Dr Milto Miltiadou is a researcher interested in the advancement of algorithms for forest monitoring. She completed her EngD at University of Bath, UK and the Remote Sensing group, Plymouth Marine Laboratory, UK. She worked on the detection of dead standing Eucalypt trees for managing biodiversity in Australia, efficient data structures for managing LiDAR during 3D polygon model creation and time-series SAR data analysis for understanding phenological changes of Cypriot forests. She is proficient in C++, python, R, computer graphics, image processing, machine learning, visualisations, co-registration and interpretation of multi-sensory data. Experience in both academia and industrial innovation was achieved through her international placements that includes two forestry companies: Carbomap (UK) and Interpine Group Ltd (NZ). She is a reviewer at high-impact well-established journals: Remote Sensing of the Envirnment, MDPI Remote Sensing, Sensors and Applied Sciences. Her manuscript was acknowledged as a distinguished contribution by Ladies of Landsat and also included in the Most Notable Articles of the MDPI Remote Sensing Journal for December 2020 - February 2021. She is an Artic code Vault Contributor of 2020 Github Archive Program with her open source software DASOS (https://github.com/Art-n-MathS/DASOS) being selected for inclusion in the program.