International Consulting Board

We focused on giving advice, suggestions, and plans to improve the UoT academic, research, and postgraduate programs.

logo-img

Dhiya Al-Jumeily, Professor

Artificial Intelligence Liverpool John Moores University, UK School of Computer Science & Mathematics

Dhiya Al-Jumeily, Professor

  • Education
  • PhD - Liverpool John Moores University, UK

    MSc - Liverpool John Moores University, UK

    BSc - University of Baghdad, Iraq

  • Technical Focus
  • Artificial Intelligence in Medicine

    Machine Learning

    Human Biology

  • Biography
  • Dhiya Al-Jumeily is a professor of Artificial Intelligence and the president of eSystems Engineering Society. He has extensive research interests covering a wide variety of interdisciplinary perspectives concerning the theory and practice of Applied Artificial Intelligence in medicine, human biology, environment, intelligent community and health care. He has published well over 300 peer reviewed scientific international publications, 12 books and 14 book chapters, in multidisciplinary research areas including: Machine Learning, Neural Networks, Signal Prediction, Telecommunication Fraud Detection, AI-based clinical decision-making, medical knowledge engineering, Human-Machine Interaction, intelligent medical information systems, sensors and robotics, wearable and intelligent devices and instruments. But his current research passion is decision support systems for self-management of health and medicine.

  • Newest Selected Publications
  • - Irshad A, Abbas ZH, Ali Z, Abbas G, Baker T, Al-Jumeily D. 2021. Wireless powered mobile edge computing systems: Simultaneous time allocation and offloading policies Electronics (Switzerland), 10

    - Ghareeb S, Hussain A, Khan W, Al-Jumeily D, Baker T, Al-Jumeily R. 2021. Dataset of student level prediction in UAE Data in Brief, 35

    - Baker T, Al-Jumeily D, Maamar Z, Tari Z. 2021. Semantic eSystems: Engineering methods, techniques, and tools SOFTWARE-PRACTICE & EXPERIENCE, 51 :487-488

    - Khan W, Hussain A, Alaskar H, Shamsa TB, Ghali F, Al-Jumeily D, Al-Shamma’a A. 2020. Prediction of Flood Severity Level Via Processing IoT Sensor Data Using Data Science Approach IEEE Internet of Things Magazine,

    - Alloghani M, Aljaaf A, Hussain A, Baker T, Mustafina J, Al-Jumeily D, Khalaf M. 2020. Implementation of machine learning algorithms to create diabetic patient re-admission profiles (vol 19, 253, 2019) BMC MEDICAL INFORMATICS AND DECISION MAKING, 20