M. Petrou

About

M. Petrou is a leading researcher at the intersection of artificial intelligence and sustainable waste management, with a primary focus on real-time object detection for construction and demolition waste (CDW). Their most influential work, a 2023 study with 95 citations, systematically evaluates state-of-the-art deep learning methods—comparing single-stage versus two-stage detectors—to enable accurate, high-speed waste localization and classification. This research is foundational to the development of successful waste-sorting robots, directly addressing the pressing need for automated recycling in the construction industry. By benchmarking models for real-time performance, Petrou has provided critical insights that bridge computer vision and environmental engineering. Their contributions are central to advancing smart waste management systems, demonstrating how deep learning can drive sustainability. With a growing citation impact, Petrou’s work is widely recognized for its practical applications in robotics and circular economy initiatives, marking them as a key innovator in AI-driven environmental technology.

Research Focus

Key Achievements

Top Papers

1. 1
   Real-time construction demolition waste detection using state-of-the-art deep learning methods; single–stage vs two-stage detectors

   95 citations · 2023
2. 2
   Real-Time Construction Demolition Waste Detection Using State-of-The-Art Deep Learning Methods; Single – Stage vs Two-Stage Detectors

   4 citations · 2023

Key Collaborators

Contact & Links