Dr Priyaa Thavasimani


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In my career, I dealt with voluminous data. The more I dealt with voluminous data, the more I am interested in learning about Big Data Analytics. I was amazed and passionate about how the data sets are used to identify the character of an individual. During the course of my Ph.D., I have dealt with US healthcare data which I analyzed to build Healthcare Fraud Detection System and also NASA imagery to build flood prediction system. Apart from this, I have dealt with a large amount of Netflix movie dataset (used ALS machine learning algorithms) to suggest movies based on past ratings as well social-media data for analyzing sentiments. I am more curious to investigate Big-Data and to make sense of it. I am keen to update my knowledge with current trends in Big Data Research by organizing international workshops and hackathon. One of the workshop and hackathon organized along with RDA is IEEE BDGMM (https://bigdatawg.nist.gov/bdgmm2018.html) and also by presenting papers at IEEE Big Data Conferences.
I have steered a state level workshop entitled “Advanced .NET Technologies” and two national level workshops on Android. Further, I have organized a CSIR funded national level seminar entitled “Energy Aware Computing”. I have given guest lectures on “Spring, Hibernate and Struts” Technologies and “Android”.

The complete profile includes my previous roles as a Data Scientist, Researcher, Assistant Professor, Software Engineer, and Guest Lecturer.

My publication details are at https://www.researchgate.net/profile/Priyaa_Thavasimani

Education / academic qualifications

  • Doctor of Philosophy, Why-Diff: Exploiting Execution Provenance to Understand Outcome Differences From Non-Identical Reproduced Workflows, Newcastle University (2015 - 2020)
  • Master of Engineering
  • Bachelor of Technology (not to be confused with BTEC)

Related information


Research output: Contribution to journalArticlepeer-review

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

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