Malik Awais Khan

Project Title

This PhD research project aims to create a multi-modal interface for age assurance in mixed reality environments for online child safety. The solution will incorporate machine learning, computer vision, NLP, and biometric analysis to analyse physical attributes, contextual information, and biometric data of the user for accurate age verification while preserving privacy. The project has significant potential to improve online child safety by providing a reliable and precise means of age verification, ensuring that children are not exposed to inappropriate content or interactions with online predators. The project will also develop the candidate’s skills in digital platform technologies such as HCI and AI, data curation, and privacy-preserving algorithms. Overall, the project aims to make a notable contribution to the field of online child safety through the creation of an innovative age assurance solution.

Supervision Team

This PhD research project aims to create a multi-modal interface for age assurance in mixed reality environments for online child safety. The solution will incorporate machine learning, computer vision, NLP, and biometric analysis to analyse physical attributes, contextual information, and biometric data of the user for accurate age verification while preserving privacy. The project has significant potential to improve online child safety by providing a reliable and precise means of age verification, ensuring that children are not exposed to inappropriate content or interactions with online predators. The project will also develop the candidate’s skills in digital platform technologies such as HCI and AI, data curation, and privacy-preserving algorithms. Overall, the project aims to make a notable contribution to the field of online child safety through the creation of an innovative age assurance solution.

Description

This PhD research project aims to create a multi-modal interface for age assurance in mixed reality environments for online child safety. The solution will incorporate machine learning, computer vision, NLP, and biometric analysis to analyse physical attributes, contextual information, and biometric data of the user for accurate age verification while preserving privacy. The project has significant potential to improve online child safety by providing a reliable and precise means of age verification, ensuring that children are not exposed to inappropriate content or interactions with online predators. The project will also develop the candidate’s skills in digital platform technologies such as HCI and AI, data curation, and privacy-preserving algorithms. Overall, the project aims to make a notable contribution to the field of online child safety through the creation of an innovative age assurance solution.