Africa, 2010.
  34. HealthChange: A change management model for an eHealth solution in developing countries. Dulindra Wijetileka, Dinusha Vatsalan, Gihan Senaviratne, Keith Chapman, Kenneth Thilakarathna, Saatviga Sudahar, Shiromi Arunatileka, Yvonne Wickramasinghe. In proceedings of IEEE Xplore in conjunction with IST-Africa, 2010.

Other:

  1. Scalable and Approximate Privacy-Preserving Record Linkage. Dinusha Vatsalan. PhD Thesis, Research School of Computer Science, College of Engineering and Computer Science, The Australian National University, October 2014. Thesis available online at ANU Digital Theses.
  2. A flexible data generator for privacy-preserving data mining and record linkage. Peter Christen and Dinusha Vatsalan. User Manual, Fujitsu Laboratories Collaboration, Research School of Computer Science, College of Engineering and Computer Science, The Australian National University, 2012
  3. Enhancing e-Health using m-Communication in Developing Countries. Dinusha Vatsalan, Shiromi Arunatileka, Keith Chapman, Gihan Senaviratne, Saatviga Sudahar, Dulindra Wijetileka, Yvonne Wickramasinghe. Magazine article, 2009.

Google Scholar Profile Page:

https://scholar.google.com.au/citations?user=gQhiZhcAAAAJ&hl=en

Invited talks and seminars:

  • Multi-Party Privacy Preserving Record Linkage Techniques. Dinusha Vatsalan. Invited presentation at Entity Resolution Workshop, Data61, November 2019.
  • Probabilistic methods for privacy preserving techniques. Dinusha Vatsalan, Dali Kaafar, Peter Christen, Rahat Masood, Muhammad Ikram, and Qing Yang. Invited poster presentation at Data61 Science Review, Canberra, May 2019.
  • Privacy preserving record linkage. Dinusha Vatsalan. Invited presentation at the DPAIP Project Kick-off Workshop, Macquarie University, April, 2019.
  • Privacy preserving matching of different data types using probabilistic data structures. Dinusha Vatsalan. Invited presentation at the Data61 Privacy Preserving Record Linkage Workshop, Sydney, February 2019.
  • Privacy preserving set intersection. Dinusha Vatsalan. Seminar to the Information and Security Privacy group, Data61-CSIRO, Sydney, July 2017.
  • Privacy preserving techniques for data matching. Dinusha Vatsalan. Seminar to the Networks group, Data61-CSIRO, Sydney, January 2017.
  • Advanced Techniques for Privacy-Preserving Linking of Multiple Large Databases. Dinusha Vatsalan. Presentation at the Data Linkage and Anonymization Programme by the Isaac Newton Institute for Mathematical Sciences, University of Cambridge, September 2016. Slides (pdf, 2.7MB).
  • A Tutorial on Population Informatics using Big Data. Peter Christen, Hye-Chung Kum, Qing Wang, and Dinusha Vatsalan. Tutorial at the Pacific Asia Conference on Knowledge Discovery and Data Mining (PAKDD), Auckland, New Zealand, April 2016. Slides (pdf, 15MB).
  • Techniques for Scalable Privacy-preserving Record Linkage. Peter Christen, Vassilios S. Verykios, and Dinusha Vatsalan. Tutorial at the 22nd ACM International Conference on Information and Knowledge Management (CIKM’13), San Francisco, United States, October 2013. Slides (pdf, 2.6 MB).
  • Scalable Privacy-preserving Record Linkage. Dinusha Vatsalan and Peter Christen. Invited presentation at the Australian Bureau of Statistics, Canberra, Australia, June 2013. Slides (pdf, 3 MB).
  • An Iterative Two-Party Protocol for Privacy-Preserving Record Linkage using Bloom Filters. Dinusha Vatsalan and Peter Christen. Invited presentation at the SAX Institute, Sydney, Australia and NICTA, Sydney, Australia, December 2012. Slides (pdf, 2.4 MB).