Member of the Division "Federated Systems and Data"
Forschungszentrum Jülich GmbH
Institute for Advanced Simulation (IAS)
Jülich Supercomputing Centre (JSC)
Gebäude 14.14 / Raum 3001
Warum und woran ich forsche
Surbhi Sharma received the B.Tech degree in electronics and communication engineering from Amity University, India, in 2015, and the M.Sc degree in Geo-information science and Earth Observation with a specialization in Geo-informatics jointly from the Indian Institute of Remote Sensing, Indian Space and Research Organization (ISRO), India, and the Faculty of Geo-information Science and Earth Observation (ITC), University of Twente, the Nethelands, in 2018. She is a member of the “High Productivity Data Processing” (HPDP) research group at the Jülich Supercomputing Centre, Germany. She is currently pursuing the Ph.D. degree in computational engineering at the University of Iceland. She is also a member in Simulation and Data Lab Remote Sensing (EuroCC- National Competence Center for HPC and AI in Iceland). Her research interest lies in scalable machine learning and deep learning methods for remote sensing applications, with a particular focus on advanced deep transfer learning methods using modern High Performance Computing (HPC) systems.