Dr. Vishwakarma's Doctoral Triumph: Advancing Human Activity Sensing with Radar Technology

Dr. Vishwakarma earned her PhD from the Indraprastha Institute of Information Technology in Delhi, India, in 2020, specializing in radar systems and signal processing, particularly for detecting, classifying, and imaging human activity in challenging through-the-wall conditions. Her doctoral research was distinguished by several top-tier publications and two student paper awards.

July 2022
Postdoctoral Milestones: Dr. Vishwakarma's Impactful Research in RF Sensing at UCL

Following her PhD, Dr. Vishwakarma worked as a research fellow on the EPSRC-funded OPERA project at University College London (UCL) from February 2020 to July 2022. During this time, she played a key role in developing both the hardware and software for RF sensing technology focused on ambient assisted living applications, such as fall detection. Her collaborative efforts with teams from the University of Bristol and Cambridge led to groundbreaking publications in Nature Scientific Data

Two Best Paper Awards

IEEE Radar Challenge 2022

Aug 2022
Lecturer | Innovator
Joining University of Southampton: Dr. Vishwakarma's New Chapter in AI-Assisted Radar Technology

In August 2022, Dr. Vishwakarma joined the Digital Health and Biomedical Engineering (DHBE) group at the University of Southampton as a Lecturer in ECS, where her focus is on advancing AI-assisted radar-based human monitoring solutions by addressing challenges related to hardware compatibility, data accessibility, technology awareness, and user attitudes.

SimHumaLator Breakthrough: Dr. Vishwakarma's Pioneering Simulator for Enhanced Human Activity Recognition

Dr. Vishwakarma ‘s most noteworthy contribution has been the creation of a motion-capture-driven human radar simulator, SimHumaLator, which has been rigorously validated and publicly released for the community to use. Her vision extends further, and she plans to expand its capabilities to encompass the intricate nuances of facial expressions and detailed finger motions alongside the main body postures, making it a valuable tool for Sign Language recognition. To enhance the realism of the synthetic radar signatures, PI has developed novel approaches based on Generative Adversarial Networks (GANs) and significantly improved these systems’ human activity recognition (HAR)  accuracy and reliability.

Scholarly Impact: Dr. Vishwakarma's Prolific Contribution to Sensing Technology Research

Dr. Vishwakarma has authored more than 30 research papers, which have been presented at esteemed conferences in the sensing community, including the IEEE Radar Conference, GLOBECOM, and ICC. Her contributions also extend to leading journals such as Nature and multiple IEEE Transactions. Dr. Vishwakarma’s contributions to the scientific community are extensive. She has held editorial roles, such as Lead Guest Editor for an IET special issue and Associate Editor for the IET Radar, Sonar & Navigation, and IET Electronics Letters journals. She also serves as a Technical Reviewer for a range of influential journals and key international conferences, including IEEE Internet of Things Journal, IEEE TAES, IEEE TGRS, IEEE TRS, IEEE ICC, IEEE GLOBECOM.