Dr Mohammad H Amirhosseini

Dr Amirhosseini's research and expertise cover a broad range of areas, with a focus on the application of AI and Machine Learning.

His interests include: 

• Psychology and Healthcare: Cognitive processing, personal development, mental health, coaching, neuro-linguistic programming, personality type prediction, and detecting depression and anxiety.
• Human-Computer Interaction & Language: Natural language processing, social media analysis, sentiment analysis, and the detection and prevention of hate speech, racism, and sexism.
• Organisational & Business Applications: Energy recycling, finance, cybersecurity, identity resolution, fraud detection, and organisational performance.
• Diverse Fields: Animal behaviour and personality, politics, and international relations.

Dr Amirhosseini's PhD thesis was titled "Neuro Linguistic Programming Automation for Improvement of Organisational Performance."

In his research, he used Natural Language Processing (NLP) and machine learning to automate Neuro-Linguistic Programming (NLP), a methodology for recognising and modifying human behavioural patterns. This resulted in the development of intelligent software.

The novel methodology he created for this automation eliminated human error, leading to software with superior accuracy, reliability, and efficiency.

After earning his PhD, Dr Amirhosseini served as a postdoctoral research fellow for the SPIRIT project, a €5 million EU Horizon 2020 initiative. The SPIRIT project brought together a consortium of 17 partners from nine European countries to help law enforcement agencies identify cybercriminals. The team developed sophisticated AI-based tools to analyse massive amounts of data from various sources. Dr. Amirhosseini was a key researcher on the technical team. He developed research methodologies for identity resolution using police datasets, data from web crawlers, and social media. He also applied Natural Language Programming (NLP) to the project's work. The team's novel approach led to a new system prototype for scalable, privacy-preserving intelligence analysis.

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).

Since joining the University of East London, he has established collaborations with several esteemed institutions, including: University of Pennsylvania, Imperial College London, University of Lincoln, London Metropolitan University, and Adelphi University. These partnerships have resulted in influential publications in prestigious venues, such as the Q1 journal Nature Scientific Reports and the IEEE World Congress on Computational Intelligence conference.

As an academic partner and senior consultant, he has collaborated with a variety of national and international companies, including 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). These partnerships have been instrumental in: Submitting Innovate UK grant applications, publishing high-quality work in top-tier (Q1 and Q2) journals and at prestigious conferences, and developing commercial products.

In partnership with Whyness Ltd., Dr Amirhosseini was awarded an Innovate UK Smart Grant. His project, titled "Automation of Neuro-Linguistic Programming methods using Artificial Intelligence to interpret unconscious thoughts and values for personal development," was built on the latest research in AI, neuroscience, and personal development. The work included three custom AI models that he developed. (More details are available in the 'Funding' section of this page.)

Following this project, he began a new collaborative project as a senior consultant for Dogvatar Ltd. in Florida, USA, and the University of Pennsylvania.

The project used Artificial Intelligence to predict dog behavioural characteristics and develop a dog personality assessment tool. This tool aims to facilitate dog adoption and improve the training success rate for working dogs. The project's findings were published in a paper titled "An artificial intelligence approach to predicting personality types in dogs" in the journal Nature Scientific Reports. This prestigious Q1 journal is globally recognised as the fifth most-cited journal, with over 738,000 citations. The paper received significant international media attention and an Altmetric score of 135. This places it in the 98th percentile, meaning it is in the top 5% of all research outputs ever tracked by Altmetric.

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

Dr Amirhosseini collaborated with Nex Power Ltd. and the University of Lincoln on a project to use artificial intelligence to improve the lithium-ion battery recycling process. In this project, they developed a framework that makes it easier to apply machine learning (ML) to this process. This framework is a valuable tool for both researchers and professionals, helping them effectively integrate ML into their work. When compared to existing frameworks, this new one offers several advantages and overcomes common limitations. By providing more detailed guidance on data pre-processing, feature engineering, and evaluation, the framework also allows researchers with limited technical skills to apply ML models in their analysis and product development. The results of this collaboration were published in two high-quality journals (Q1 and Q2).

Dr Amirhosseini collaborated with Keptika Ltd. (UK) to create an AI-powered system that improves self-reflection in coaching. The system helps coaches by assisting with note-taking and tracking the progress of a live session and helping coaches stay focused and achieve their goals. Evaluated using a dataset of over 1,000 English coaching sessions, the system accurately identifies key coaching segments with an 85 per cent accuracy rate. This innovative approach offers a new way to actively practice self-reflection and evaluate performance during live sessions.

He has submitted grant applications in collaboration with Uptime Labs Ltd. (UK) and Solve Energy Service Ltd. (UK).

For more information on the outcomes of other industrial collaborations, you can check the list of publications in the following sections of this page, which have been published in prestigious international journals and conferences. 

Dr Amirhosseini has organised and chaired several special sessions and issues, focusing on the intersection of AI and various fields: 

• Machine Learning in Cybersecurity: He was the main organiser and chair for special sessions at the 2020 IEEE World Congress on Computational Intelligence and the 2020 IEEE Symposium Series on Computational Intelligence.
• Machine Learning in Psychology: He organised a special session for the 2022 IEEE World Congress on Computational Intelligence and served as a guest editor for a special issue with the same title in the Cognitive Computation and Systems Journal.
• AI Applications in Healthcare and Psychology: He also organised two other special issues for the Electronics Journal on "Applications of Recommender Systems in Healthcare" and "Applications of Artificial Intelligence in Psychology."

He has served as a reviewer for numerous academic journals and conferences, including: 

• Journals: Applied Sciences, Cognitive Processing, Multimedia Technologies and Interaction, Mathematics, Digital Scholarship in the Humanities, Cognitive Computation and Systems, Informatics, Sensors, and Modelling.
• Conferences: IEEE World Congress on Computational Intelligence (WCCI), IEEE International Joint Conference on Neural Networks (IJCNN), and IEEE Symposium Series on Computational Intelligence (SSCI).

Additionally, he was a reviewer for the Artificial Intelligence Health & Care Award Competition 3, a collaborative effort by the Accelerated Access Collaborative (AAC), 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.