Dr. Rozita Dara
Research Overview
Dr. Rozita Dara’s research applies artificial intelligence and data governance to advance sustainable, safe, and transparent agri-food systems. Her work focuses on using AI for food safety monitoring, disease modeling and outbreak prediction (such as avian influenza), smart farming, and decision support systems that improve agricultural operations, including greenhouse management.
A central theme of her research is the development of ethical, privacy-preserving, and user-centered AI solutions. She leads interdisciplinary efforts on agri-food data strategy, interoperability, and AI sovereignty, ensuring that agricultural data is trusted, protected, and responsibly used. Her work bridges AI innovation with policy, governance, and real-world deployment to benefit farmers, consumers, and the environment.
Research Keywords
Artificial intelligence in agriculture | Food safety and disease modeling | Smart farming systems | Decision support systems | Agri-food data governance | Privacy-preserving AI | Ethical and trustworthy AI | Food traceability and transparency | IoT data management | AI sovereignty
Dr. Dara's Projects
Data Governance
This theme focuses on improving the quality, security, interoperability, usability, and trustworthy use of agri-food data through AI. Current projects include smart farms, blockchain in agri-food, and agriculture open data.
Data Analytics
This theme applies machine learning and data mining to support reliable, data-driven, and trustworthy decision-making in agri-food systems. Projects include computer vision for agriculture applications (e.g., mushroom harvesting), text analysis of legal intelligence, food intelligence documents, and decision support systems for avian influenza modeling and swine genetics.
Privacy-Enhancing Solutions
This theme develops AI-driven methods to protect sensitive agri-food data while maintaining usability, access, and trustworthiness. Current work includes blockchain and usable privacy policies for agri-food data, focusing on adaptive access control and privacy-preserving data management across farming and supply chain systems.
Data Traceability
This theme uses AI and blockchain to enable end-to-end traceability across agri-food systems, ensuring transparency, accountability, and trust. Projects include food supply chain traceability and IoT data traceability, supporting automation and reliable tracking across the value chain.
