Khoa Tran
Khoa Tran
Department: Artificial Intelligence & Machine Learning
Dr. Khoa Tran is a Doctoral Advisor for AI/ML students at The George Washington University. He is a seasoned AI and network engineering professional with over two decades of experience building enterprise-grade infrastructure and intelligent systems for Fortune 500 companies. He currently serves as an AI Application Engineer at Airbnb, where he builds and deploys enterprise AI agents across HR, Legal, Finance, Security, and other business functions, and designs custom MCP servers and tooling to accelerate developer and non-developer workflows alike. He also continues to serve as a Staff Network/DevOps Engineer at Airbnb, leading the design and implementation of multi-cloud networking solutions supporting production workloads and AI capabilities. Prior to Airbnb, Dr. Tran held senior engineering and architecture roles at Apple, Yahoo!, Juniper Networks, and Cisco.
Dr. Tran's research sits at the intersection of artificial intelligence and network engineering, with a focus on agentic AI systems, intelligent network management, predictive analytics, and automated optimization. As a doctoral advisor, he guides students on advanced research topics including energy-aware dynamic adaptation for edge AI devices, AI-driven approaches to financial risk supervision, and generative AI for secure Infrastructure-as-Code. His own published research includes work on time series analysis and stock price forecasting using customized decoder architectures. He holds dual Cisco CCIE certifications in Routing & Switching and Wireless, as well as AWS Solution Architect and SysOps Associate certifications.
Dr. Tran holds a Doctor of Engineering (D.Eng.) in Artificial Intelligence & Machine Learning from The George Washington University, a Master of Computer Science with a specialization in Machine Learning from the Georgia Institute of Technology in Atlanta, Georgia, a graduate certificate from Santa Clara University in Santa Clara, California, and a Bachelor of Applied Science in Computer Engineering from the University of Toronto, Canada.