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About

Jelena Tabak is a researcher specializing in agricultural robotics, autonomous systems, and precision farming technologies, with a particular focus on applying robotic intelligence to indoor and greenhouse cultivation environments. Her work sits at the intersection of computer vision, robot autonomy, and sustainable agriculture, addressing some of the most pressing challenges in modern food production. Tabak's most influential contribution, "Structured Ecological Cultivation with Autonomous Robots in Indoor Agriculture" (2021, 23 citations), demonstrates her systems-level thinking by coordinating heterogeneous robot teams — including UAVs, UGVs, and compliant manipulators — to perform collaborative farming tasks no single robot could accomplish alone. Her work on sweet pepper harvesting perception (22 citations) highlights her expertise in developing practical computer vision pipelines for real-world agricultural deployment. She has also pioneered simulation infrastructure for agricultural robotics, creating a render-in-the-loop simulator combining ROS, Gazebo, and Blender's Cycles engine to enable realistic sim-to-real transfer for yield estimation tasks. More recently, Tabak has advanced robotic irrigation management by automating soil moisture assessment through multimodal sensing. Across her growing body of work, she exemplifies a researcher translating cutting-edge robotics into tangible solutions for sustainable, automated food production.