DataNinja Spring School 2023

Spring School Information

8th to 10th of May 2023, Hybrid Event; All slots for in-person attendance are already booked out. We welcome interested participants to joint virtually. Virtual registration remains open until shortly before the event. There will be a poster session on 09th of May at 15:00 PM.
DataNinja Spring School 2023
Organizers: Barbara Hammer, Ulrike Kuhl

We are excited to invite you to the 2nd Data-NInJA Spring School, which will take place from May 8th to May 10th, 2023 in hybrid mode. This year’s theme is “Trustworthy AI: Building Safe and Reliable Solutions”, and we have a fantastic line-up of speakers who will be sharing their insights on reinforcement learning, the social and ethical impact of Artificial Intelligence, with a special focus on sustainability, and causal inference in Machine Learning.

The Data-NInJA Spring School is aimed at PhD students, master students and interested researchers from the broad area of Artificial Intelligence and Machine Learning. At this event, participants will learn about latest trends and developments in trustworthy AI from leading experts in the field)

  • Prof. Virgina Dignum (Umeå University, Sweden)
  • Prof. Ann Nowé (Vrije Universiteit Brussel, Belgium)
  • Prof. Christian Igel (University of Copenhagen, Denmark)
  • Dr. Martin Riedmiller (Google DeepMind)
  • Prof. Jonas Peters (ETH Zurich)

Lectures will be complemented by tutorial style talks, geared towards providing hands-on experience and application or transfer of methods to own tasks and problems. In addition, participants will have the opportunity to showcase their own work in a virtual poster session. This is a wonderful chance for students, researchers, and practitioners to share their ideas, get feedback, and network with others in the field. We strongly encourage all attendees to consider presenting a poster.

Monday, 08.05.2023Tuesday, 09.05.2023Wednesday, 10.05.2023
9:00 – 10:30Tutorial: Multi-armed bandits
Dr. Viktor Bengs,
LMU Munich
1, 2, 3: Deep Learning for Semantic Segmentation
Prof. Christian Igel,
University of Copenhagen
Data-efficient RL Agents – how to build and why they matter
Dr. Martin Riedmiller,
10:30Coffee BreakCoffee BreakCoffee Break
11:00 – 12:30Causality
Prof. Jonas Peters,
ETH Zurich
Responsible AI: From Principles To Action
Prof. Virgina Dignum,
Umeå University
A Brief Tutorial on Geometric Methods in Robot Learning
Dr. Noémie Jaquier,
Karlsruhe Institute of Technology
15:00 – 16.30Reinforcement learning in ChatGPT, Robotics, and AI agents
Dr. Andrew Melnik,
KI-Starter, Uni Bielefeld
Virtual poster session,
17:00 – 18.30Aspects of Trustworthy Reinforcement Learning
Prof. Ann Nowé,
Vrije Universiteit Brussels
Biosignal-Adaptive Cognitive Systems
SAIL Lecture
Prof. Tanja Schultz, University of Bremen

Details on the Lectures

Monday, 08.05.2023

Tutorial: Multi-armed bandits, Viktor Bengs – 9:00

Causality, Prof. Jonas Peters – 11:00

Reinforcement learning in ChatGPT, Robotics, and AI agents, Dr. Andrew Melnik – 15:00

Aspects of Trustworthy Reinforcement Learning, Prof. Ann Nowé – 17:00

Tuesday, 09.05.2023

1, 2, 3: Deep Learning for Semantic Segmentation, Prof. Christian Igel – 9:00

Responsible AI: From Principles To Action, Prof. Virginia Dignum – 11:00

Biosignal-Adaptive Cognitive Systems, Prof. Tanja Schultz – 17:00

Wednesday, 10.05.2023

Data-efficient RL Agents – how to build and why they matter, Dr. Martin Riedmiller – 9:00

A Brief Tutorial on Geometric Methods in Robot Learning, Dr. Noémie Jacquier – 11:00


All slots for in-person attendance are already booked out. We welcome interested participants to joint virtually. Advance registration is required via the following link:

At registration, you will need to indicate whether you plan to submit a poster.

Important Dates

  • until April 14 th , 2023, 00.00h CET: Abstract submission deadline for the virtual poster presentation and the KAI Travel Grant
  • until April 21st , 2023, 00.00h CET: Poster acceptance notification

Poster Session

The virtual poster session will be held in We look forward to hearing about your current work, be it planned, just finished, or already published. To qualify for the the poster session (and the chance to win the 2023 DataNinja Poster Prize), please

  1. indicate that you want to present a poster during the registration process, and
  2. submit a short extended abstract of up to two pages to, until April 14th , 2023, 00:00h CET (note: for female in-person attendees who would like to apply for the KAI Travel Grant, also attach a CV, more information below)

Contributions will be reviewed and selected by the organizers. All workshop contributions will appear as online proceedings on our webpage.

Kunoichi in AI (KAI) Travel Grant

The Kunoichi in AI (KAI) Travel Grant is a program designed to support female attendees who wish to participate in person in the Data-NInJA Spring School. The grant provides financial assistance to cover travel and accommodation expenses, allowing more female up-and-coming scientisits to attend and benefit from this event.

To be eligible for the grant, applicants must identify as female and submit a poster for presentation at the Spring School. In addition, they must have a demonstrated interest or background in AI. Registration to the Spring School is mandatory for application.

To apply fort he KAI Travel Grant, please

  1. specify that you “hereby apply for the KAI Travel Grant“ within the body of the mail submitting the extended poster abstract
  2. also submit a CV together with the extended poster abstract

The organization committee reviews and evaluates each application based on several criteria. The KAI Travel Grant is an excellent opportunity for women to network with other professionals, learn about the latest developments in trustworthy AI, and gain exposure to new ideas and perspectives in their field.

Recipients of the (KAI) Travel Grant will be notified shortly before the event.

Expenses for travel and accommodation will be reimbursed (after the event) according to the specifications of the LRKG NRW.