Juan Sandino

Dr. Juan Sandino is a Research Fellow at the QUT Centre for Robotics, affiliated with the School of Electrical Engineering and Robotics at Queensland University of Technology (QUT). He holds a BEng (Mechatronics) from Nueva Granada Military University and a PhD in Robotics and Autonomous Systems from QUT (2022). His research focuses on autonomous UAV decision-making, machine learning, and remote sensing for environmental monitoring, biosecurity, and search and rescue operations.

Education:

• PhD in Robotics and Autonomous Systems (2018–2022), QUT
• Bachelor of Engineering (Mechatronics, 2010–2015), Nueva Granada Military University
• Diploma in Project Management (2017–2018), Australian Pacific College

Research Interests:

Dr. Sandino specializes in developing drone-based solutions for environmental challenges. His work integrates autonomous systems, reinforcement learning, and hyperspectral imaging to address issues such as biosecurity threats, Antarctica's fragile ecosystems, and search and rescue missions in GPS-denied environments. His projects include UAV frameworks for planetary exploration (UAV4PE), detection of invasive species like Bitou Bush and Parthenium Weed, and real-time vegetation monitoring in polar regions.

Awards & Recognition:

• CSIRO Data61 PhD and Top-Up Scholarships (2018–2021)
• Best Team Award, QUT Centre for Robotics (2021)
• Phase 1 Finalist, OpenCV AI Competition (2021)

Projects & Grants:

He leads projects funded by the Australian Research Council (SAEF initiative) and industry partners, including aerial mapping of forests affected by pathogens, UAV-based monitoring in Antarctica, and pest risk modeling for Buffel Grass. His work emphasizes collaboration with organizations like CSIRO Data61 and Charles Sturt University.

Labs & Teams:

Dr. Sandino contributes to the Securing Antarctica’s Environmental Future (SAEF) initiative and collaborates with interdisciplinary teams at QUT’s Centre for Robotics. His research integrates robotics software (ROS, PX4), sensor instrumentation, and AI for real-world applications.