New collaboration positions Salford as global centre of expertise in data science and AI

The International Conference on Data Science, AI, and Applications was organised by a collaboration between the University, the DSAI (Data Science and AI) Hub, and the EATL (Ethics Advanced Technology Ltd) Innovation Hub, Bangladesh.

Receiving outstanding feedback, the conference helped to further enhance the university’s profile in the region. Academic participation was impressive, with 218 submissions, 85 papers presented orally and 14 posters displayed. 

Mr Mubin Khan, Managing Director of the EATL Innovation Hub, said: “Collaborating with the University of Salford’s Data Science and AI Hub to deliver the conference at the EATL Innovation Hub has demonstrated the strength of our joint efforts on a global stage. It has clearly positioned Salford as a global centre of expertise in data science and AI, with research that responds directly to industry needs. This is a powerful example of how international collaboration between academia and industry can drive innovation, build global networks, and deliver real-world impact.”

Taking place in Kalakair Hi-Tech City, Dhaka,  several high-profile Bangladeshi dignitaries attended the event, including Finance Adviser to the Government of Bangladesh, Secretary of State for Information, Communications and Technology to the Government of Bangladesh, Managing Director and CEO of Pubali Bank and three Vice Chancellors, (University of Dhaka, Bangladesh Digital University and National University of Bangladesh (the second-largest university in the world, with 3.5 million students)).

The opening day keynote address was delivered by Dr. Latifur Khan, IEEE Fellow and Director of the Big Data Analytics and Management Lab at the University of Texas, Dallas. On the second day, Professor Sushmita Mitra of the Indian Statistical Institute will present a keynote on advancements in machine intelligence.

Including in the global speakers, 10 papers were accepted from University of Salford researchers and students, highlighting the significance of data science and AI to the University's research community.

Chairing the Technical Programme Committee was Head of Computer Science and Software Engineering at Salford and Director of Data Science and AI (DSAI) Hub, Professor Mo Saraee. He said: “This first International Conference on Data Science, AI, and Applications brought together high-quality research with clear relevance to real-world challenges. The submissions showed strong links between academic work and industry needs in areas like healthcare, agriculture, cybersecurity, and manufacturing — a crucial step in making sure research leads to real impact.'"

A continuation with the University’s work with EATL, and associated organisations in Bangladesh (EATL Ltd, International Nursing College, International Medical College), this conference has laid a strong foundation for several promising collaborations between Salford and key institutions and stakeholders in Bangladesh. 

Professor Mo Saraee said: “We are enthusiastic about the legacy this conference is already creating, not just in terms of the academic publications, but the new collaborations, and look forward to building on this momentum. The feedback we received from the conference was incredible and we hope to continue this collaboration.”   

Projects currently being explored include Salford to be a lead partner in Bangladesh’s national start-up competition; Short course development for Government of Bangladesh Information and Communication Technology Division; Collaborative development with National University. 

List of papers from the University of Salford

• Understanding Public Perceptions and Behaviours Towards COVID-19 Vaccination: A Multifaceted Analysis - Archanaben Prajapati, Azadeh Mohammadi, and Mohamad Saraee
• Mitigating Intersectional Bias in AI Recruitment: The HITHIRE Model for Ethical Hiring in Saudi Arabia - Elham Albaroudi, Taha Mansouri, Ali Alameer, and Mohammad Hatamleh
• Comparative Evaluation of Machine Learning and Signature-Based NIDS for Multi-Class and Binary Threat Detection - Somayina C. Wen-Udeoji, Maybin K. Muyeba, and Azadeh Mohammadi
• AIMA: An Agentic AI Approach to Vulnerability Scanning of Higher-Education Assessment - Taha Mansouri and Mohammad Saleh Torkestani
• Design and implementation of a Hybrid Fall Detection model: Combining Faster R-CNN Inception V2 with YOLO Object Detection Algorithms in Surveillance System - Benedict Ibe, Dagogo Godwin Orifama, Ali Dan, Ikechukwu Nwagbo Enumah, Dominic Chinedu Ogbuagu, and Gbubemi Erics
• Ecological Overshoot: The Blindspot of Sustainable Computing      - Aviad Bessler, Kaveh Kiani, and Taha Mansouri
• Plant Disease Classification by Ensemble Metaheuristic-Deep Learning Approach - Zerin Jahan, Muhammad Hammad Saleem, Fakhia Hammad, Muhammad Taha, Joy Paul, and Mohamad Saraee
• Analysing and Predicting Housing Affordability Trends in the UK Using Machine Learning - Ebin Varghese, Maybin K. Muyeba, and  Azadeh Mohammadi
• An End-to-End Aspect-Based Sentiment Analysis Framework for a Real-Time Personalized Product Recommendation System -  Usama Ahmed Qasmi, Kaveh Kiani, and Mo Saraee
• A Comparative Analysis of State-of-the-Art Speech-to-Text models for court applications - Ali Alameer, Hamid Kouhpeimay Jahromi, Zeshan Afzal, Manzar Malik, Sean Morphy, and Taha Mansouri