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Workshop: Machine Learning and Data Management for Earth Observation

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

09:00 - 09:45 Keynote   Dr. Manil Maskey,  AI Lead, NASA Optimizing Earth Sciences Research and Applications with Data-Centric, AI-Integrated and Collaborative Approach
09:45 - 10:30 Keynote Noel Gorelick, PhD, Chief Extraterrestrial Observer, Google Sustainable Futures: Planetary Scale Applications in Sustainability with AI and EO Data
10:30 - 11:00  Coffee Break       
11:00 - 11:45 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
11:45 - 12:20 Spotlight Dr. Johannes Jakubik, IBM Research Foundation Models for Earth Observation and Weather Modeling
12:20 - 13:20 Lunch Break    
13:20 - 14:05 Keynote Prof. Dr. Ribana Roscher, University Bonn / Forschungszentrum Jülich Beyond Heatmapping: On the Benefit of Explainable Machine Learning for the Agricultural and Environmental Sciences
14:05 - 14:50 Keynote Prof. Dr. Konstantinos Karantzalos, National Technical University of Athens Sensing the Marine Environment with Cloud and Edge AI
14:50 - 15:20 Coffee Break    
15:20 - 16:20 Panel Discussion  Prof. Dr. Ribana Roscher, University Bonn / Forschungszentrum Jülich
Prof. Dr. Paolo Gamba, University of Pavia, Editor-in-Chief of IEEE GRSM
Dr. Nicolas Longépé, Philab Explore Office, ESA
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:

Prof. Dr. Begüm Demir 

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

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

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.