International Workshop in Berlin
During the last decade, an ever-increasing number of satellites equipped with optical and synthetic aperture radar sensors have been launched. Advancements in satellite technology have increased the variety, amount, and spatial/spectral resolution of Earth Observation (EO) data.
The efficient processing and intelligent analysis of complex, heterogeneous EO data at a large scale holds the potential to substantially improve our understanding of the state of our planet and the changes occurring on it. Data Management and Machine Learning are the scientific and technical pillars powering the current wave of innovation in Artificial Intelligence for EO.
Program & Information
The 2-day workshop Machine Learning and Data Management for Earth Observation aims to explore the emerging methods, approaches and systems in the context of Data Management and Machine Learning for EO. In addition to keynote and spotlight talks of renowned speakers in their fields, this workshop includes poster presentations and a panel discussion exploring challenges and determining future directions in Data Management and Machine Learning for Earth Observation.
Date: March, 18. & 19. 2024
Time: 09:30 am - 05:00 pm
Location: Showroom Forum Digitale Technologien, Salzufer 15/16, 10587 Berlin
Registration: The event is open to the public. Please register here!
Preliminary Agenda
18.03.2024
| 09:00 - 09:30 | Registration & Coffee | ||
| 09:30 - 10:00 | Opening remarks | Prof. Dr. Volker Markl, BIFOLD Director Prof. Dr. Begüm Demir, BIFOLD Group Lead | |
| 10:00 - 11:00 | Keynote | Prof. Dr. Alex Szalay, Director of the Institute for Data Intensive Science, Johns Hopkins University | Science in the Era of AI |
| 11:00 - 11:30 | Coffee Break | ||
| 11:30 - 12:00 | Keynote | Dr. Pierre-Philippe Mathieu, Implementation Manager of Civil Security from Space Programme, ESA | Artificial Intelligence for Space and Rapid & Resilient Crisis Response |
| 12:00 - 12:35 | Spotlight | Assist. Prof. Dr. Hannah Kerner, Arizona State University, AI Lead at NASA Harvest | Unlocking the Potential of Planetary-Scale Machine Learning for a Sustainable Future |
| 12:35 - 13:35 | Lunch Break | ||
| 13:35 - 14:20 | Keynote | Grega Milčinski, General Manager, Sinergise | Repeatability and Reusability of ML Workflows powered by European Resources - Copernicus Data Space Ecosystem |
| 14:20 - 14:55 | Spotlight | Dr. Alejandro Coca-Castro, Alan Turing Institute | Enhancing Reproducibility in Earth Observation through Open Science Principles |
| 14:55 - 15:25 | Coffee Break | ||
| 15:25 - 16:10 | Keynote | Dr. Vitaly Feldman, Apple Research | Efficient Algorithms for Locally Private Learning with Optimal Accuracy Guarantees |
| 16:10 - 16:45 | Spotlight | Prof. Dr. Mrinalini Kochupillai, Ethics Group Lead, AI4EO Future Lab, TU München | Earth Observation, Ethics, and Data Management: Insights from the Proposed EU AI Act |
| 16:45 - 17:45 | Poster & Demo Session | Reception |
19.03.2024
| 09:30 - 10:15 | Keynote | Dr. Manil Maskey, AI Lead, NASA | Optimizing Earth Sciences Research and Applications with Data-Centric, AI-Integrated and Collaborative Approach |
| 10:15 - 11:00 | Keynote | Noel Gorelick, PhD, Chief Extraterrestrial Observer, Google | Sustainable Futures: Planetary Scale Applications in Sustainability with AI and EO Data |
| 11:00 - 11:30 | Coffee Break | ||
| 11:30 - 12:15 | Keynote | Dr. Ingo Simonis, CTIO, Open Geospatial Consortium (OGC) | SDI 3.0 or Geospatial Data Ecosystems of the Next Generation: Solutions for AI ready Systems of the Future |
| 12:15 - 12:50 | Spotlight | Dr. Johannes Jakubik, IBM Research | Foundation Models for Earth Observation and Weather Modeling |
| 12:50 - 13:50 | Lunch Break | ||
| 13:50 - 14:35 | Keynote | Prof. Dr. Ribana Roscher, University Bonn / Forschungszentrum Jülich | Beyond Heatmapping: On the Benefit of Explainable Machine Learning for the Agricultural and Environmental Sciences |
| 14:35 - 15:00 | Spotlight | Dr. Katarzyna Ewa Lewinska, HU Berlin | Spatio-Temporal Overview of Usable Landsat and Sentinel-2 Data - Opportunities and Limitations for Vegetation Monitoring |
| 15:00 - 15:30 | Coffee Break | ||
| 15:30 - 16:30 | Panel Discussion | Prof. Dr. Ribana Roscher, University Bonn / Forschungszentrum Jülich Prof. Dr. Paolo Gamba, University of Pavia, Editor-in-Chief of IEEE GRSM Assist. Prof. Dr. Hannah Kerner, Arizona State University, AI Lead at NASA Harvest Dr. Ronny Hänsch, ML Team Lead/Department SAR Technology, DLR | Opportunities and Future Directions in Machine Learning and Data Management for Earth Observation |
Workshop Organizers
Scientific coordinators:
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).
Contact: demir@tu-berlin.de
Tom Burgert is a Ph.D researcher in the Big Data Analytics for Earth Observation research group at the Berlin Institute for the Foundations of Learning and Data (BIFOLD) and Remote Sensing Image Analysis (RSiM) group at the TU Berlin.
Contact: t.burgert@tu-berlin.de
Kai Norman Clasen is a Ph.D researcher in the Big Data Analytics for Earth Observation research group at the Berlin Institute for the Foundations of Learning and Data (BIFOLD) and Remote Sensing Image Analysis (RSiM) group at the TU Berlin.
Contact: k.clasen@tu-berlin.de
Local coordinator:
Dr. Laura Wollenweber
Laura Wollenweber is Scientific Coordinator Strategy at BIFOLD and coordinates the workshop on site.
Contact: laura.wollenweber@tu-berlin.de
Funding:
This event is partially funded by the European Research Council (ERC) through the ERC-2017-STG BigEarth Project under Grant 759764.