Prof. Dr. Begüm Demir
Prof. Dr. Begüm Demir
Research Group Lead
Begüm Demir is currently a Full Professor and the founder head of the Remote Sensing Image Analysis (RSiM) group at the Faculty of Electrical Engineering and Computer Science, TU Berlin and the head of the Big Data Analytics for Earth Observation research group at the Berlin Institute for the Foundations of Learning and Data (BIFOLD). Her research activities lie at the intersection of machine learning, remote sensing and signal processing. Specifically, she performs research in the field of processing and analysis of large-scale Earth observation data acquired by airborne and satellite-borne systems. She was awarded by the prestigious '2018 Early Career Award' by the IEEE Geoscience and Remote Sensing Society for her research contributions in machine learning for information retrieval in remote sensing. In 2018, she received a Starting Grant from the European Research Council (ERC) for her project "BigEarth: Accurate and Scalable Processing of Big Data in Earth Observation". She is an IEEE Senior Member and Fellow of European Lab for Learning and Intelligent Systems (ELLIS).
| 2018 | Recipient of the “2018 Early Career Award” presented by the IEEE Geoscience and Remote Sensing Society. |
| 2017 | Recipient of the Starting Grant from the European Research Council (ERC). |
| 2017 | Recipient of the national accreditation as Associate Professor in Telecommunications in Italy. |
- Remote Sensing
- Machine Learning
- Signal Processing
- Image Processing
- Big Data in Earth Observation
- IEEE Senior Member
- Fellow of European Lab for Learning and Intelligent Systems (ELLIS)
Devis Tuia, Konrad Schindler, Begüm Demir, Gustau Camps-Valls, Xiao Xiang Zhu, Mrinalini Kochupillai, Sašo Džeroski, Jan N. van Rijn, Holger H. Hoos, Fabio Del Frate, Mihai Datcu, Jorge-Arnulfo Quiané-Ruiz, Volker Markl, Bertrand Le Saux, Rochelle Schneider
Artificial intelligence to advance Earth observation: a perspective
Ahmet Kerem Aksoy, Mahdyar Ravanbakhsh, Prof. Dr. Demir Begüm
Multi-Label Noise Robust Collaborative Learning for Remote Sensing Image Classification
Gencer Sumbul, Jun Xiang, Begüm Demir
Towards Simultaneous Image Compression and Indexing for Scalable Content-Based Retrieval in Remote Sensing
Ahmet Kerem Aksoy, Pavel Dushev, Eleni Tzirita Zacharatou, Holmer Hemsen, Marcela Charfuelan, Jorge-Arnulfo Quiané-Ruiz, Begüm Demir, Volker Markl
Satellite Image Search in AgoraEO
Smart Sky: Transforming Earth Observation through AI
Through three engaging lectures, scientists from NASA, the Planetarium Berlin, and BIFOLD explained the significance of satellite images and modern AI techniques.
New open research positions
Join BIFOLD and collaborate with renowned experts on cutting-edge Machine Learning and Data Management research! Develop robust, trustworthy, and sustainable AI solutions with our team of international scientists.
Research from the very top
BIFOLD scientist Prof. Dr. Begüm Demir explains the benefits of using Explainable Artificial Intelligence (XAI) to enhance earth observation satellite data analysis in the Tagesspiegel TU Berlin supplement.
DA4DTE: Pioneering Satellite Data Archives with a Revolutionary Digital Assistant
Demonstrator Precursor Digital Assistant Interface for Digital Twin Earth (DA4DTE) is a project by the European Space Agency (ESA) that aims to simplify the usage of satellite data archives. A BIFOLD research group led by Prof. Dr. Begüm Demir has been pivotal in developing three of the four search engines featured in the digital assistant.
Earth Observation data for Climate Change research
Many environmental reports are based on the analysis of satellite images. BIFOLD researchers are creating AgoraEO, an infrastructure for Earth Observation (EO) data that enables federated analysis across different platforms, making modern EO technology accessible to all scientists and society, thus promoting climate change innovation worldwide.
An overview of the current state of research in BIFOLD
Since the official announcement of the Berlin Institute for the Foundations of Learning and Data in January 2020, BIFOLD researchers achieved a wide array of advancements in the domains of Machine Learning and Big Data Management as well as in a variety of application areas by developing new Systems and creating impactfull publications. The following summary provides an overview of recent research activities and successes.