Event Calendar

 
Workshop

What Will it Take to Succeed at Research? Taking Reproducibility to Action for Transformative AI-and Data-enabled Scientific Research

Tuesday, 21 January 2025, 9:00-17:00
Triangel Studio (building 05.20 at Kronenplatz)

In this interactive workshop, Victoria Stodden invites the KIT community, especially early career researchers, to create ideas and proposals for facilitating research that is data-, compute-, or AI-enabled. The goal is to formulate a draft set of recommendations for accelerating research, focusing on shared and open workflows and reproducibility of results. We will workshop a "reproducible pipeline" with either real examples of the work you are currently doing, or prototype examples. We will identify reproducibility barriers you are facing and then 1) validate or repudiate the ideas from the plenary talk and 2) use this as a springboard to formulate a set of recommendations emerging from the workshop.

The workshops will build on ideas that will be introduced during the plenary talk by Victoria Stodden on January 20th, but the events will be stand-alone - if you can't attend the talk, you will still be able to participate in the workshop.

Register until January 14, 2025!

Costs/ Payment
Participation is free of charge
Speaker
Prof. Victoria Stodden

University of Southern California
Organizer
Angela Hühnerfuß
KIT Graduate School Computational and Data Science (KCDS)
KIT-Center MathSEE
Karlsruhe
Mail: kcds ∂does-not-exist.kit edu
https://www.kcds.kit.edu
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Upcoming and Recent Events

View from the Hohlohturm in the Black ForestHarke, CC BY-SA 3.0 , via Wikimedia Commons
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A signpost pointing to "Past" and "Future" Hadija on Unsplash
Timeline

Find an overview of past events in our timeline.

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Highlights

Group photo KCDS Summer School 2026
KCDS Summer School on Graph Neural Networks 2026

We had a blast at the 2026 KCDS Summer School, with participants from all over the world and sessions covering both fundamental concepts and practical applications of Graph Neural Networks (GNNs). Combined with social activities, it was a great week! The summer school took place Sep 21-25, 2026 at KIT Campus South.

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CDS Runners - running as a team at 12th KIT MeisterschaftUwe Ehret
CDS Runners @ 12th KIT Meisterschaft! (July 4, 2026)

The CDS Runners team ran like the wind at the 12th KIT Meisterschaft, a 10km fun run at KIT Campus South and, thanks to the fastest four runners in the team, came in as team 13 of 59! Congratulations!

Visualization of a stochastic PDE
Pathways into Mathematics of SPDEs: A Workshop for Young Researchers 2026

The workshop was co-organized by doctoral researchers from HGS MathComp (Heidelberg) and KCDS and provided a smooth introduction to a challenging, yet highly relevant topic: Stochastic partial differential equations in applied mathematics. It took place from March 9-11, 2026 in Heidelberg.

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About KCDS

Concept of the graduate school KCDS
KIT Graduate School Computational and Data Science (KCDS) is a graduate school at KIT Center MathSEE that offers an interdisciplinary training program for doctoral researchers in the field of model-driven and data-driven computational science.
In this unique program, doctoral researchers will be able to conduct an interdisciplinary research project that revolves around computational methods such as mathematical models, simulation methods and data science techniques, all the while building bridges between mathematical sciences and an applied SEE discipline (science, economics and engineering).
Addressing global challenges, the school provides a wide variety of topics, from meteorological ensemble forecasting to machine learning in elementary particle physics.
At KCDS, doctoral researchers have one supervisor from the mathematical sciences and one from the applied discipline. They are part of a dynamic community and participate in the school’s interdisciplinary training program, including hands-on training in small groups, summer schools, networking events and hackathons/datathons.
Thinking simulations and data together, we are ready to conquer the data-driven challenges of tomorrow!

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