About the Journal

UMT Artificial Intelligence Review (UMT-AIR) is a double-blind peer-reviewed biannual journal that provides a wide variety of perspectives on the theory and practices of work in the realm of AI. We welcome research papers on foundational and applied work, as well as case studies. UMT-AIR also invites studies on critical analytical studies on AI applications, which present an in-depth evaluation of the AI tools and methods being employed.

Announcements

Current Issue

Vol. 6 No. 1 (2026): Spring 2026
View Vol. 6 No. 1 (2026): Spring 2026
Published: 2026-06-25

Articles

  • PRISM: A Framework for Preprocessing Impact Analysis in Machine Learning via Signature-based Modeling

    ABU BAKAR SHABBIR, Khadija Amber
    1-23
    DOI: https://doi.org/10.32350.umt-air.61.01

  • EEG-Based Depression Detection using Time-frequency Representation and Transfer Learning Techniques on MODMA Dataset

    Rida Fatima, Amad Ud Din, Amair Arsalan
    24-44
    DOI: https://doi.org/10.32350.umt-air.61.02

  • An AI-Driven Predicative Frameworks for Sustainable Road Infrastructure and Annual Budget Forecasting in District Level Urban Planning

    Saba Memon
    45-56
    DOI: https://doi.org/10.32350.umt-air.61.03

  • Credit Card Fraud Detection Using an Ensemble Deep Learning Approach: CNN, LSTM, and DNN

    abdullah mehboob
    57-73
    DOI: https://doi.org/10.32350.umt-air.61.04

  • Reinforcement Learning for Optimizing Climate Change Interventions: A DQN-Based Approach

    Sana Irshad, Muhammad Mateen Sadiq
    74-86
    DOI: https://doi.org/10.32350.umt-air.61.05
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