Julia Tan

I am a machine learning engineer from Sydney, passionate about AI for biodiversity conservation. My background is in Mechatronics Engineering (Space major) at the University of Sydney, having previously completed my Honours thesis at NASA Jet Propulsion Laboratory in California. My research focused on a self-supervised machine learning approach to robotic perception and mobility, developed for an autonomous lunar rover planning to explore the farside of the moon. Prior to joining the Australian Museum Herpetology team, I have worked as a machine learning engineer in a variety of applications, including wearable neurotechnology, distributed computer vision, and consumer robotics. At the Australian Museum, I am currently working on applying machine learning methods to the FrogID project, aiming to achieve automatic species identification on the calls recorded with the FrogID app. Outside of work, I spend my time hiking and birdwatching, as well as making electronic music and DJing.

• Tan, J. & Rowley, J.J.L. (2025). Scaling Frog Monitoring with FrogID: A Robust Classification Pipeline for Citizen Science Using Bioacoustic Foundation Models. Proceedings of the 39th Conference on Neural Information Processing Systems (NeurIPS 2025). full text
• Tan, J., Senanayake, R., & Ramos, F. (2022). Renaissance Robot: Optimal Transport Policy Fusion for Learning Diverse Skills. 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pp. 7052-7059. full text