KIT Campus South, NTI Lecture Hall (building 30.10)
Richard Samworth, University of Cambridge
The workshop for registered participants is complemented by a keynote by Richard Samworth to which everyone interested is invited, no registration necessary!
For more than two centuries, least-squares regression has been a cornerstone of statistical practice, while classical nonparametric smoothing methods have long served as standard tools for analysing complex data. In this workshop, we will revisit these methods from a modern perspective and ask: Are we making the best possible use of them? Recent work in statistical theory by Richard Samworth and others shows that these familiar methods can often be improved by incorporating additional structural information, such as shape constraints or properties of the underlying error distribution.
Richard Samworth will explore recent developments in distributionally adaptive statistical methods. Richard Samworth is Professor of Statistical Science and Director of the Statistical Laboratory at the University of Cambridge. A Fellow of the Royal Society, he is the recipient of numerous distinctions, including the COPSS Presidents' Award, the David Cox Medal and the Royal Statistical Society Guy Medal in Silver in 2025. His research has made fundamental contributions to nonparametric statistics, statistical learning theory, and high-dimensional methodology, particularly in shape-constrained estimation and adaptive nonparametric procedures. A defining feature of his research is the combination of rigorous theoretical guarantees with methods designed to be computationally efficient and practically applicable.
Richard Samworth will present recent work with Elliot H. Young and Rajen D. Shah on "Outrigger local polynomial regression“. A preprint of the paper is available on arXiv https://arxiv.org/abs/2603.11282.
This two-day on-site workshop takes place on November 26 & 27, 2026.
Content
“Do I have a plan for how to achieve my PhD? How do I define priorities and draw up a schedule? What is required for the process of writing?” A PhD project lasting a number of years will raise many questions requiring individual and tailor-made solutions.
This workshop will help you develop your individual strategy ensuring that your planning will both be effective and efficient in achieving your goal. You will not only learn more about self-management methods, but will also identify and explore external resources such as dealing with the expectations of others and receiving active support from your supervisors.
Registration
Please visit the KCDS intranet portal to register for this course.
For non-members of KCDS:
Booking for non-members starts on October 19, 2026.
In order to be able to book the course, a KCDS guest/non-member account is necessary.
If you don't have an account yet, you can register here: Create a KCDS account to book courses
Once your account is activated by a KCDS administrator, you will be able to book the course.
This two-day on-site workshop takes place on November 26 & 27, 2026.
Content
“Do I have a plan for how to achieve my PhD? How do I define priorities and draw up a schedule? What is required for the process of writing?” A PhD project lasting a number of years will raise many questions requiring individual and tailor-made solutions.
This workshop will help you develop your individual strategy ensuring that your planning will both be effective and efficient in achieving your goal. You will not only learn more about self-management methods, but will also identify and explore external resources such as dealing with the expectations of others and receiving active support from your supervisors.
Registration
Please visit the KCDS intranet portal to register for this course.
For non-members of KCDS:
Booking for non-members starts on October 19, 2026.
In order to be able to book the course, a KCDS guest/non-member account is necessary.
If you don't have an account yet, you can register here: Create a KCDS account to book courses
Once your account is activated by a KCDS administrator, you will be able to book the course.
KIT Centers MathSEE and KCIST are jointly hosting “AI Perspectives” at Triangel Space: The goal of this format is to foster scientific exchange among our active but very spread-out AI community at KIT.
AI Perspectives will take place on Thursday, February 4, 2027 from 13:00-16:00h at Triangel (Kronenplatz), Karlsruhe.
Register here: https://indico.kit.edu/event/5857/
The workshop will feature talks by
Jan Kieseler, professor at the Institute for Experimental Particle Physics (ETP),
Anne Meyer, professor for Data Science in Mechanical Engineering at the Institute for Information Management in Engineering (IMI) and
Christian Wressnegger, professor at the Institute of Information Security and Dependability (KASTEL)
as well as a networking opportunity with a poster session. We would like to encourage doctoral researchers to show their research related to AI and submit a poster! For KCDS Fellows, poster contributions will be credited with 1 CP („cutting-edge knowledge“).
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.
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!
The AI Community at KIT is active, but spread-out: KIT Centers MathSEE and KCIST aim to bring AI researchers together in this joint workshop. Join us at Triangel Space for inspiring talks by Benjamin Unger, Maria Francesca Spadea and Tobias Käfer and show your AI-related research at our poster session.
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.
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.
A worthwhile journey to KIT Institute of Statistics: Talks by Sebastian Engelke, Linda Mhalla, Gabriele Messori, Petra Friederichs gave insights into state-of-the-art research in statistics and data science for climate and weather extremes. The workshop took place on November 20, 2025 at the Campus South outpost in Blücherstraße.
A friendly place in the Black Forest, sunny autumn weather, good food, lively (scientific) discussions, board games and activities ranging from powerpoint karaoke to trampoline jumping were the ingredients of a lovely KCDS Retreat this year! It took place from November 10-12, 2025.
Short courses and an interactive tutorial on Neural Operators and Gaussian Processes, along with a poster session and lots of opportunities for networking with other researchers - that was the KCDS Summer School 2025! It took place from August 27-29, 2025 at KIT Campus South.
KIT International Excellence Fellow Prof. Victoria Stodden invited the KIT community, especially early career researchers, to create ideas and proposals for facilitating research that is data-, compute-, or AI-enabled - taking reproducibility to action! The workshop took place on January 21, 2025 at Triangel Studio.
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!
+49 721 608-47748
angela huehnerfuss ∂does-not-exist.kit edu
www.kcds.kit.edu/