Rate My Professor Dinusha Vatsalan

Dr. Vatsalan's research specializes in privacy-preserving technologies for data matching, record linkage, data mining, machine learning, data sharing, privacy risk quantification, and defenses against attacks on machine learning models. She has authored over 60 scientific articles, including highly cited works such as 'Privacy-preserving record linkage for big data: current approaches and research challenges' (2017), 'Privacy-Preserving Deep Learning Based Record Linkage' in IEEE Transactions on Knowledge and Data Engineering (2024), 'Privacy risk quantification in education data using Markov model' in British Journal of Educational Technology (2022), and book chapters like 'Privacy-Preserving Record Linkage' in Springer Encyclopedia of Big Data Technologies (2019). Her contributions appear in prestigious venues including IEEE TKDE, IEEE TIFS, and ACM conferences. She has received major awards including the Australian Government’s Endeavour Postgraduate Research Award, Ruby Payne-Scott Award and Women in Science Career Award from CSIRO, Data61 Research Plus PhD Scholarship, Australia-Germany Joint Research Cooperation Scheme grant, and Best Student Paper Award at ITNAC 2020. At Macquarie University, she teaches units such as COMP6013 Introduction to Cyber Security, COMP6310 Digital Forensics, COMP8220 Machine Learning, and COMP6325 Cyber Security Management in Practice. Her work advances privacy-preserving techniques for big data and cyber-physical systems, contributing to secure data analytics and AI model robustness.