Dr Mohammad Amirhosseini

NameDr Mohammad Amirhosseini
ORCIDhttps://orcid.org/0000-0002-3404-084X
Job titleAssociate Professor
Email addressm.h.amirhosseini@uel.ac.uk
Research instituteArchitecture, Computing & Engineering

Research outputs

Utilizing machine Learning Techniques to Predict State-of-Charge in Li-ion Batteries

Khatri, A., Lota, J., Nepal, P. and Amirhosseini, M. H. 2024. Utilizing machine Learning Techniques to Predict State-of-Charge in Li-ion Batteries. IS'24: 12th IEEE International Conference on Intelligent Systems. Varna, Bulgaria 29 - 31 Aug 2024 IEEE. https://doi.org/10.1109/IS61756.2024.10705192

AI-Enhanced Prediction of Multi Organ Failure in COVID-19 Patients

Rajakaruna, I., Amirhosseini, M. H., Li, Y. and Arachcillage, D. J. 2024. AI-Enhanced Prediction of Multi Organ Failure in COVID-19 Patients. IS'24: 12th IEEE International Conference on Intelligent Systems. Varna, Bulgaria 29 - 31 Aug 2024 IEEE. https://doi.org/10.1109/IS61756.2024.10705181

Prediction of Depression Severity and Personalised Risk Factors Using Machine Learning on Multimodal Data

Amirhosseini, M. H., Ayodele, A. L. and Karami, A. 2024. Prediction of Depression Severity and Personalised Risk Factors Using Machine Learning on Multimodal Data. IS'24: 12th IEEE International Conference on Intelligent Systems. Varna, Bulgaria 29 - 31 Aug 2024 IEEE. https://doi.org/10.1109/IS61756.2024.10705185

An AI Powered System to Detect Autism Spectrum Disorder in Toddlers

Amirhosseini, M. H., Alam, N., Kalabi, F. and Virdee, B. 2024. An AI Powered System to Detect Autism Spectrum Disorder in Toddlers. ICDAM-2024: 5th International Conference on Data Analytics and Management. London, UK 14 - 15 Jun 2024

Machine Learning in Lithium-Ion Battery: Applications, Challenges, and Future Trends

Valizadeh, A. and Amirhosseini, M. 2024. Machine Learning in Lithium-Ion Battery: Applications, Challenges, and Future Trends. SN Computer Science. 5 (Art. 717). https://doi.org/10.1007/s42979-024-03046-2

A Graph-Based Method for Identity Resolution to Assist Police Force Investigative Process

Amirhosseini, M., Kazemian, H. and Phillips, M. 2024. A Graph-Based Method for Identity Resolution to Assist Police Force Investigative Process. Journal of Cyber Security and Technology. In Press. https://doi.org/10.1080/23742917.2024.2354555

Predictive precision in battery recycling: unveiling lithium battery recycling potential through machine learning

Valizadeh, A., Amirhosseini, M. H. and Ghorbani, Y. 2024. Predictive precision in battery recycling: unveiling lithium battery recycling potential through machine learning. Computers and Chemical Engineering. 183 (Art. 108623). https://doi.org/10.1016/j.compchemeng.2024.108623

An artificial intelligence approach to predicting personality types in dogs

Amirhosseini, M. H., Yadav, V., Serpell, J. A., Pettigrew, P. and Kain, P. 2024. An artificial intelligence approach to predicting personality types in dogs. Scientific Reports. 14 (Art. 2404). https://doi.org/10.1038/s41598-024-52920-9

Forecasting Bitcoin Prices in the Context of the COVID-19 Pandemic Using Machine Learning Approaches

Sontakke, P., Jafari, F., Saeedi, M. and Amirhosseini, M. 2024. Forecasting Bitcoin Prices in the Context of the COVID-19 Pandemic Using Machine Learning Approaches. ICDAM-2023: 4th International Conference on Data Analytics & Management. London, UK 23 - 24 Jun 2023 Springer. https://doi.org/10.1007/978-981-99-6544-1_7

An AI powered system to enhance self-reflection practice in coaching

Jelodari, M., Amirhosseini, M. H. and Giraldez Hayes, A. 2023. An AI powered system to enhance self-reflection practice in coaching. Cognitive Computation and Systems. 5 (4), pp. 243-254. https://doi.org/10.1049/ccs2.12087

Sentiment-Driven Cryptocurrency Price Prediction: A Machine Learning Approach Utilizing Historical Data and Social Media Sentiment Analysis

Bhatt, S., Ghazanfar, M. and Amirhosseini, M. 2023. Sentiment-Driven Cryptocurrency Price Prediction: A Machine Learning Approach Utilizing Historical Data and Social Media Sentiment Analysis. Machine Learning and Applications: An International Journal (MLAIJ). 10 (2/3), pp. 1-15. https://doi.org/10.5121/mlaij.2023.10301

Machine Learning based Cryptocurrency Price Prediction using historical data and Social Media Sentiment

Bhatt, S., Ghazanfar, M. and Amirhosseini, M. 2023. Machine Learning based Cryptocurrency Price Prediction using historical data and Social Media Sentiment . 5th International Conference on Machine Learning & Applications (CMLA 2023). Sydney, Australia 17 - 18 Jun 2023 AIRCC Publishing Corporation.

A Machine Learning Approach to Identify the Preferred Representational System of a Person

Amirhosseini, M. and Wall, J. 2022. A Machine Learning Approach to Identify the Preferred Representational System of a Person. Multimodal Technologies and Interaction. 6 (12), p. 112. https://doi.org/10.3390/mti6120112

Application of Graph-Based Technique to Identity Resolution

Kazemian, H., Amirhosseini, M. H. and Phillips, M. 2022. Application of Graph-Based Technique to Identity Resolution. AIAI 2022: 18th International Conference on Artificial Intelligence Applications and Innovations. Crete, Greece 17 - 20 Jun 2022 Springer. https://doi.org/10.1007/978-3-031-08333-4_38

A Rule and Graph-Based Approach for Targeted Identity Resolution on Policing Data

Phillips, M., Amirhosseini, M. and Kazemian, H. 2020. A Rule and Graph-Based Approach for Targeted Identity Resolution on Policing Data. 2020 IEEE Symposium Series on Computational Intelligence. Online 01 - 04 Dec 2020 IEEE. https://doi.org/10.1109/SSCI47803.2020.9308182

Machine Learning Approach to Personality Type Prediction Based on the Myers–Briggs Type Indicator®

Amirhosseini, M.H. and Kazemian, H. 2020. Machine Learning Approach to Personality Type Prediction Based on the Myers–Briggs Type Indicator®. Multimodal Technologies and Interaction. 4 (Art. 9). https://doi.org/10.3390/mti4010009

Automating the process of identifying the preferred representational system in Neuro Linguistic Programming using Natural Language Processing

Amirhosseini, M.H. and Kazemian, H. 2019. Automating the process of identifying the preferred representational system in Neuro Linguistic Programming using Natural Language Processing. Cognitive Processing. 20 (2), p. 175–193. https://doi.org/10.1007/s10339-019-00912-3

Natural Language Processing approach to NLP Meta model automation

Amirhosseini, M.H., Kazemian, H., Ouazzane, K. and Chandler, C. 2018. Natural Language Processing approach to NLP Meta model automation. 2018 International Joint Conference on Neural Networks (IJCNN). Rio de Janeiro, Brazil 08 - 13 Jul 2018 IEEE. https://doi.org/10.1109/IJCNN.2018.8489609
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