Christopher Porras is a graduate researcher at The University of Texas at El Paso (UTEP), where he is pursuing a Master of Science in Software Engineering with a focus on Secure Cyber-Systems. His primary research centers on enhancing the security of Operational Technology (OT) networks, specifically through the development of a Delay-Sensitive Provenance Framework for detecting intrusions in critical infrastructure. As a CyberCorps® Scholarship for Service (SFS) Scholar, Christopher has been actively involved in designing methods to audit system-level logs and building provenance graphs to monitor OT network activity, aiming to improve the detection and response to cyber threats. He has constructed a comprehensive mock OT network environment to simulate real-world conditions and validate his security frameworks. Additionally, he collaborated with Pacific Northwest National Laboratory on leveraging High Performance Computing (HPC) resources for distributed deep learning (DDL) applications, utilizing profiling tools like Score-P and frameworks such as PyTorch and Horovod.