
Dr Mohammad Amirhosseini
Senior Lecturer
Department of Engineering & Computing , School of Architecture, Computing and Engineering
Dr Amirhosseini is the course leader of BSc and MSc Digital and Technology Solutions Apprenticeship courses. He has contributed to national and international granted research projects, and has published papers in different international refereed journals and conferences. He has also been the main organiser and chair of different special sessions in renowned international conferences, guest editor of special issues in international refereed journals, and the reviewer for different journals, conferences and grant competitions. Dr Amirhosseini is the winner of the School Staff Award for 'Innovative Teaching' and 'Leadership through Change'.
Areas Of Interest
Dr Amirhosseini's research interests and expertise include, but are not limited to, applications of AI and Machine Learning in different areas such as:
- Psychology
- Cognitive processing
- Personal development
- Mental health
- Depression and anxiety detection
- ADHD and Autism diagnosis
- Coaching and therapy
- Personality type prediction
- Human-computer interaction
- Natural language processing
- Animals' behaviour and personality
- Organisational performance
- Cyber security
- Identity resolution
- Fraud detection
- Finance
- Price Prediction
- Social media analysis
- Hate speech detection and prevention
- Racism and sexism detection and prevention
- Politics and international relations
OVERVIEW
Dr Amirhosseini joined UEL in April 2020 and is currently the course leader of BSc and MSc Digital and Technology Solutions Apprenticeship courses. Prior to UEL, he was a Postdoctoral Research Fellow at London Metropolitan University, contributing to the SPIRIT (Scalable Privacy Preserving Intelligence Analysis for Resolving Identities) project European Horizon 2020 consisting of a consortium of 17 partners from 9 different European countries.
He has been involved in teaching in higher education for 8 years, lecturing in a variety of modules in computer science for some of which he was appointed as the module leader. During his time at University of East London, he has been contributing to design, delivery, assessment, and leadership of a variety of modules at both undergraduate and postgraduate levels. Furthermore, he was the academic Year Tutor for all BSc final year students in the department of Computer Science and Digital technologies. In 2022, he was honoured as the receiver of the School Staff Award for 'Innovative Teaching'. He also received the School Staff Award for 'Leadership through Change' in 2023.
In January 2021, he was successful in being awarded a grant in the Innovative UK Smart Grants competition. The title of his project was "Automation of Neuro-Linguistic Programming methods using Artificial Intelligence to interpret unconscious thoughts and values for personal development". This project was granted £118,618, and built on the latest R&D in AI, neuroscience, and personal development, including three bespoke AI models developed by himself. He has also been collaborating with international industrial partners as a senior consultant and recently started a consultancy project with a startup company in Florida, USA. This project focuses on using Artificial Intelligence to predict behavioural characteristics of dogs and developing a dog personality assessment tool to facilitate their adoption. Moreover, he has published in different peer-reviewed journals and conferences, as well as contributing to renowned international conferences as a special session main organiser, and international refereed journals as a guest editor.
Dr Amirhosseini graduated with a BSc in Software Engineering, before achieving his MSc in Information Technology from Coventry University. He then completed his PhD in Computing and Artificial Intelligence at London Metropolitan University.
FUNDING
Dr Amirhosseini was successful in the Innovate UK Smart Grants, January 2021 competition. The amount of funding which was granted to his innovative industrial project was £118,618.
The title of his project was "Automation of Neuro-Linguistic Programming methods using Artificial Intelligence to interpret unconscious thoughts and values for personal development." This project was a collaboration between University of East London and Whyness company, and Dr Amirhosseini was working with them as their academic partner.
This project was motivated by the opportunity for emerging technology to unlock new levels of workplace fulfilment and human potential, expanding specialist services limited to (and by) physical human interactions.
The pioneering AI-driven platform developed in this project will disrupt the way personal development is provided to individuals, unlocking benefits of proven neuroscientific practices to a wider audience. Employers will be able to provide reliable, affordable, personalised behavioural development tools to employees at different stages of their careers.
The innovation in this project involved developing and integrating multiple AI models to intelligently identify personal values and purpose. The project aimed to digitise Neuro-Linguistic-Programming (NLP) methods to help users become more self-aware by interpreting unconscious thoughts and behaviours.
This project was built on the latest research and development in AI, neuroscience, and personal development, including two bespoke AI models developed by Dr Amirhosseini, that automate some core NLP methods.
The collaborative project team had a unique blend of diverse expertise across academia, industry, business and technology. By digitising proven neuroscientific practices and behavioural development tools that harness personal motivations and self-awareness, human consciousness, performance and potential will be elevated.
Following this successful Innovate UK funded project, he brought another research fund to the University from a consultancy project that he started with Dogvatar company in Florida, USA. This project focuses on using Artificial Intelligence to predict behavioural characteristics of dogs and developing a dog personality assessment tool to facilitate their adoption.
CURRENT RESEARCH
Dr Amirhosseini's research interests and expertise include, but are not limited to, applications of AI and Machine Learning in different areas such as Psychology, Cognitive processing, Personal development, Mental health, Depression and anxiety detection, ADHD and Autism diagnosis, Coaching and therapy, Personality type prediction, Human-computer interaction, Natural language processing, Animals' behaviour and personality, Organisational performance, Cyber security, Identity resolution, Fraud detection, Finance, Price Prediction, Social media analysis, Hate speech detection and prevention, Racism and sexism detection and prevention, Politics and international relations.
The title of Dr Amirhosseini's PhD thesis was "Neuro Linguistic Programming Automation for Improvement of Organisational Performance." Neuro Linguistic Programming (NLP) is a methodology used for recognition of human behavioural patterns and the modification of the behaviour. Natural Language Processing and machine learning techniques were used for the automation process and an intelligent software was developed. The novel methodology used for this automation was able to eliminate human errors, thereby the software was able to perform with a higher level accuracy, reliability and efficiency.
Dr Amirhosseini contributed to the SPIRIT project as a postdoctoral research fellow, following his PhD. This project was a five million Euro EU Horizon 2020 project consisting of a consortium of 17 partners from 9 different European countries including Germany, Italy, Sweden, Spain, Greece, Belgium, Poland, Serbia, and the United Kingdom. The aim of this project was to help law enforcement agencies identify cybercriminals by developing sophisticated artificial intelligence-based (AI) tools that analyse millions of pieces of data from a wide range of sources. The SPIRIT technical team used a novel approach in the development, testing, training and evaluation of a new scalable privacy preserving intelligence analysis for resolving identities system prototype, and Dr Amirhosseini was one of the main researchers on the team who contributed to developing research methodologies for identity resolution on policing datasets and extracted data from web crawlers and social media, as well as application of Natural Language Programming (NLP). Some of the end users in this project included West Midlands Regional Police (UK), Thames Valley Police (UK), Hellenic Police (Greece), Police Academy in Szczytno (Poland), Ministry of Interior (Serbia).
Dr Amirhosseini was successful in being awarded a grant in the Innovative UK Smart Grants competition. The title of his project was "Automation of Neuro-Linguistic Programming methods using Artificial Intelligence to interpret unconscious thoughts and values for personal development". This project was built on the latest R&D in AI, neuroscience, and personal development, including three bespoke AI models which he has developed. (More details available in the 'Funding' section on this page) More recently, he started a consultancy project with a startup company in Florida, USA. This project focuses on using Artificial Intelligence to predict behavioural characteristics of dogs and developing a dog personality assessment tool to facilitate their adoption.
Moreover, he has published in different peer reviewed journals and conferences. He was the main organiser and chair of a special session on "Machine Learning Applications in Cyber Security" at the 2020 IEEE World Congress on Computational Intelligence, and the 2020 IEEE Symposium Series on Computational Intelligence. He organised a special session on "Machine Learning Applications in Psychology" for the 2022 IEEE World Congress on Computational Intelligence. Additionally, as a guest editor, he organised a special issue with the same title, for the Cognitive Computation and Systems Journal. He also organised two other special issues on "Applications of Recommender Systems in healthcare", and "Applications of Artificial Intelligence in Psychology" for the Electronics Journal.
Furthermore, he has been a reviewer for journals and conferences including 'Cognitive Processing', 'Cognitive Computation and Systems', 'Human-centric Intelligent Systems', 'Multimedia Technologies and Interaction', 'Applied Sciences', 'Mathematics', 'Digital Scholarship in the Humanities', 'Informatics', 'Sensors', 'Modelling', IEEE World Congress on Computational Intelligence (WCCI), IEEE International Joint Conference on Neural Networks (IJCNN), and IEEE Symposium Series on Computational Intelligence (SSCI). He was also a reviewer for Artificial Intelligence Health & Care Award Competition 3, run by the Accelerated Access Collaborative (AAC) in partnership with NHSX and the National Institute for Health Research (NIHR). Dr Amirhosseini has one PhD completion and has supervisory roles for four other PhD and Professional Doctorate students.
PUBLICATIONS
Paper publications in international refereed journals and conferences
- Amirhosseini, M.H., Yadav, V., James, A.S., Pettigrew, P., and Kian, P. (2023) 'An Artificial Intelligence Approach to Predicting Personality Types in Dogs', Nature Scientific Reports (Manuscript Submitted)
- Amirhosseini, M.H., Kazemian, H., Phillips, M. (2023) 'A Graph-Based Method for Identity Resolution to Assist Police Force Investigative Processes', Human-Centric Intelligent Systems, (Manuscript Submitted)
- Valizadeh, A., Amirhosseini, M.H., Ghorbani, Y. (2023) ‘Predictive Precision in Battery Recycling: Unveiling Lithium Battery Recycling Potential through Machine Learning’, Computers and Chemical Engineering, (Manuscript Submitted)
- Jelodari, M., Amirhosseini, M.H., and Giraldez-Hayes, A. (2023) 'An AI Powered System to Enhance Self-Reflection Practice in Coaching', IET Cognitive Computation and Systems, (Manuscript Accepted)
- Bhatt, S., Ghazanfar, M.A., Amirhosseini, M.H. (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), Vol 10. DOI:10.5121/mlaij.2023.10301 DOI:10.5121/mlaij.2023.10301
- Sontakke, P., Jafari, F., Saeedi, M., Amirhosseini, M.H. (2023) Forecasting Bitcoin Prices in the Context of the COVID-19 Pandemic Using Machine Learning Approaches, 4th International Conference on Data Analytics & Management (ICDAM-2023), London, UK.
- Bhatt, S., Ghazanfar, M.A., Amirhosseini, M.H. (2023) Machine Learning based Cryptocurrency Price Prediction using historical data and Social Media Sentiment, 5th International Conference on Machine Learning & Applications, Sydney, Australia.
- Amirhosseini, M.H. 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. DOI: 10.3390/mti6120112
- Kazemian, H., Amirhosseini, M.H., and Phillips, M. (2022) 'Application of Graph-Based Technique to Identity Resolution', 18th International Conference on Artificial Intelligence Applications and Innovations, Crete, Greece.
- Phillips, M., Amirhosseini, M.H., and Kazemian, H. (2020) 'A Rule and Graph-Based Approach for Targeted Identity Resolution on Policing Data', IEEE Symposium Series on Computational Intelligence, IEEE Symposium on Computational Intelligence in Data Mining, Canberra, Australia.
- Amirhosseini, M.H. and Kazemian, H. (2020) 'Machine Learning Approach to Personality Type Prediction Based on the Myers–Briggs Type Indicator®️', Multimodal Technologies Interaction, Vol 4(1). DOI: 10.3390/mti4010009
- 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 Journal, Vol 20(2), pp. 175-193. DOI: 10.1007/s10339-019-00912-3
- Amirhosseini, M.H., Kazemian, H., Ouazanne, K. and Chandler, C. (2018) 'Natural Language Processing approach to NLP Meta model automation', IEEE World Congress on Computational Intelligence, International Joint Conference on Neural Networks, Rio de Janeiro, Brazil. DOI: 10.1109/IJCNN.2018.8489609
International journal and conference participation
- Technical Chair for the 5th International Conference on Data Analytics and Management (ICDAM 2023), from 23-24 June 2023, London, United Kingdom.
- Associate editor for Special Issue on "Machine Learning Applications in Psychology" at IET Cognitive Computation and Systems Journal.
- Lead Guest Editor for Special Issue on "Applications of Artificial Intelligence in Psychology" at "Electronics" Journal.
- Guest Editor for Special Issue on "Application of Recommended Systems in Healthcare" at "Electronics" Journal.
- Main organiser and chair of a special session on "Machine Learning Applications in Psychology" at the International Joint Conference on Neural Networks (IJCNN 2022), one of the main three conferences in the IEEE World Congress on Computational Intelligence (WCCI 2022), from 18-23 July 2022, Padua, Italy.
- Main organiser and chair of a special session on "Machine Learning Applications in Cyber Security" at the International Joint Conference on Neural Networks (IJCNN 2020), one of the main three conferences in the IEEE World Congress on Computational Intelligence (WCCI 2020), from 19-24 July 2020, Glasgow, Scotland.
- Main organiser and chair of a symposium on "Machine Learning Applications in Cyber Security" at the IEEE Symposium Series on Computational Intelligence (SSCI 2020), from 1-4 December 2020, Canberra, Australia.
- Reviewer for international refereed Journals including 'Applied Sciences', 'Cognitive Processing', 'Multimedia Technologies and Interaction', 'Mathematics', 'Digital Scholarship in the Humanities', 'Cognitive Computation and Systems', 'Informatics', 'Sensors', and Modelling'.
- Reviewer for international refereed conferences including IEEE World Congress on Computational Intelligence (WCCI), IEEE International Joint Conference on Neural Networks (IJCNN), and IEEE Symposium Series on Computational Intelligence (SSCI).
- Reviewer for Artificial Intelligence Health & Care Award Competition 3, run by the Accelerated Access Collaborative (AAC) in partnership with NHSX and the National Institute for Health Research (NIHR).
TEACHING
Dr Amirhosseini is the course leader of BSc and MSc Digital and Technology Solutions Apprenticeship courses. Before taking this role, he was the Academic Year Tutor for level 6 (BSc final year) students in the department. He is also contributing to the UEL overseas collaboration and partnership portfolio as an academic link tutor for UEL international partners. He is currently the academic link tutor for 6 different computing courses at Ain Shams University in Egypt.
Dr Amirhosseini also supervises a significant number of MSc and BSc final projects. In 2022, he was honoured as the receiver of the School Staff Award for 'Innovative Teaching'. He also received the School Staff Award for 'Leadership through Change' in 2023.
Academic year 2023/2024
2023/24 Teaching (Fall semester):
- Module Leader of Cyber Security (Level 5 - Second year of BSc course))
2023/24 Teaching (Spring semester):
- Module Leader of Artificial Intelligence (Level 5 - Second year of BSc course)
Academic year 2022/2023
2022/23 Teaching (Fall semester):
- Module Leader of Cyber Security (Level 5 - Second year of BSc course)
- Module Leader of Professional Practice 1 (Level 4 - First year of BSc Apprenticeship course)
- Artificial Intelligence (Level 6 - Third year of BSc course)
2022/23 Teaching (Spring semester):
- Module Leader of Business Intelligence Analysis (Level 6 - Third year of BSc course)
Academic year 2021/2022
2021/22 Teaching (Fall semester):
- Module Leader of Cyber Security (Level 5 - Second year of BSc course)
- Artificial Intelligence (Level 6 - Third year of BSc course)
- Advanced Software Engineering (Level 7 - MSc course)
2021/22 Teaching (Spring semester):
- Module Leader of Business Intelligence Analysis (Level 5 - Second year of BSc course)
- Web Technologies (Level 4 - First year of BSc course)
Academic year 2020/2021
2020/21 Teaching (Fall semester):
- Artificial Intelligence (Level 6 - Third year of BSc course)
- Cyber Security (Level 5 - Second year of BSc course)
- Advanced Software Engineering (Level 7 - MSc course)
- Information Systems Modelling & Design (Level 4 - First year of BSc course)
- IT Project Management (Level 6 - Third year of BSc course)
- Project Management (Level 6 - Third year of BSc course)
2020/21 Teaching (Spring semester):
- Artificial Intelligence and Machine Vision (Level 7 - MSc course)
- Business Intelligence Analysis (Level 6 - Third year of BSc course)
- Web Technologies (Level 4 - First year of BSc course)
- IT Project Management (Level 6 - Third year of BSc course)
- Mental Wealth; Professional Life 2 (Computing Practice) (Level 5 - Second year of BSc course)
2020/21 Teaching (Summer semester):
- Module Leader of Cyber Security Module (Level 5 - Second year of BSc course)