Rafid Umayer Murshed
PhD Student · Computer Science · University of Illinois Urbana–Champaign
I'm Rafid Umayer Murshed, a Computer Science PhD student at the University of Illinois Urbana-Champaign. I design physics-informed machine learning algorithms that unlock the full potential of 6G networks by enabling hyper-realistic channel modeling and intelligent control of the radio environment.
Biography
I received my B.Sc. in Electrical and Electronic Engineering from the Bangladesh University of Engineering and Technology (BUET) in May 2022, with a concentration in signal processing and wireless communications. My undergraduate thesis, under the supervision of Dr. Farhad Hossain, explored deep learning–based hybrid beamforming for MIMO systems.
After graduation, I worked as a research engineer at the Japan Institute of Disaster Prevention and Urban Safety (BUET-JIDPUS), where I contributed to the Earthquake Early Warning (EEW) project. In August 2023, I began my M.Sc. in Electrical and Computer Engineering at The University of Texas at Dallas under Dr. Mohammad Saquib, completing the degree in May 2025 with a perfect GPA of 4.0/4.0. My master’s thesis, Real-Time Beamforming and Metasurface Design for Low-Latency 6G Wireless Networks, advanced low-complexity algorithms for massive MIMO and RIS optimization.
I am currently pursuing my Ph.D. in Computer Science at the University of Illinois Urbana-Champaign (UIUC) as a recipient of the Siebel School Fellowship. I have joined the iSens Lab under Dr. Elahe Soltanaghai, where my research focuses on physics-informed deep learning for next-generation wireless systems. My work spans trustworthy digital twins, RF propagation modeling, MU-MIMO beamforming, reconfigurable intelligent surfaces, resource allocation, and wireless sensing. I have published in leading journals and conferences, and have been invited to present my research in venues such as the NSF MERIF workshop and the ARAFest.
Focus areas
- Physics-guided deep learning for RF propagation and ultra-massive MIMO beamforming.
- Neural representations and generative models for wireless channel emulation.
- Reliable sensing-communication co-design, RIS/metasurface control, and 6G digital twins.
Latest updates
- August 2025 Started the PhD program in Computer Science at UIUC focusing on physics-informed AI for 6G. Crossed 100+ citations on Google Scholar.
- May 2025 Graduated from UT Dallas with an M.Sc. thesis on RF learning and intelligent wireless systems.
- March 2025 Released the MetaFAP preprint on meta-learning frequency-agnostic metasurface models.
- October 2024 Presented our work on self-supervised robustness for UM-MIMO THz communications at IEEE ICC Workshops 2024 in Denver.
- June 2024 Published Beyond Traditional Beamforming in IEEE Communications Letters, introducing singular vector projection techniques.
- March 2024 Our contrastive GNN approach for earthquake early warning appeared in IEEE Transactions on Geoscience and Remote Sensing.