Proceedings of International Conference on Information Technology and Applications

Dr. Abrar Ullah is an associate professor and director of Postgraduate Studies at the School of Mathematical and Computer Sciences, Heriot-Watt University, Dubai Campus. He holds an M.Sc. in Computer Science (2000) from the University of Peshawar and a Ph.D. in Security and Usability from the University of Hertfordshire, UK.Dr. Ullah has over 20 years of experience in both industry and academia, with a strong background in teaching and enterprise systems development. He began his teaching career in 2002 as a lecturer at the University of Peshawar and the Provincial Health Services Academy, Peshawar. In 2008, he joined ABMU NHS UK as a lead developer, contributing to several key NHS systems. In 2011, Abrar joined professional services at Cardiff University as “Team Lead & Senior Systems Analyst” and led a number of successful strategic and national level projects.Dr. Sajid Anwar is a full professor at the Center of Excellence in Information Technology Institute of Management Sciences (IMSciences), Peshawar, Pakistan. He received his M.S. (Computer Science, 2007) and Ph.D. degrees (Software Engineering, 2011) from NUCES-FAST, Islamabad. Previously, he was the head of Undergraduate Program in Software Engineering at IMSciences. Dr. Sajid Anwar is a leading expert in software architecture engineering and software maintenance prediction. His research interests are cross-disciplinary and industry focused and includes search-based software engineering; prudent-based expert systems; customer analytics, active learning and applying data mining and machine learning techniques to solve real-world problems. Dr. Sajid Anwar is an associate editor of Expert Systems Journal Wiley. He has conducted and led collaborative research with government organizations and academia and has published over 50 research articles in prestigious conferences and journals.

• Unveiling the Hidden Pandemic of IoT Malware with Biological and Health Approaches.- Auditing Windows Bluetooth Security at the Application Layer.- Comparison of Machine Learning Models for Early Prediction of Diabetes with LIME Interpretability.- Pattern Recognition in Disaster Response: Leveraging Machine Learning for Twitter Analysis.- TTL: Transformer and Transfer Learning Approach To Detect Sunflower Disease.- The Moderating Role of Risk Aversion in an Extended UTAUT Cryptocurrency Adoption Model.- NLP on Text Messages using Sentimentality Investigation.- Audio-Visual Features-based Framework for Advertisement Detection from Sports Videos.- Context-aware Medical Question Answering: An Extended Transformers-Based Approach with BioBERT Encoding for Restricted Domain Queries.- Enhancing Seabass Detection in Aquaculture: A Step Towards Automated Behavioural Analysis using AI.