Richard Capraru -

His research stands out because of its focus on the unexpected intersections of these fields—such as how adverse weather can be used to expose system vulnerabilities. He demonstrates a consistent ability to identify security gaps in emerging technologies before they become mainstream.

: Injecting realistic physical weather distortions into clear point clouds to broaden the model’s exposure.

: Analyzing vulnerabilities in autonomous vehicle vision systems to understand how they might be targeted by adversarial attacks.

Capraru's research has fundamentally improved how machines interpret human movement through non-optical sensors. Low-Cost Radar Systems richard capraru

Capraru’s research spans several advanced technological domains:

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.

Before shifting fully into autonomous vehicle security, Dr. Capraru vastly expanded the open-source signal processing community's access to clean radar datasets. Alongside co-researchers from UCL and TU Delft, he developed . His research stands out because of its focus

[Adversarial Laser Emitter] ──> (Low-Power Pulse Hidden in Rain) ──> [Vehicle LiDAR Sensor] │ [Sudden Deceleration / Accident] <── (Perceives Fake Obstacle) <─────────────┘ Enhancing Autonomous Vehicle Defense Frameworks

Traditionally, rain, fog, and snow have been viewed strictly as operational hindrances that attenuate signals and reduce a sensor's effective range. However, Capraru and his fellow researchers demonstrated that these meteorological conditions actually lower the barrier of entry for bad actors. Environmental noise can mask malicious laser injections, allowing hackers to execute highly potent spoofing attacks using significantly lower power and less complex equipment than what is typically required on a clear day.

Dr. Capraru’s research career spans leading technological institutions across Europe and Asia, featuring educational and research experience at institutions including University College London (UCL) , Nanyang Technological University (NTU), and A*STAR. His background includes fellowships and research residencies at institutions like Imperial College London. Before shifting fully into autonomous vehicle security, Dr

Earned his Bachelor of Engineering (B.Eng.) in Electrical and Electronic Engineering in 2021. During his tenure, he was named a Laidlaw Scholar and contributed to foundational radar signal processing datasets.

Exploring vulnerabilities in autonomous driving, such as "LiDAR spoofing" and "ghost object attacks".

Capraru’s research primarily addresses how sensors—specifically and radar —behave in challenging real-world environments.