Completed his Ph.D. in Electrical and Electronic Engineering in 2026 under the prestigious Singapore International Graduate Award (SINGA). His doctoral work was largely carried out in tandem with the Institute for Infocomm Research (I²R) under Singapore's Agency for Science, Technology and Research (A*STAR).
Participated in summer terms and leadership programs at the Hong Kong University of Science and Technology (HKUST) and the University of Southern California (USC). Key Research Areas
Proved ghost object insertion using 8.8x fewer points by leveraging rainy atmospheric degradation. richard capraru
His research on this topic was featured in the IEEE Vehicular Technology Magazine in 2026. Context in Autonomous Vehicle Security
If you are looking for information about a different person named Richard Capraru, or if you can provide more context (e.g., in which industry or field they work), I can help you find more specific details. Dr. Jian-Gang Wang | Author - SciProfiles Completed his Ph
Developed a collaborative benchmark dataset for micro-Doppler signatures, aiding low-cost gesture and motion recognition tracking.
Explore his latest AI security projects at the . Share public link Participated in summer terms and leadership programs at
His studies proved that modern, low-cost Continuous Wave (CW) radar modules could effectively substitute larger, complex radar systems for short-range movement tracking. 2. Tackling the "Adverse Weather" Problem in AVs
He expanded his global perspective and research acumen as an alumnus and visiting student at several world-class institutions: Hong Kong University of Science and Technology Peking University The University of Tokyo
Capraru's work analyzes the specific vulnerabilities posed by these conditions, aiming to provide insight into how to make AI perception systems more resilient against malicious environmental manipulation. Significance in Autonomous Security
A key theme running through Capraru's work is the fusion of with the physical world through sensors . His research is centred on teaching machines how to "see," "hear," and navigate through complex and often hostile environments.