DR. SHAPLA KHANAM
Department of Artificial Intelligence
Faculty of Computer Science and Information Technology
shapla.kum.edu.my| View CV | |
| View 1-Page CV | |
| Publons | |
| Scopus Link | |
| Biography | |
|
Dr. Shapla Khanam is a renowned academician and researcher celebrated for her substantial contributions to Cybersecurity and AI. Dr. Khanam is currently a Senior Lecturer at the Department of Artificiall Intelligence (AI), Faculty of Computer Science and Information Technology at University of Malaya (UM), in Malaysia. Previously, she held the position of Senior Lecturer at HELP university and Assistant Professor at two different universities in Bangladesh. Additionally, she has worked as a Research Assistant at the University of Malaya (UM), a Lecturer, and an Application Engineer at Atlassian (an Australlian owned IT company) in Malaysia. Dr. Khanam earned her Ph.D. in Cybersecurity of Internet of Things using Deep Learning and her M.Eng. in Telecommunications Engineering from UM. She obtained her B.Sc. in Computer Science from the International Islamic University Malaysia (IIUM). Throughout her career, Dr. Khanam has actively contributed to various roles within professional organizations, notably serving as Vice-Chair of IEEE-UM and as Chair of the IEEE Women in Engineering (WIE) affinity group at UM. Dr. Khanam has authored numerous articles published in reputable international Q1-rated journals and has presented various research ideas at conferences. Her research interests span several areas, including:
|
|
Publication
Finance
Machine learning model for predicting net environmental effects
NURTURING CREATIVITY AND INNOVATION IN STUDENTS: EMBRACING HOLISTIC APPROACHES THROUGH BRAIN HEMISPHERES, HEART-BRAIN COHERENCE, AND CARDIOGNOSIS
Social engineering threat analysis using large-scale synthetic data
Gen-Optimizer: A Generative AI Framework for Strategic Business Cost Optimization
Tackling Intruders in Wireless Mesh Networks.
AI Literacy and LLM Engagement in Higher Education: A Cross-National Quantitative Study
Performance Evaluation of Weighted Fair Queuing Model for Bandwidth
An Enhanced Mechanism to Defend Selective Forwarding Attacks in IoT
Investigation of frequency reuse techniques for LTE networks
