Jessica Sanson

Led groundbreaking research on Wi-Fi-based sensing, developing a patented approach enabling commercial PCs to detect the position and velocity of nearby users in real-time. Pioneered multimodal gesture recognition and hand tracking models combining wireless and camera inputs, designing and training transformer-based vision models for 3D gesture recognition.

Responsible for the research and development of innovations in sensing-related technologies, serving as a crucial link between the radar and perception/ML teams. Developed machine learning algorithms for detecting partial and total sensor blockage, overseeing all development stages until successful product implementation.

Developed a comprehensive perception system based solely on radar, with proposed algorithms for instantaneous velocity disambiguation, ego-motion, cluttering, tracking, SLAM, radar-based occupancy grid mapping and freespace. Developed algorithms for coherent distributed aperture radar, with proof of concept development with real data for coherent beamforming between isolated radars/sensors.

Developed signal processing techniques for MIMO multicarrier technology (OFDM-type waveforms) for sensing and communications systems for automotive applications. Proposed sensor fusion algorithms based on raw data aimed to increase resolution in a vehicular network.

Conducted research on network technologies for mobile communications. Implemented solutions in C++.

Activities and societies: Published 10 first-author papers, with results validated in laboratory experiments at 24 GHz.

Developed signal processing techniques for MIMO multicarrier technology (OFDM-type waveforms) for sensing and communications systems for automotive applications. Proposed sensor fusion algorithms based on raw data aimed to increase resolution in a vehicular network. Developed an Kalman filtering tracking algorithm based on distributed radar sensor data, where both active sensors (radars) and passi

Specialized in Signal Processing, focusing on advanced concepts and applications within the field. Funded through a merit-based full-ride scholarship, demonstrating academic excellence.

Completed a comprehensive curriculum in Electrical Engineering, gaining foundational knowledge and practical skills. Received an honorable mention for the best graduation average, highlighting strong academic performance.