Rozita Dara

Headshot of Rozita Dara
Associate Professor, Data Strategy Director (Ontario Agri-Food Innovation Alliance)
School of Computer Science
Phone number: 
(519) 824-4120 ext. 58762
Reynolds 3311
Seeking academic or industry partnerships in the area(s) of: 
Decision support systems, social media analytics, text document analytics, agent-based data protection, usable privacy policies, privacy preferences, and adaptive access control.
Seeking academic or industry partnerships in the area(s) of: 

Education and Employment Background

Professor Rozita Dara is the Principal Investigator of Data Management and Privacy Governance research program in the School of Computer Science at the University of Guelph. Prior to joining the University of Guelph in 2013, Professor Dara worked in industry (BlackBerry) and government (Office of Information and Privacy Commissioners/Ontario). She led research projects in the area of Mobile Health, in collaboration with University Health Network and Hospital for Sick Children. In collaboration with the Identity, Privacy and Security Institute at the University of Toronto, she led projects on building autonomous artificial intelligence algorithms to manage and protect data in the Internet of Things.

Research Themes

Prof. Dara’s research explores Big Data analytics, data mining, and data governance, with a focus on applications such as privacy enhancing technologies, social intelligence, and precision agriculture. She is interested in ethical and social implications of artificial intelligence and automated systems. Professor Dara has several projects in progress in the area of smart farming, food transparency, legal intelligence, and data governance using blockchain technology solutions. Her key research themes include:

  1. Data Governance. Research into data governance involves taking an interdisciplinary approach to enhance quality, security, accessibility, and usability of data and data management practices. 
  2. Data Analytics. This theme focuses on big/small data analytics using machine learning methods, such as deep learning and data mining. Projects are performed in collaboration with subject matter experts to facilitate more reliable decision making.
  3. Privacy Enhancing Solutions. This theme examines the applications of artificial intelligence to protect data. Projects are performed in collaboration with privacy practitioners and data owners/stewards.
  4. Data Traceability. This theme relates to all the above themes and focuses on artificial intelligence methods to enable automation end-to-end and enhance processes.


  • Member of the IEEE Global Initiative for Ethical Considerations in Artificial Intelligence and Autonomous Systems, 2016-present
  • Member of IEEE Blockchain Initiative, 2018-present
  • Certified Information Privacy Technologist, 2019
  • NSERC Discovery Grant for “Context­aware Software Defined Privacy in the Internet of Things,” 2018-2019
  • NSERC Collaborative Research and Development Grant for “Development of strategies for control of AIV transmission,” 2018-2019
  • OMAFRA New Directions Program for “A Comprehensive Analysis of Data Governance Practices and Policies in E-Agriculture Infrastructure,” 2019-2020

Media Coverage

Social Networks to Track Disease Outbreaks

Data Privacy

Artificial Intelligence

Data Analytics