To battle these severe cyber-physical risks, Dr. Capraru’s engineering research concentrates heavily on defense resilience. His works, such as "Overcoming catastrophic forgetting in radar and LiDAR object detection in rain via layer freezing and data augmentation," offer real-time neural network patches. By restricting weight adaptation to specific core sensor-processing layers and applying smart synthetic data augmentation, machines can sustain their perception accuracy across vastly different climates without needing completely fresh datasets. Seminal Publications and Contributions
The formal beginning of his high-tech career can be traced to London, at , one of the world’s leading research universities. In 2021 , Capraru earned his Bachelor of Engineering (B.Eng.) degree in Electrical and Electronic Engineering from UCL. During his time at UCL, he published his first research paper and began to establish his academic identity in the field of radar technology. richard capraru
When neural networks are optimized to handle clear weather, retraining them to recognize objects in rain often causes them to "forget" how to operate safely in sunshine. Dr. Capraru solved this paradox through advanced training methodologies utilizing: To battle these severe cyber-physical risks, Dr
: Training deep learning perception networks to understand the baseline signature of rain or fog, making anomalous laser injections stand out. During his time at UCL, he published his