I am an Assistant Research Professor in Electrical and Computer Engineering at Rice University. My research lies at the intersection of wireless networking, machine learning, and reconfigurable computing and software-defined systems. My current work focuses on developing intelligent and efficient wireless networks by leveraging AI-driven resource allocation, RAN virtualization, and large-scale MIMO architectures. I design and implement end-to-end systems that integrate real-time machine learning algorithms with advanced wireless protocols to optimize performance in next-generation networks, including 5G and beyond.
MagmaML: Towards Automated Management for Low-resource 5G Cellular Network Deployments
Facebook Magma Conference, Feb 2021 [
Slides][
Video]
POWDER-RENEW: A shared software-defined massive MIMO platform
IEEE Communications Theory Workshop, June 2019 [
Slides]
A Deep Reinforcement Learning-Based Resource Scheduler for Massive MIMO Networks
Qing An, Chris Dick, Santiago Segarra, Ashutosh Sabharwal, and Rahman Doost-Mohammady
IEEE TMLCN 2023
Agora: Software-based real-time massive MIMO baseband processing
Jian Ding, Rahman Doost-Mohammady, Anuj Kalia, and Lin Zhong
CoNEXT 2020 [
PDF]
Good Times for Wireless Research
Rahman Doost-Mohammady, Oscar Bejarano, and Ashutosh Sabharwal
WiNTECH 2020 [
PDF]
Design and Implementation of Scalable Massive MIMO
Clayton Shepard, Josh Blum, Ryan Guerra, Rahman Doost-Mohammady, and Lin Zhong
OpenWireless 2020 [
PDF]
Postdoc
Current
Alumni