The AI in Education Group

The AI in Education Group is at the forefront of integrating Artificial Intelligence (AI) into educational settings, focusing on the development and application of AI technologies to enhance teaching and learning experiences.

Our group is dedicated to exploring theoretical and practical aspects of AI in education, including machine learning, natural language processing, AI-generated content, and intelligent tutoring systems.

Our Mission 

We aim to foster innovation in education through AI technologies. By developing workshops both within and outside the University, we seek to enlighten educators and students about the advancements in AI and their potential applications in educational contexts. Our activities underscore the importance of ethical considerations, safety, and the responsible use of AI in education. 

Collaboration and Impact 

We actively engage in collaborations with industry and academic partners to ensure our research and projects remain relevant and impactful. Our initiatives are designed to demonstrate practical use cases of AI in education, ranging from AI-generated videos that address unconscious bias and Equity, Diversity, and Inclusion (EDI) issues, to AI-powered tools for student assessment and feedback. 

Key areas of focus

  • AI-Generated Educational Content: Creating immersive learning materials using AI, such as videos, music, and images, to enhance lecture delivery and student engagement. 
  • AI in Assessment: Leveraging AI for generating feedback on student assessments, providing personalised and timely insights to learners. 
  • Safe Integration of AI Technologies: Implementing OpenAI's local models into Virtual Learning Environments (VLEs) safely, ensuring data protection and privacy. 
  • Interactive AI Tools for Education: Developing user interfaces for chatbots and other AI models to facilitate interactive learning experiences. 

Projects and innovations

Our group runs projects that showcase the application of AI in education. Examples include: 

  • Unconscious Bias Education: Utilising AI-generated videos to teach about unconscious bias and promote EDI within educational contexts. 
  • Feedback Generation: Developing AI-powered systems for generating constructive feedback on student assessments, aiming to enhance formative learning processes. 
  • Enhancing Lectures: Integrating AI-generated music and images into lectures to create more engaging and stimulating learning environments. 
  • Chatbot Interfaces: Designing user-friendly interfaces for educational chatbots, making AI more accessible to educators and students. 

Dr Firat Bitmaz (Group Leader)

Research interests:

Technology enhanced teaching and learning; Database systems; Educational Data Mining (EDM); Transformers; Human-Computer Interaction (HCI); Case-Based Reasoning (CBR)

Dr Parisa Derakhshan (AI in Health Lead)

Research interests:

Graph theory; Interconnection network topologies; Combinatorics; Computer Graphics

Dr Hui Fang

Research interests

Applying visual computing and AI technologies for: digital healthcare, precision agriculture, business intelligence, environment change monitoring, and contemporary transportation systems

Professor Baihua Li

Research interests:

Artificial Intelligence; Computer vision and pattern recognition; Machine learning and deep learning; Image and signal processing; Human-computer interaction; Computer graphics, virtual reality and visualisation technology

Dr Hossein Nevisi (AI in Career Lead)

Research interests:

Generative AI and Large Language Models; Data Visualisation/Analysis; Open and Big Data Applications; Web/Mobile/Software Development

Dr Mohamad Saada (Embodied AI Lead)

Research interests:

Deep learning (DNNs, CNNs, GANs); Computer vision; Human computer/robot interaction; Probabilistic modelling (Bayesian Networks, Dynamic Bayesian Networks, Hidden Markov Models, Kalman filters, Graphical Models); Human activity recognition; Anomaly detection; Multi-object tracking

Dr Sara Saravi (AI in EDI Lead)

Research interests:

Image/Video processing; Computer vision; Machine learning; Data analytics, Big Data and Data visualisation

Dr Yanning Yang (AI in Team Work Lead)

Research interest:

Pedagogy to enhance learning; Wireless sensor networks; Computer networking; Mobile Peer-to-Peer Networks