Mir Lodro received an MRes and a Ph.D. in Electrical and Electronic Engineering from the University of Nottingham, UK, in 2015 and 2021, respectively. While obtaining his Ph.D. and MRes, he worked on software-defined radio testbeds for near-field MIMO in complex propagation environments and spectrum sensing techniques for cognitive radio, respectively. He was a research fellow in RF and communication engineering at the George Green Institute for Electromagnetics Research (GGIEMR), University of Nottingham, where he worked with an industrial partner on signal intelligence and the design of an SDR-based passive RF sensor system for drone detection. He has worked on embedded SDRs, in particular, the E310/E312 and N321 USRPs from Ettus Research and the Artificial Intelligence Radio-Transceiver (AIR-T) from DeepWave. He has worked on the SDR and Reconfigurable Intelligent Surface (SDR-RIS) testbeds for the PoC of channel hardening and digital modulation classification using deep learning. In 2022, he was a postdoctoral research associate in signal processing for 5G and Beyond Networks at the Wolfson School of Mechanical, Electrical, and Manufacturing Engineering, Loughborough University, UK. He has continued enhancing the RIS-SDR testbed for RF sensing and wireless communication systems. He has participated in fieldwork at the University of Nottingham's Jubilee campus and Sturgate Airfield, UK, for the testing of passive RF sensor systems for drone detection and ranging.