Dr Taha Mansouri

Biography	Taha is an expert in AI, Computer Vision, and Deep Learning. He holds a dual PhD, one in Artificial Intelligence and Deep Learning from the University of Salford (UK), and another in Information Technology Management from Allameh Tabataba'i University in Iran. With over 14 years of industry experience, he brings a strong practical foundation to his academic career, which began in 2012. Since joining the University of Salford as a KTP Associate in 2019, and later becoming a Lecturer in AI in 2022, Taha has focused his research on key areas such as AI Ethics, Computer Vision, and Large Multimodal Models, including LLMs and LVMs. His research has been published in respected journals and reflects both academic depth and real-world relevance. He is also actively involved in several research projects as either Principal Investigator or Co-Investigator. Taha holds two Advance HE teaching qualifications: Fellowship and Senior Fellowship of the Higher Education Academy. These reflect his ongoing commitment to excellence in teaching and learning. He leads the High Performance Computing (HPC) facilities in the School of Science, Engineering and Environment at the University of Salford, supporting research and innovation across various disciplines. Taha also chairs the Salford AI Club, an inclusive community that brings together individuals from diverse backgrounds and roles who share an interest in Artificial Intelligence. The club focuses particularly on the applications of AI in Higher Education. He is an active member of several review panels, including: The EPSRC Peer Review College The EDI Hub+ Flexible Fund Peer Review College The British Council’s International Science Partnerships Fund Review College In 2024, Taha contributed to the academic community as a member of the Organizing Committee and Programme Committee for the 35th Annual Conference of the International Information Management Association (IIMA). He also served as Track Chair for Ethics in Digital, AI, Big Data, Data Science, and Marketing Science. https://iima.org/wp/call-for-papers/
Research Interests	Ethics in AI Taha’s research explores a wide range of ethical challenges in Artificial Intelligence, focusing on fairness, explainability, transparency, and compliance. He has published extensively in this area and regularly presents his work at national and international conferences. He led the Expert Legal Intelligence (ELI) project, an Innovate UK Smart Grant-funded initiative with a total value of £500,000. This project focused on ensuring ethical compliance of Large Language Model (LLM)-based AI systems within the legal sector. As part of the project, Taha also supervised a postdoctoral research associate to support the development of robust, ethically sound AI solutions. In another project, Taha is currently developing ethical Automatic Speech Recognition (ASR) models through a £30,000 collaboration funded by Evidential Ltd and the Manchester Growth Hub. He has previously led or contributed to three externally funded research projects focused on fairness and bias in AI. These include: Academic Lead for WATCH-AI: UK–EU Benchmarking Tools for Trustworthy General-Purpose AI, funded by the British Academy’s Horizon Europe Pump Priming initiative. Academic Lead for Towards Inclusive AI, a University of Exeter internal fund project investigating fairness in emotion recognition algorithms across cultures. Co-Investigator for Innovate UK ICURe: Ethical AI. Beyond these projects, Taha is committed to advancing fairness and transparency in AI systems. His research includes developing techniques for measuring fairness in computer vision models and exploring Explainable AI (XAI) to make deep learning models more interpretable. Recently, he initiated a study on bias in facial emotion detection systems, investigating how age, gender, ethnicity, and culture may influence AI outcomes—highlighting important concerns about equity and accountability in automated systems. Computer Vision Taha has a deep interest in Large Vision Models (LVMs) and Foundation Models, which drives his research in computer vision. He has authored a number of impactful publications in this space and currently supervises three PhD students working on practical, real-world applications of computer vision technologies. One of his recent projects involved leading a pump-priming initiative at the University of Salford to integrate computer vision into Retrieval-Augmented Generation (RAG) models. The aim was to support residents in social housing by identifying and mitigating issues like mould and dampness through automated visual analysis. Taha also supervised an iCASE-funded PhD project focused on corrosion detection using computer vision techniques, contributing to the development of smarter infrastructure monitoring systems. AI for Good Taha is deeply passionate about using AI for social good. His research and outreach efforts focus on leveraging AI to address critical challenges in education, poverty, and social justice. He believes that AI, when thoughtfully applied, can be a powerful force for positive change. His current research includes exploring the role of AI in higher education, with a particular focus on curriculum design and the development of assessment methods that are resilient to AI misuse. He contributed to the development of an AI-based framework for detecting and addressing academic misconduct, which has been shared widely through conferences and academic publications. RAs: 1. Manzar Malik - m.i.malik2@salford.ac.uk - Developing Ethical LLMs; mould and dampness detection using multimodal generative AI 2. Zeeshan Afzal - Z.Afzal2@edu.salford.ac.uk - Developing ASR models for legal settings 3. Hamid Kouhpeimay Jahromi - KouhpeimayJahromi1@salford.ac.uk - Developing Ethical transcripting models for legal settings
Teaching and Learning	Taha has led the following modules: Data Structures and Algorithms (DSA): Providing a strong foundation in computational thinking and problem-solving techniques. Machine Learning and Data Mining (MLDM): Equipping students with the skills to analyze large datasets and extract meaningful insights. He takes a leadership role, curriculum development, and delivering new modules, including: Big Data Tools and Techniques (BDTT) (MSc): Equipping students with the skills to handle and analyze large and complex datasets. Principles and Design of IoT Systems (PDIoT) (MSc): Providing students with the knowledge to design and develop Internet of Things (IoT) systems, in particular Computer Vision and Remote Sensing.
Scopus Author ID	25958222000
PhD Supervision Availability	Yes
PhD Topics	My research focus is on AI, particularly in Computer Vision, LLMs, and broader Multimodal Large AI Models. I'm passionate about exploring how AI can be applied to real-world problems and how it can be ethical. At present, I am supervising the following PhD students. Feel free to contact them for information about the supervision process or any other informal inquiries: PhD Students: 1. Thomas Bolton - t.j.e.bolton@edu.salford.ac.uk - iPhD topic in Computer Vision 2. Elham Albaroudi - e.o.albaroudi@edu.salford.ac.uk - PhD topic in AI fairness 3. Kumail Abbas – k.abbas6@edu.salford.ac.uk - PhD project in collaboration with Chulalongkorn University, Thailand, and the University of Bristol, UK, focusing on machine vision for detecting cow feeding behaviour.