HIDA CIFAR Summer School on Data Science & ClimateIn-Person Event

Jun 30, 2025, 4:00 PM → Jul 4, 2025, 6:00 PM Europe/Berlin

HIDA Hub (Helmholtz-Gemeinschaft, Anna-Louisa-Karsch-Straße 2, 10178 Berlin)

HIDA CIFAR Summer School on Data Science & Climate

Dive into the Crossroads of Data Science, AI, and Climate

Join us for an immersive and interdisciplinary Summer School on Climate Research and Remote Sensing bringing together young researchers, professionals, and students eager to tackle global climate challenges using innovative data-driven approaches.

Please note that you do not need to work in climate research to attend this summer school, we are explicitly looking for a diverse and interdisciplinary group of participants!

Date: June 30 – Juy 4, 2025

Locations: Berlin at the HIDA Hub (Helmholtz-Gemeinschaft, Anna-Louisa-Karsch-Straße 2, 10178 Berlin) & Helmhotz Centre for Geosciences (Telegrafenberg, 14473 Potsdam)

Description

Together, CIFAR and the Helmholtz Information & Data Science Academy (HIDA) are planning an in-person summer school for graduate and postgraduate students on the theme of Data Science for Climate, using data science and new technologies to support interdisciplinary research. Students will have the opportunity to dive into the crossroads of data science, AI, climate research, and in particular remote sensing with sessions on different methodologies and domain-specific applications. Our program offers a unique blend of theoretical foundations, hands-on experience, and collaborative learning.

What to Expect?

 

• Expert-Led Sessions: Engage with renowned scientists through keynotes, panel discussions, and interactive lectures.
• Hands-On Data Exploration: Work with a real-world dataset from the Helmholtz Centre for Geosciences (GFZ), applying remote sensing and feature detection to extract meaningful insights.
• Collaborative Group Project: Tackle an assignment in small, interdisciplinary teams using GFZ’s dataset, fostering problem-solving and teamwork.
• Practical Training: Learn from specialists in courses and workshops
• Networking & Career Insights: Connect with experts and fellow participants from diverse fields, expanding your research and career opportunities.

Find more details in the timetable, which is continuosuly updated! 

Speakers

Please find more information about our speakers and their research interests here!

	Ariel L. Furst (MIT)		Mike Sips  (GFZ)
	Ann Gregory (University of Calgary)		Sigrid Roessner     (GFZ)
	Maximilian Gelbrecht (PIK)		Stefan Bauer (Helmholtz AI)
	Peer Nowack (KIT)		Wolfgang Graf zu       Castell - Ruedenhausen      (GFZ)

 

Who can participate?

Participants must be PhD students or postdoctoral fellows either affiliated with Helmholtz or as a student of a CIFAR program member. The Summer School will include equal participation from Helmholtz students and CIFAR program trainees.

For Helmholtz spots, applications from the six Helmholtz Information & Data Science Schools - MUDs, HIDSS4Health, MarDATA, HDS-LEE, HEIBRIDS, DASHH - will be given priority. 

How to apply:

To apply for one of the 15 seats allocated to Helmholtz, please go to "Apply now" to apply for participation in the HIDA CIFAR Summer School. Admission notifications will be sent out in the beginning of May. We strongly advise to wait with your travel arrangements until then. 

Application deadline has passed!

Questions?

Please contact us: hida-courses@helmholtz.de

 

Mon, June 30

5:30 PM → 7:00 PM Meet- up & Networking Session

Tue, July 1

8:30 AM → 9:00 AM Arrival at HIDA Hub

9:00 AM → 9:30 AM Welcome and Introductions

9:30 AM → 10:30 AM Earth System Models and AI - Can they work together?

Comprehensive Earth System Models (ESMs) are the key tools to model the dynamics of the Earth system and its climate, and in particular to estimate the impacts of increasing atmospheric greenhouse gas concentrations in the context of anthropogenic climate change. ESMs couple general circulation models (GCMs) of ocean and atmosphere with models of land surface processes, hydrology, ice, vegetation, atmosphere and ocean chemistry and carbon cycle model. Despite their remarkable success in reproducing observed characteristics of the Earth’s climate system, such as the spatial patterns of the increasing temperatures of the last century, there remain many great challenges for state-of-the-art Earth System Models such as the representation of extreme events, the multistability of components and the reduction of climate uncertainties in the models.

The recent years saw the advance of purely data-driven AI models. In Earth System Science, we have now AI weather models such as GenCast, Aurora or Pangu Weather that are competitive with process-based weather models. Despite their remarkable success in weather forecasting, they are ultimately limited on the longer time scales and scenarios we need for climate projections.

Can we still make use of AI models to address some of the aforementioned challenges in ESMs? In this talk, we will get an initial glimpse into how ESMs work, and what both the potentials and challenges are when we want to integrate AI approaches into these models.

Speaker: Maximilian Gelbrecht (PIK)

10:30 AM → 11:00 AM Coffee Break

11:00 AM → 12:00 PM Machine Learning to Advance Climate Science

Global climate change projections, such as those from the Coupled Model Intercomparison Project phase 6 (CMIP6), are still subject to substantial modelling uncertainties. These uncertainties limit our ability to fully assess future climate risks and to effectively inform policy. At the same time, running high-resolution, global climate models remains computationally intensive, posing further challenges.

In this talk, I will highlight three key ways in which machine learning (ML) can help advance climate science:
(a) using observational constraints, i.e. to constrain uncertainty in CMIP6 projections on the basis of high-dimensional relationships in Earth observations,
(b) developing ML parameterizations of complex Earth system processes that can be both more accurate and computationally efficient than traditional parameterizations or explicit process representations, and
(c) building fast AI-driven emulators of climate models to enable rapid exploration of a variety of future scenarios.

I will emphasize the importance of addressing core challenges such as extrapolation in a changing climate system and understanding causal relationships, which are central to consider when working with purely data-driven ML models.

Speaker: Peer Nowack (KIT)

12:00 PM → 1:00 PM The Importance of Data Standardization for Effective Implementation of CleanTech

As new technologies are introduced to support the clean energy transition, questions of their efficiency often arise. Evaluating such technologies based on data reported without established standards makes even direct comparisons between them akin to comparing apples and oranges. We will discuss case studies focused on the challenges associated with data comparisons for battery technologies as well as electrocatalysis. We will then compare these reports to the standardized reporting for photovoltaics, which is often promoted as the ‘gold standard’ of testing and data reporting.

Speaker: Ariel L. Furst (MIT)

1:00 PM → 2:00 PM Lunch

2:00 PM → 3:30 PM Roundtable discussion. Pursuing an Academic Career

Featuring keynote speakers from the School, this roundtable discussion will discuss pursuing a career in academia, the practice of interdisciplinary research, and provide practical advice for early-career researchers. The panel will share their experiences in academia, collaboration across disciplines, and insights on navigating an academic journey.

Speakers: Ann Gregory (University of Calgary), Ariel L. Furst (MIT), Peer Nowack (KIT), Stefan Bauer (Helnholtz AI), Wolfgang zu Castell (GFZ)

3:30 PM → 4:00 PM Coffee Break

4:00 PM → 5:00 PM Mentoring session

Wed, July 2

8:30 AM → 9:30 AM Transfer Berlin - Potsdam

9:30 AM → 10:00 AM Arrival and welcome

10:00 AM → 11:00 AM Exploring Virus Roles in Climate Change Through Genomics and Data Science

Viruses are the most abundant biological entities on Earth and are ubiquitous across ecosystems, from oceans and soils to the atmosphere, and play critical roles in regulating microbial communities and biogeochemical cycles. As climate change accelerates, understanding the ecological functions of viruses becomes increasingly important. This talk will examine how genomics and data science converge to uncover the roles of viruses in climate-related processes. We'll explore methods such as viral metagenomics (viromes), machine learning, and ecological modeling to identify viral genomes and investigate viral contributions to biogeochemical cycling, microbial interactions, and ecosystem resilience. By using these approaches, we aim to shed light on the hidden influencers of our planet’s climate system.

Speaker: Ann Gregory (University of Calgary)

11:00 AM → 12:30 PM Guided Tour Telegrafenberg

Speaker: Ludwig Grunwaldt (GFZ)

12:30 PM → 2:00 PM Lunch

2:00 PM → 3:00 PM Introduction to Remote Sensing

Remote Sensing Research at GFZ aims at establishing remote sensing as a core methodology towards better understanding of Earth system dynamics. For this purpose, the full range of available remote sensing data acquired by satellites, airborne and ground based systems is used for area-wide mapping at different spatial and temporal scales. For this purpose, novel bio- and geo-physical information products are derived and a variety of computer-based methods is developed for their analytical exploitation. The goal is the spatiotemporal characterization of Earth's surface properties related to a large variety of application fields, such as observation of landscape and vegetation development, impacts of climate change and natural disasters and effects of human land use.

Speaker: Sigrid Roesnner (GFZ)

3:00 PM → 5:30 PM Workshop: Feature Detection in Remote Sensing Data

In the workshop, we follow Jim Gray’s approach to data-intensive science to answer scientific questions using Sentinel-2 satellite data. Jim Gray’s approach to data-intensive science involves four phases: capturing data, storing and managing data efficiently, exploring data through statistical and computational analysis, and finally visualizing and communicating results. The workshop thoroughly examines each phase and discusses practical methods with participants using widely adopted Python libraries. The hands-on activities focus on characterizing and monitoring wildfire activity in California. While the workshop focuses on this specific use case, participants can use Gray’s approach in future projects as a reusable template for answering a wide range of questions with Sentinel-2 data.

Speaker: Mike Sips (GFZ)

5:30 PM → 6:30 PM Transfer Potsdam - Berlin

Thu, July 3

8:30 AM → 9:00 AM Arrival at HIDA Hub

9:00 AM → 10:00 AM Causality as an Inductive Bias in AI for Science

Deep neural networks have achieved outstanding success in many tasks ranging from computer vision, to natural language processing, and robotics. However, even models trained on internet scale data pale in their ability to understand the world around us, as well as continuously adapting to new tasks or environments. One prevailing approach is to train on massive, internet-scale datasets to cover diverse distributions, while an alternative focuses on leveraging inductive biases to improve generalization. This talk will explore causality as an inductive bias in neural networks, examining its potential to enhance robustness and generalization, particularly in AI for Science applications including inference of gene regulatory networks or materials discovery.

Speaker: Stefan Bauer (Helnholtz AI)

10:00 AM → 10:30 AM Technical Set-up (Optional)

10:30 AM → 12:00 PM Group Work Phase 1

Assignment: Feature Detection in Remote Sensing Data

12:00 PM → 1:30 PM Lunch

1:30 PM → 3:00 PM Group Work Phase 2

Assignment: Feature Detection in Remote Sensing Data

3:00 PM → 3:30 PM Coffee Break

3:30 PM → 5:00 PM Group Presentations

5:00 PM → 6:00 PM Farewell and Networking

Fri, July 4

9:00 AM → 9:30 AM Arrival at HIDA Hub

9:30 AM → 10:00 AM Walk / Transfer BIMSB

10:00 AM → 11:30 AM Tour: Berlin Institute for Medical Systems Biology (MDC-BIMSB)

10:00 am -10:30 am Ralf Streckwall (Head of the MDC Planning & Construction Department): MDC-BIMSB tour with focus on climate-friendly construction
10:30 am -10:45 am Break on the rooftop terrace
10:45 am -11:15 am Dagmar Kainmüller: Helmholtz Foundation Model Initiative & AqQua - building a foundation model on images from diverse aquatic environments
11:15 am -11:30 am Q&A and goodbye

11:30 AM → 12:00 PM Walk / Transfer HIDA Hub

12:00 PM → 12:30 PM Goodbye