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About

Monika Roznere is a robotics researcher specializing in underwater perception, autonomous navigation, and aquatic robot systems. Her work addresses some of the most technically demanding challenges in marine robotics, particularly developing low-cost, reliable sensing solutions for visually complex underwater environments. Roznere's most influential contribution, "Underwater Monocular Image Depth Estimation using Single-beam Echosounder" (2020, 24 citations), pioneered a real-time depth estimation methodology by fusing monocular camera imagery with single-beam sonar data — a creative solution to the prohibitive cost of traditional underwater sensing hardware. This work laid the foundation for her subsequent research on collision-free underwater navigation using domain randomization, which has garnered 14 citations since 2023. Her research extends beyond individual robots to multi-agent systems, exploring cooperative underwater mapping with teams of autonomous vehicles. She has also contributed to environmental applications through water quality monitoring systems and advanced 3D scene reconstruction using photometric stereo techniques. Most recently, her SeePerSea dataset (2025) represents a significant community resource, offering the first publicly labeled multimodal perception dataset for autonomous surface vehicles, compiled over four years of fieldwork. Collectively, her portfolio reflects a researcher bridging fundamental perception challenges with real-world aquatic deployment.