Dr Mohammad Hossein Amirhosseini

Dr Mohammad H Amirhosseini

Senior Lecturer

Department of Engineering & Computing , School Of Architecture, Computing And Engineering

Dr Mohammad Hossein Amirhosseini is currently a Senior Lecturer in Computer Science and Digital Technologies at University of East London and a Fellow of the Higher Education Academy (FHEA). He is the Apprenticeship Lead in the School of Architecture, Computing and Engineering, and 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 renown journals and international conferences. He has been the main organiser and chair of different special sessions at international conferences, guest editor of special issues in international refereed journals, and the reviewer for different journals, conferences, and grant competitions.

Dr Amirhosseini has been collaborating with different national and international industrial partners as an academic partner or a senior consultant and has been invited by different Universities and events as a guest speaker to talk about different aspects of Artificial Intelligence and its applications.

Dr Amirhosseini is the winner of the Staff Award for 'Innovative Teaching' in 2022 and for 'Leadership through Change' in 2023. Additionally, the University of East London achieved the prestigious 2024 AAC National Apprenticeship High Commendation Award for ‘Digital Apprenticeship Provider of the Year’ because of the Digital and Technology Solutions Apprenticeship course led by Dr Amirhosseini.
 

Areas Of Interest

Dr Amirhosseini's research interests and expertise include 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
Dr Mohammad Hossein Amirhosseini

OVERVIEW

Dr Amirhosseini completed his PhD in Computing at London Metropolitan University, where he subsequently served as a Research Fellow, contributing to the SPIRIT (Scalable Privacy Preserving Intelligence Analysis for Resolving Identities) project European Horizon 2020, which was granted a €5 million fund by the European Union, and had a consortium of 17 partners from 9 European countries.

In April 2020, he moved to the University of East London, starting as a lecturer, and progressing to Senior Lecturer in Computer Science and Digital Technologies, while also achieving the status of Fellow of the Higher Education Academy (FHEA).

In his current roles, he has been the apprenticeship lead in the School of Architecture, Computing, and Engineering, and the Course leader of BSc and MSc Digital and Technology Solutions Apprenticeship courses. He has also been the Module leader for a variety of modules at different levels and have supervised a significant number of MSc and BSc dissertations. Moreover, he has been the lead supervisor for different PhD and Professional Doctorate researchers, celebrating his first PhD completion in November 2023. His contributions extend to university-wide commitments, including School representative in the Education and Experience Committee, and in the University Apprenticeship Compliance Committee. Furthermore, he was the Year Tutor for all BSc final year students in the department of Computer Science and Digital Technologies, and the Academic Link Tutor for 6 Dual Degree Computing courses at Ain Shams University in Egypt, where he collaborated closely with their head of department, course leaders, module leaders and external examiners to ensure a smooth and high quality course delivery and to conduct a proper assessment moderation for all the modules in these courses.

He has established national and international collaborations with esteemed institutions such as University of Pennsylvania, Imperial College London, University of Lincoln, London Metropolitan University, and Adelphi University. These partnerships have yielded impactful publications in prestigious Q1 journals such as Nature Scientific Reports, and renowned conferences such as the IEEE World Congress on Computational Intelligence.

He has also been collaborating with different national and international industrial partners such as Whyness Ltd. (UK), Nex Power Ltd. (UK), Solve Energy Service Ltd. (UK), Keptika Ltd. (UK), Accenture (UK), Uptime Labs Ltd. (UK), and Dogvatar Ltd. (US). His collaboration with these industrial partners led to successful grant applications such as the Innovate UK Smart Grant (value: £118,618), and high-quality publications in Q1 and Q2 Journals and renowned conferences, as well as developing commercial products.

His research has attracted international attention, leading to interviews with major media outlets such as CBS News, Fox TV and German Public Radio, and contributions to public knowledge through national and international newsletters, magazines, and online sources such as The Telegraph (UK), Science Magazine (UK), Mirage News (Australia), Study Finds (US), EurekAlert! (US), SciTechDaily (US), Police Magazine (US), BNN (China), Ladepeche (France), Liberated Digital (Spain), ADP Live (India), Med India (India), Power Info Today Magazine (India) and La Stampa (Italy).

He has also been invited by different Universities and events as a guest speaker to talk about different aspects of Artificial Intelligence and its applications. Examples include the 2024 Big Data & AI World London Conference at ExCeL London, 2022 International IORMA Webinar, and Global Leaders Program at Coventry University.
Dr Amirhosseini is the winner of the Staff Award for 'Innovative Teaching' in 2022 and for 'Leadership through Change' in 2023. Additionally, University of East London achieved the prestigious 2024 AAC National Apprenticeship High Commendation Award for ‘Digital Apprenticeship Provider of the Year’ because of the Digital and Technology Solutions Apprenticeship course led by Dr Amirhosseini.

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 the 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 the 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 the 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, Healthcare, Cognitive Processing, Personal Development, Mental Health, Coaching, Neuro Linguistic Programming, Personality Type Prediction, Depression and Anxiety Detection, Human-Computer Interaction, Natural Language Processing, Animals’ Behaviour and Personality, Organisational Performance, Energy Recycling, Finance, Cyber Security, Identity Resolution, Fraud Detection, Social Media Analysis, Sentiment 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).

After joining University of East London, he has established national and international collaborations with esteemed institutions such as University of Pennsylvania, Imperial College London, University of Lincoln, London Metropolitan University, and Adelphi University. These partnerships have yielded impactful publications in prestigious Q1 journals such as Nature Scientific Reports, and renowned conferences such as the IEEE World Congress on Computational Intelligence.

He has also been collaborating with different national and international industrial partners as an academic partner od senior consultant. Companies include Whyness Ltd. (UK), Nex Power Ltd. (UK), Solve Energy Service Ltd. (UK), Keptika Ltd. (UK), Accenture (UK), and Uptime Labs Ltd. (UK), Dogvatar Ltd. (US). His collaboration with these industrial partners led to submitting different Innovate UK grant applications, and high-quality publications in Q1 and Q2 Journals and renowned conferences, as well as developing commercial products.

In a collaboration with Whyness Ltd., 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) 

After this project, he started a collaborative project with Dogvatar Ltd. in Florida, USA, and University of Pennsylvania, where he served as a senior consultant. This project was focused on using Artificial Intelligence to predict behavioural characteristics of dogs and developing a dog personality assessment tool to facilitate their adoption and to improve the training success rate for working dogs. The outcomes of this project were published in a paper entitled ‘An artificial intelligence approach to predicting personality types in dogs, at the prestigious journal Nature Scientific Reports. This journal is a top-tier Q1 journal celebrated as the fifth most-cited journal globally, boasting over 738,000 citations and 134,873,093 downloads (2022 Journal Citation Reports® Science Edition, Clarivate Analytics, 2023). This paper received a significant international news coverage and Almetric score of 135 (by 23rd April 2024). This means that the paper is in the 98th percentile and it is in the top 5% of all research outputs ever tracked by Almetric (more than 25 million research outputs) (Source). 

This research is ongoing, with additional publications currently in development.

Furthermore, Dr Amirhosseini collaborated with Nex Power Ltd. and University of Lincoln to work on a project about using Artificial Intelligence to enhance the Lithium Battery Recycling process. In this collaboration, a framework was developed that facilitates the application of ML in LIB recycling. This framework serves as a valuable guide for researchers and practitioners looking to integrate ML into this field effectively. This framework was compared with other existing frameworks and the outcomes show that it can provide more advantages and can address most common limitations that the previous frameworks were facing with. By providing more details on the pre-processing, feature engineering, and evaluation phases, this framework can also enable the researchers with low technical skills to apply ML models in their analysis and product development. The outcomes of this collaboration were published in two Q1 and Q2 journals.

Additionally, Dr Amirhosseini collaborated with Keptika Ltd. (UK) to develop an AI powered system to enhance self-reflection practice in coaching. The developed system can assist coaches in note-taking and tracking a live session progress, helping maintain focus and achieve goals. This system, which can identify key coaching segments with 85% accuracy, was evaluated using a dataset of over 1000 English coaching sessions, making it a novel approach for active self-reflection and performance evaluation during live sessions.

Moreover, he has submitted different grant applications in collaboration with Uptime Labs Ltd. (UK) and Solve Energy Service Ltd. (UK). 

Please check the list of publications in the following sections on this page to know more about the outcomes of other industrial collaborations which have been published in renowned international journals and conferences. 
Dr Amirhosseini 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 ‘Applied Sciences’, ‘Cognitive Processing’, ‘Multimedia Technologies and Interaction’, ‘Mathematics’, ‘Digital Scholarship in the Humanities’, ‘Cognitive Computation and Systems’, ‘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 so far and is the lead supervisor for 4 PhD and Professional Doctorate students. 

PUBLICATIONS AND APPEARANCES

Paper publications in international refereed journals and conferences

  • Amirhosseini, M.H., Yadav, V., James, A.S., Pettigrew, P., and Kian, P. (2024) 'An Artificial Intelligence Approach to Predicting Personality Types in Dogs', Nature Scientific Reports, 14, 2404. DOI: 10.1038/s41598-024-52920-9
  • Valizadeh, A., Amirhosseini, M.H., Ghorbani, Y. (2024) ‘Predictive Precision in Battery Recycling: Unveiling Lithium Battery Recycling Potential through Machine Learning’, Computers and Chemical Engineering, 183, pp. 108623. DOI: 10.1016/j.compchemeng.2024.108623
  • Amirhosseini, M.H., Kazemian, H., Phillips, M. (2024) 'A Graph-Based Method for Identity Resolution to Assist Police Force Investigative Processes', Journal of Cyber Security Technology, DOI: 10.1080/23742917.2024.2354555
  • Amirhosseini, M.H., Alam, N., Kalabi, F., and Virdee, B. (2024) 'An AI Powered System to Detect Autism Spectrum Disorder in Toddlers', 5th International Conference on Data Analytics & Management (ICDAM-2024), London, UK.
  • Amirhosseini, M.H., Adefemi, L.A., and Karami, A. (2024) 'Prediction of Depression Severity and Personalised Risk Factors Using Machine Learning on Multimodal Data', The 12th IEEE International Conference on Intelligent Systems, Golden Sands, Bulgaria.
  • Mudianselage, I.D., Amirhosseini, M.H., Li, Y., and Arachchillage, D.J. (2024) 'Artificial Intelligence Driven Prediction of Multi Organ Failure in Patients with COVID-19', The 12th IEEE International Conference on Intelligent Systems, Golden Sands, Bulgaria.
  • Khatri, A., Lota, J., Nepal, P., and Amirhosseini, M.H. (2024) Utilizing machine Learning Techniques to Predict State-of-Charge in Li-ion Batteries, The 12th IEEE International Conference on Intelligent Systems, Golden Sands, Bulgaria.
  • Valizadeh, A., Amirhosseini, M.H., (2024) ‘Machine Learning in Lithium-Ion Battery: Applications, Challenges, and Future Trends’, SN Computer Science. (Manuscript Accepted)
  • Amirhosseini, M.H., Nabeela, B., Gaikwad, K., and Iwuchukwu, C.E. (2024) 'Machine learning-based sentiment analysis for the social media content related to the Ukraine-Russia conflict', The 16th International Conference on Advances in Social Networks Analysis and Mining, Calabria, Italy. (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, 1–12, DOI: 10.1049/ccs2.12087
  • 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
  • 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, Proceedings of Data Analytics and Management (ICDAM 2023), Lecture Notes in Networks and Systems, vol 785, pp. 81-94. DOI: 10.1007/978-981-99-6544-1_7
  • Bhatt, S., Ghazanfar, M.A., Amirhosseini, M.H. (2023) Machine Learning based Cryptocurrency Price Prediction using historical data and Social Media Sentiment, The 5th International Conference on Machine Learning & Applications, Sydney, Australia. Proceedings published at Computer Science & Information Technology, 13 (10), pp. 1-11, DOI: 10.5121/csit2023.131001
  • 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, Proceedings published at IFIP Advances in Information and Communication Technology, vol 646, pp. 471-482, Springer, DOI: 10.1007/978-3-031-08333-4_38.
  • Phillips, M., Amirhosseini, M.H., and Kazemian, H. (2020) "A Rule and Graph-Based Approach for Targeted Identity Resolution on Policing Data," 2020 IEEE Symposium Series on Computational Intelligence (SSCI), Canberra, ACT, Australia, pp. 2077-2083, doi: 10.1109/SSCI47803.2020.9308182.
  • 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

  • Associate editor for Special Issue on “Machine Learning Applications in Psychology” at IET Cognitive Computation and Systems Journal. 
  • Technical Chair for the 5th International Conference on Data Analytics and Management (ICDAM 2024), 14-15 June 2024, London, United Kingdom.
  • Technical Chair for the 4th International Conference on Data Analytics and Management (ICDAM 2023), 23-24 June 2023, London, United Kingdom.
  • 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 organizer and chair of a special session on “Machine Learning Applications in Psychology” at the IEEE World Congress on Computational Intelligence, 18-23 July 2022, Padua, Italy.
  • Main organizer and chair of a Symposium on “Machine Learning Applications in Cyber Security” at the IEEE Symposium Series on Computational Intelligence (IEEE SSCI 2020), 1-4 December 2020, Canberra, Australia. 
  • Main organizer and chair of a special session on “Machine Learning Applications in Cyber Security” at the IEEE World Congress on Computational Intelligence (IEEE WCCI 2020), 19-24 July 2020, Glasgow, Scotland.
  • 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 (IEEE WCCI), IEEE International Joint Conference on Neural Networks (IJCNN), and IEEE Symposium Series on Computational Intelligence (IEEE 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).

Guest speaker and panellist

  • Guest speaker at the Big Data & AI World London Conference at ExCeL London. Title of presentation:  'Artificial Intelligence and Social Media - Opportunities and Threats.' (2024)
  • Speaker at the 84th Annal Meeting of the Academy of Management (AOM 2024) in Chicago, IL, USA. Symposium 12834: Uncovering the Hidden Economic Value of Social capital. Title of presentation: ‘How AI can Improve Learning through Self-Reflection: The Example of AI-Supported Executive Coaching’. (2024)
  • Panellist at the Black Voices in Coaching Research Conference in London. Title of the discussion panel: ‘Decolonizing Coaching: Integrating Indigenous and Ancestral Knowledge.’ (2024)
  • Panellist at the Year of Science Event at University of East London.  Title of panel discussion: ‘Can AI Revolutionize inclusivity in Recruitment?’ (2024)
  • Panellist at the International IORMA Webinar. Title of panel discussion: ‘How AI is enhancing Personal Development.’ Available at: https://iorma.com/archives/11206. (2022)
  • Guest speaker at Coventry University, Global Leaders Programme. Title of presentation: ‘The future of AI and the impact of AI-based automation on jobs during the new industrial revolution.’ (2020)

In media

Dr Amirhosseini’s research has attracted international attention, leading to interviews with major media outlets such as CBS News and Fox TV, and contributions to public knowledge through national and international newsletters, magazines, and online sources such as The Telegraph (UK), Science Magazine (UK), Mirage News (Australia), Study Finds (US), EurekAlert! (US), SciTechDaily (US), Police Magazine (US), BNN (China) , Ladepeche (France) , Liberated Digital (Spain) , ADP Live (India) , Med India (India) ,and  La Stampa (Italy).

International news coverage

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 has also contributed to the UEL overseas collaboration and partnership portfolio as a link tutor for UEL international partners.

Dr Amirhosseini supervises a significant number of MSc and BSc final projects. He has one PhD completion so far and is the lead supervisor for 4 PhD and Professional Doctorate students. 

He is the winner of the Staff Award for 'Innovative Teaching' in 2022 and for 'Leadership through Change' in 2023. Additionally, University of East London achieved the prestigious 2024 AAC National Apprenticeship High Commendation Award for ‘Digital Apprenticeship Provider of the Year’ because of the Digital and Technology Solutions Apprenticeship course led by Dr Amirhosseini.

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)
  • Module Leader of Artificial Intelligence (Level 5 - Second year of BSc course)
  • Module Leader of Professional Practice 1 (Level 4 - First year of BSc Apprenticeship 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)

Publications

The last four years of publications can be viewed below. 

Full publications list

Visit the research repository to view a full list of publications

Research repository