: He earned his Bachelor of Engineering (B.Eng.) in Electrical and Electronic Engineering from University College London (UCL) in 2021. During his tenure at UCL, he was recognized as a Laidlaw Scholar.
Co-author of "Dop-NET: a micro-Doppler radar data challenge" published in IET Electronics Letters , providing the robotics community with standard open-source datasets to train advanced gesture-recognition systems.
This public link is valid for 7 days and shares a thread, including any personal information you added. This link or copies made by others cannot be deleted. If you share with third parties, their policies apply. Can’t copy the link right now. Try again later. richard capraru
is a prominent researcher in the fields of robotics, autonomous vehicles, signal processing, and AI cybersecurity, currently affiliated with the International Research Center for Neurointelligence (IRCN) at the University of Tokyo. His groundbreaking work primarily addresses the critical safety bottlenecks of self-driving perception systems. By investigating how autonomous sensory pipelines fail under adverse environmental conditions—and how these vulnerabilities can be exploited by malicious threat actors—Capraru has positioned himself at the cutting edge of AI-driven automotive safety and robust embodied intelligence.
Richard Capraru is a researcher and engineer specializing in , 3D object detection , and machine learning . He has published significant work on micro-Doppler radar databases, such as the Dop-NET project , and explores deep learning applications for automotive and sensing industries. : He earned his Bachelor of Engineering (B
. Currently affiliated with University College London (UCL) and Nanyang Technological University (NTU) Singapore, his work bridges the gap between signal processing and advanced deep learning. Laidlaw Scholars Network Advancements in Gesture Recognition
Investigating how these sensors perceive environments, particularly in adverse weather conditions like rain. This public link is valid for 7 days
: Injecting realistic physical weather distortions into clear point clouds to broaden the model’s exposure.
Richard Capraru’s published works chart a clear progression from broad physical sensor attacks to targeted, complex environmental exploits: 1. Adversarial Sensor Attacks on LiDAR Perception