Upcoming events

 
Lecture

KCDS Fellows present their research - KCDS Talks - February 2025

Thursday, 20 February 2025, 16:00-17:30
Hybrid: TRIANGEL Studio @Kronenplatz and Zoom

The KIT Graduate School Computational and Data Science (KCDS) at KIT Center MathSEE is excited to present a special edition of the KCDS Talks in February, where KCDS Fellows will showcase their cutting-edge research. This event offers a glimpse into the innovative work being done by the next generation of computational and data scientists.

 

Join us to hear from four talented fellows as they present their fascinating research topics:

 

  • Gabriel Mejia Ruiz (KIT SCC)
    "Trainability of Data-Driven Quantum Models"
    Gabriel will explore the challenges and possibilities of training quantum models using data-driven approaches and discuss their implications for of quantum computing.

 

  • Louise Kluge (KIT SCC)
    "Efficient Bayesian Inference in Cosmological Simulations: A Challenge in Uncertainty Quantification"
    Louise will delve into how Bayesian inference can be applied to large-scale cosmological simulations, particularly focusing on methods to address uncertainty quantification.

 

  • Lisa Leimenstoll (KIT STAT)
    "Causality in Extremes: Exploring the General Case of Different Tails"
    Lisa will present her research on extreme value theory, particularly focusing on estimating causal relationships in extreme events.

 

  • Lilly Osburg (KIT SCC)
    "Exploitation of Humanities Data for Big Data Analysis"
    Lilly will explore how data from the humanities can be exploited for large-scale analysis using big data techniques, shedding light on interdisciplinary research opportunities.

 

Following the talk, there will be a discussion with the speakers, offering attendees the opportunity to ask questions and engage in conversation about the topic. The session will be hosted by Lilly Osburg and Lukas Frank.

 

Snacks and Drinks & Networking Opportunity: After the event, there will be food provided, offering an excellent opportunity to network with the speakers and other attendees. Make the most of this chance to connect and discuss ideas with fellow researchers and professionals.

 

Whether you're a student, researcher, or simply curious about the latest trends in computational science, this event will provide valuable insights into diverse and impactful research areas.

 

Join us in person or via Zoom – the event is free and open to all without prior registration.

Speaker
Louise Kluge, Lisa Leimenstoll, Gabriel Mejia Ruiz, Lilly Osburg

KIT
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

Past Events

KCDS background
Recent Advances in Kernel Methods for Neural Networks

Deep Learning Workshop (Oct 5-6, on-site at TRIANGEL.space)

info and registration
KCDS Summer School 2023
KCDS Summer School 2023

Sep 18-20, 2023 at KIT

Info and registration
Outstretched hand holding a muffin with one candle in front of a confetti background
KCDS Fellows present + KCDS 1st birthday party - KCDS Talk - June 2023

KCDS Fellows present: Elevator Pitches on PhD projects and previous scientific work + KCDS 1st Birthday Party on June 27, 2023, 13:00-14:00

more
Dr. John Alasdair Warwicker
"A Unified Framework For Clustering And Regression Problems Via Mixed-integer Linear Programming" - KCDS Talk - May 2023

Dr. John A. Warwicker (IOR), May 23, 2023, 13:00-14:00h

more
Johannes Bracher
"Forecasts in Epidemiology" - KCDS Talk - April 2023

Dr. Johannes Bracher (ECON), April 25, 2023, 13:00-14:00h

more
Cihan Ates
"How the brain learns and why adaptive models matter" - KCDS Talk - March 2023

Dr. Cihan Ates (ITS), March 28, 2023, 13:00-14:00h

more
Uwe Ehret
"Basics of Information Theory" - KCDS Talk - February 2023

PD Dr.-Ing. Uwe Ehret (IWG), Feb 28, 2023, 13:00-14:00h

more
KCDS/GRACE 'Pcess609/stock.adobe.com'
Data and Models in Climate and Environmental Sciences

KCDS X GRACE Crossover Workshop (Dec 2022, on-site)

more