Tom Ngo
M.S. in Artificial Intelligence at Santa Clara University · Research Assistant at the Wireless Intelligent Networks (WIN) Lab
I'm a Master's student in Artificial Intelligence at Santa Clara University and a Research Assistant in the Wireless Intelligent Networks (WIN) Lab, where I apply deep reinforcement learning to the design and optimization of next-generation wireless systems such as Wi-Fi 7 and 6G.
Previously, I worked as a Data Science Intern at the Sacramento Municipal Utility District (SMUD), where I built, fine-tuned, and deployed machine learning models that ran in production at scale. I hold a B.A. in Economics from UC Davis, and I'm broadly interested in how learning-based methods can make complex systems — from wireless networks to utility operations — more efficient and adaptive.
Research Focus
Reinforcement Learning
Deep RL agents (DQN) for intelligent network optimization and control.
Wi-Fi 7 & Multi-Link Operation
Learning-based uplink traffic allocation across MLO links.
6G Technologies
Fluid Antenna, Pinching Antenna, RSMA, and NOMA optimization.
Applied Machine Learning
Predictive modeling and production ML pipelines on real-world data.
News
Paper accepted at IEEE LANMAN 2026
"Application-Aware Learning-Based Uplink Traffic Allocation for Wi-Fi 7 MLO" accepted to the IEEE 32nd International Symposium on Local and Metropolitan Area Networks.
Joined the WIN Lab as a Research Assistant
Started research on deep reinforcement learning for Wi-Fi 7 and 6G network optimization at Santa Clara University.