Summary
Raktim Ghosh is a research and technology scientist with eight years of experience at the intersection of remote sensing, machine learning, and planetary science, currently contributing to AI-driven Earth observation projects at LIST. He completed a PhD (cum laude) at Università di Trento focused on automatic analysis of radar sounder data for the JUICE mission and has applied quantum machine learning and deep learning techniques during visits to Forschungszentrum Jülich and earlier research roles. His background spans geoinformatics, mineral mapping from hyperspectral imagery, and practical systems engineering, blending academic rigor with hands-on implementation. Based in Trentino-Alto Adige/Südtirol and pursuing cross-disciplinary work, he brings the rare combination of space mission research experience and applied disaster-monitoring AI collaborations with CERN and WFP.
8 years of coding experience
6 years of employment as a software developer
Doctor of Philosophy - PhD, Information Engineering and Computer Science, Cum Laude, Doctor of Philosophy - PhD, Information Engineering and Computer Science, Cum Laude at Università di Trento
Bachelor of Engineering - BE, Mining and Mineral Engineering, 8.39, Bachelor of Engineering - BE, Mining and Mineral Engineering, 8.39 at Indian Institute of Engineering Science and Technology (IIEST), Shibpur
MSc, Geoinformation Science and Earth Observation with specialisation in Geoinformatics, 7.67, MSc, Geoinformation Science and Earth Observation with specialisation in Geoinformatics, 7.67 at Faculty of Geo-Information Science and Earth Observation (ITC) of the University of Twente