Michael McGarry

Michael McGarry is an Associate Professor in the Department of Electrical and Computer Engineering at the University of Texas at El Paso (UTEP). His research focuses on communication networks, particularly mechanisms for improving network efficiency through machine learning and optimization. He leads UTEP's Communication Networks Laboratory (NetLab), which explores fault localization, automated network management, and bandwidth forecasting. McGarry's work has garnered over 2100 citations, with an h-index of 16 and an Erdős number of 2. He has mentored three Ph.D. students, including Rami Haddad, Salvador Melendez, and Christopher Mendoza, who now hold prominent roles in academia and industry.

His research interests span machine learning applications in networking, video networking, cloud computing, and medium access control (MAC) protocols. Notable contributions include techniques for network fault localization using unsupervised machine learning and innovations in hybrid PON/xDSL access networks. McGarry has also developed methodologies for optimizing bandwidth distribution and reducing energy consumption in communication systems.

• Awards: 2009 IEEE Communications Society Best Tutorial Paper Award
• Grants: Recent funding focuses on network management automation and fault detection.

McGarry's collaborative projects include integrating OpenTap with quantum entanglement testbeds and advancing SDON (Software Defined Optical Networks) architectures. His lab’s work emphasizes practical solutions for real-world network challenges, from enterprise systems to military applications.