In 2015, I was the youngest ever to graduate in my major at the University of Helsinki (UH) - My doctoral dissertation dealt with physically based vegetation remote sensing, focusing on developing ground reference methods and validating different global satellite-based vegetation products in a boreal region. After I completed my doctoral dissertation, I had short research visit in USA (Duke university). Following 1.5-yr I continued to work at the UH, during which I extended my expertise into processing and applying airborne laser scanning data for quantifying forest canopy structures. During my years in UH, I participated in teaching remote sensing courses and leading GIS-practicals. Autumn 2016 I received postdoc position from the NIBIO (Norwegian Institute of Bioeconomy research), in a project that targeted towards developing methods for accounting forest management impacts in different land surface model (LSM) simulations employing prescribed landcover information. I developed a forest classification scheme and related landcover product for enhancing the description of managed Fennoscandic forests in different LSMs using Scandinavian forest inventory data. In addition, I refined the ‘time invariant optical properties’ -table that is used in LSM. I moved back to Finland mid-2019 and started working at the Aalto University Geoinformatics -section where I focused on themes of remote sensing of forest understory, forest landcover classification, and land surface phenology. After that (9/2021) opportunity emerged to expand my competence to forest biodiversity research at the UH, where I processed a landcover map series to allow applying “ELITE-method” for forest biodiversity-analysis in Finland between 2000-2018, and created a simulator which extends the temporal window of ELITE-simulations until 2040 for analysing the impacts of alternative forest related biodiversity-policy decisions. On 10/2022 I took up for a new challenge at the UH, that employs running a process-based forest growth model for developing improved parameterizations for the European Forestry Dynamics Model (EFDM).