Mark Philip Philipsen

Aalborg University, Danish Technological Institute

Papers

Total Citations

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About

Mark Philip Philipsen is a researcher at the forefront of applying artificial intelligence and robotics to critical infrastructure and industrial automation. His primary research areas include computer vision for sewer inspection, human-robot collaboration, and the use of deep learning for environmental monitoring. Philipsen’s most notable contribution is his work on automating sewer pipe assessment, where he developed 3D sensor analysis and semi-supervised autoencoder models to overcome the limitations of slow, subjective manual video inspections. His 2021 paper, "3D Sensors for Sewer Inspection: A Quantitative Review and Analysis," has garnered 38 citations, reflecting its impact on helping utilities optimize maintenance schedules and save billions. Additionally, his 2022 study on autoencoders for water level modeling addresses the challenge of sparse labeled data, further advancing automated infrastructure monitoring. Beyond sewer systems, Philipsen explores safe human-robot interaction, using virtual reality to evaluate perceived safety and predictability in collaborative meat processing—a step toward socially accepted robots in dynamic environments. His work bridges practical engineering and cutting-edge AI, offering scalable solutions for aging infrastructure and next-generation industrial collaboration.