News

Prof. Victoria StoddenVictoria Stodden
Taking Reproducibility to Action - Workshop with Prof. Victoria Stodden (Jan 21)

KIT International Excellence Fellow Prof. 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.

Register until January 14, 2025!

Learn more and register
Symbolic picture for doctoral researchers
Call for proposals (KIT internal): DAAD Graduate School Scholarships at KCDS

We are calling researcher tandems (MATH and SEE) at KIT to submit interdisciplinary project ideas!

Deadline: January 31, 2025

Learn more (only visible in KIT intranet)

Upcoming events

 
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
Online registration
Register on the KCDS website
Online Registration

Highlights

Panel discussion with KIT Alumni at Triangel Space
Report: Career Talk with KIT Alumni 2024

From Computational and Data Science to Industry and Academia - four KIT Alumni gave insights into their jobs during a lively panel discussion on October 11, 2024 at Triangel Space.

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Group picture of the participants of the RainQuest Hackathon 2024
Report: RainQuest Hackathon 2024

The hackathon on precipitation estimation with weather radar and rain gauge data took place from October 8-11, 2024 at Triangel Studio.

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Group picture of the participants of the KCDS Workshop on Data Processing and Data Assimilation 2024Na Luo
Report: KCDS Workshop on Data Processing and Data Assimilation 2024

The workshop with Dr. Annika Oertel (IMKTRO) and Dr. Vandana Jha (SCC) took place from September 11-12, 2024 at the Mathematics building.

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KCDS Retreat 2023 - group picture
Report: KCDS Retreat 2023

The second annual KCDS Retreat took place from November 13-15, 2023 at Naturfreundehaus Kniebis in the Black Forest.

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Deep Learning workshop group picture
Report: Deep Learning Workshop 2023

The workshop with a focus on "Recent Advances in Kernel Methods for Neural Networks" took place in October 5-6, 2023 at the Triangel.

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KCDS Summer School 2023 group photo
Report: KCDS Summer School 2023

The first KCDS Summer School centered on the topic of Stochastic and Hybrid Modelling and took place at KIT Campus South, September 18-20, 2023.

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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!

Coordination Office