Email: makbar[at]utep[dot]edu | Phone: (915) 747-5883
I am an Associate Professor in the Department of Computer Science at The University of Texas at El Paso (UTEP), where I have been a faculty member since Fall 2017. Before that, I was a Research Assistant Professor and the Assistant Director of the CyberShare Center of Excellence at UTEP. I received my Ph.D. in Computer Science from Virginia Tech, a Master’s degree from Montana State University–Bozeman, and a Bachelor’s degree from Shahjalal University of Science and Technology in Bangladesh.
My research focuses on information retrieval, data integration, and analytics, with applications in areas such as cybersecurity for industrial control systems and manufacturing, as well as public health. I develop methods to identify and analyze vulnerabilities and weaknesses and to anticipate emerging threats, with the goal of making critical systems more secure and resilient. In teaching, I design and integrate technology-enabled approaches that support student learning and strengthen problem-solving in computing and programming.
Research Focus
Information Retrieval and Integration
My work in this area develops methods for retrieving, integrating, and representing information from diverse sources. This includes designing computational frameworks that bring together heterogeneous datasets, such as cybersecurity knowledge bases (e.g., CVE, CWE, ATT&CK) or public health records, to enable effective search, reasoning, and decision-making.
Predictive Modeling and Data Analytics
I design and apply AI/ML- and data-driven predictive models to assess risks in complex systems. My research advances methodologies for forecasting and early warning, with applications in areas such as cyberattack prediction, vulnerability evolution, and multi-disease outbreak detection.
Cybersecurity
A significant portion of my work focuses on cybersecurity, particularly for critical infrastructure domains such as manufacturing and health sector. My research explores software vulnerabilities, attack vectors in industrial control systems, and methods for bridging cyber threat and weakness datasets to enhance risk analysis and defense strategies.
Technology-Enabled Learning
I investigate how technology can advance learning by creating systems that adapt to learner needs and provide meaningful insights for instructors. My work spans mobile platforms, game-based environments, and AI/ML-based predictive systems such as PULSE, which analyzes programming activity data to detect and address student struggles in real time. Across projects like Dysgu, Sol y Agua, and PULSE, I focus on building innovative, evidence-based approaches that enhance how learning is experienced, supported, and understood.
Prospective Students
I am looking for motivated graduate students to join my research group. My work spans AI/ML, data integration, and predictive modeling, with applications in cybersecurity, public health, and technology-enhanced education. If you are interested, please reach out to me by email.