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
REYN 3311
Seeking academic or industry partnerships in the area(s) of: 
Disease modeling, social media analytics, information privacy, supply chain resilience, and applied machine learning in agriculture.
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. Professor Dara obtained her PhD from the System Design Engineering, University of Waterloo.

Research Themes

Professor Dara’s research explores applied machine learning and data governance, with a focus on applications such as privacy enhancing technologies, precision agriculture, and food supply chain. 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 disease modeling, legal intelligence, and food transparency 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. Supply Chain Resilience. This theme relates to use of artificial intelligence methods and data governance best practices and standards to enable automation end-to-end and enhance supply chain processes, and resilience.


  • Chair, IEEE Society on Social Implication of Technology, 2015-present.
  • Lead, Strategy Team on Ontario Beef and Dairy Data Platform
  • Co-Lead, Food product ID verification and governance standard
  • Member, Canola Blockchain Standardization, SCC Data Governance, SCC Data Security and Privacy, SCC Blockchain Standardization, IEEE Blockchain, IEEE ethical and responsible artificial intelligence.
  • Certified Information Privacy Technologist, 2019.
  • Received funding from NSERC Discovery, OMAFRA New Directions, NSERC Collaborative Research and Development, OMAFRA Alliance Tier I, MITACS and private sector.

Media Coverage

Disease Outbreaks

Data Privacy

Artificial Intelligence

Data Analytics