Dr Massoud Khodadadzadeh
Lecturer in Computer Science
Dr Massoud Khodadadzadeh, a Lecturer in Computer Science at the University of Bedfordshire, holds a PhD in Computer Science from Ulster University. His research journey includes impactful roles such as a Research Associate in Artificial Intelligence for Data Science at The Bath Institute for the Augmented Human, University of Bath, and previously at the Intelligent Systems Research Centre, Ulster University.
With international collaborations, he has contributed to pioneering projects, including a visiting researcher position at the Centre for Complex Systems and Brain Sciences, Florida Atlantic University. His work encompasses cutting-edge developments in machine learning and deep learning methods for various applications, such as Remote Sensing, Brain-Computer Interface, advanced techniques for Inner Speech Classification, and identifying emergent agency in infants.
Teaching Expertise/Areas
- Concepts and technologies of Artificial Intelligence (AI)
- Intelligent systems and data mining
- Data Science
- Decision support systems
- Computer Vision
Research Interests/Areas
- Artificial Intelligence (AI)
- Machine Learning
- Deep Learning
- Robotics
- Remote Sensing
- Brain-Computer Interface (BCI)
MSc/PhD Opportunities
Khodadadzadeh welcomes inquiries from exceptional candidates interested in pursuing MSc or PhD research in areas related to the topics outlined above. For more information, please feel free to email him at Massoud.Khodadadzadeh@beds.ac.uk.
Additional details are available at the provided links:
Professional Activities
- Member of the IRAC: Institute for Research in Applicable Computing
- Course coordinator for MSc in Artificial Intelligence (AI)
- Link co-ordinator Majan University College (MUC), Oman
- Reviewer of IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
- External Reviewer of Mitacs Accelerate research proposals
Publications
- Sloan, A. T., Jones, N. A., Boiten, N., Friston, K., Khodadadzadeh, M., Coyle, D., Gudibanda, K., Jirsa, V., & Kelso, J. A. S. (2023). “Coordination Dynamics meets Active Inference and Artificial Intelligence (CD + AI2): A multi-pronged approach to understanding the dynamics of brain and the emergence of conscious agency”. Society for Neuroscience (SfN), https://doi.org/10.1016/j.tics.2016.04.004
- Khodadadzadeh, M., Sloan, A. T., Jones, N. A., Coyle, D., & Kelso, J. A. S. (2023). 2D Capsule Networks Detect Perceived Changes in Infant∼Environment Relationship Reflected in 3D Movement Dynamics. Scientific Reports, Nature, https://doi.org//10.21203/rs.3.rs-3088795/v1
- M. Khodadadzadeh, N. deBois, and D. Coyle, “Knowledge Extraction using Capsule Deep Learning Approaches.” UK AI Fellows Conference. Accessed: May. 24, 2023.
- M. Khodadadzadeh and D. Coyle, “Imagined Speech Classification from Electroencephalography with a Features-Guided Capsule Neural Network.” 15th Irish Human Computer Interaction (iHCI) Symposium, Dec. 18, 2022. Accessed: Feb. 26, 2023.
- M. Khodadadzadeh, X. Ding, P. Chaurasia, and D. Coyle, “A Hybrid Capsule Network for Hyperspectral Image Classification,” IEEE J Sel Top Appl Earth Obs Remote Sens, vol. 14, pp. 11824–11839, 2021.
- Korik A, McCreadie K, McShane N, Du Bois N, Khodadadzadeh M, Stow J, et al., “Competing at the Cybathlon championship for people with disabilities: long-term motor imagery brain–computer interface training of a cybathlete who has tetraplegia,” J Neuroeng Rehabil, vol. 19, no. 1, pp. 1–22, Dec. 2022.
- M. Khodadadzadeh, X. Ding, P. Chaurasia, and D. Coyle, “Data Analysis with Capsule Deep Learning Approaches,”Intelligent Systems Research Centre, Faculty of Computing, Engineering and Built Environment, Ulster University, Confirmation report, 2019.
- M. Khodadadzadeh, X. Ding, P. Chaurasia, and D. Coyle, “Intelligent Data Analysis with Capsule Neural Networks,”Intelligent Systems Research Centre, Faculty of Computing, Engineering and Built Environment, Ulster University, Initial assessment report, 2018.
- M. Khodadadzadeh and H. Gholizadeh-Narm, “Improvement of chaotic secure communication scheme based on steganographic method and multimodal dynamic maps,” International Journal of Systems, Control and Communications, vol. 6, no. 4, pp. 305–320, 2015.
Contact Details
telephone
University switchboard
During office hours
(Monday-Friday 08:30-17:00)
+44 (0)1234 400 400
Outside office hours
(Campus Watch)
+44 (0)1582 74 39 89
Admissions
admission@beds.ac.uk
International office
international@beds.ac.uk
Student support
sid@beds.ac.uk
Registration
sid@beds.ac.uk