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ESSAI 2026 : 4th European Summer School on Artificial Intelligence (ESSAI 2026)

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Link: https://essai2026.eu
 
When Jul 6, 2026 - Jul 10, 2026
Where Vienna
Submission Deadline Dec 3, 2025
Notification Due Jan 21, 2026
Categories    artificial intelligence
 

Call For Papers

# Call for Course Proposals

## 4th European Summer School on Artificial Intelligence (ESSAI 2026)
## 2nd International Summer School on Bilateral AI
## 6-10 July 2026, Vienna, Austria
## https://essai2026.eu

*General Information*

ESSAI is the annual summer school on AI held under the auspices of the European Association for Artificial Intelligence (EurAI), and in 2026 it will encompass the 2nd International Summer School on Bilateral AI. ESSAI is the largest school of broad AI in Europe, offering courses in all areas of Artificial Intelligence and from a wide range of perspectives. Its thematic scope is analogous to major AI conferences like ECAI, IJCAI and AAAI, covering all AI subdisciplines and their interconnections. ESSAI is a central meeting place for AI students and young researchers to deepen their knowledge, broaden their perspectives, discuss current research, and build connections with other researchers.

*Location*

The fourth edition of ESSAI will be held in Vienna, a city where history and innovation walk side by side. Home to world-renowned universities and research centers, Vienna has inspired great thinkers for centuries—think of Erwin Schrödinger, Lise Meitner, Sigmund Freud, Kurt Gödel, Ludwig Wittgenstein, or the Vienna Circle. Today, Vienna continues to welcome students, scholars, and curious minds from around the globe. Vienna awaits you with world-class culture, groundbreaking science, and cozy coffee houses—all in a city celebrated for its quality of life.

*Invitation to Submit a Course Proposal*

We welcome leading AI researchers to submit course proposals for inclusion in this school, which provides a uniquely stimulating teaching environment. We expect to welcome around 400 students with diverse backgrounds, who can choose courses from parallel tracks in order to deepen their understanding of familiar AI disciplines, dive into new ones, and discover new interdisciplinary research areas combining different AI approaches. The lecturers of the selected courses will be invited to join the school’s academic and social program and enjoy an exciting summer week in beautiful Vienna.

*Important Dates*

* December 3 (AoE), 2025: Deadline for submitting a course proposal
* January 21, 2026: Notification of acceptance of course proposals
* July 6-10, 2026: Summer school

*Topics*

ESSAI aims to cover a broad range of AI subdisciplines and the interactions thereof. Proposals for courses are invited in all areas of AI, including but not limited to the following:
* Autonomous Agents and Multi-agent Systems (MAS)
* AI for Social Good (A4SG)
* Causality and Causal Learning (CL)
* Computer Vision (VIS)
* Ethical, Legal and Social Aspects of AI (ELS)
* Foundation Models (FM)
* Human-In-The-Loop AI (HLAI)
* Knowledge Representation and Reasoning (KR)
* Learning Theory (LT)
* Machine Learning (ML)
* Natural Language Processing (NLP)
* Neural Networks (NN)
* Neuro-Symbolic Learning and Reasoning (NSLR)
* Planning & Strategic Reasoning (PLAN)
* Quantum Machine Learning (QML)
* Reinforcement Learning (RL)
* Robotics (ROB)
* Safe, Explainable and Trustworthy AI (SET)
* Search & Optimization (SO)
* Uncertainty in AI (UAI)

*Special Themes*

ESSAI 2026 will feature two special themes. We welcome in particular course proposals that align with the following topics:

**Bilateral AI**, which aims at developing the foundation for broad AI systems with interacting sub-symbolic and symbolic components.

**Digital Humanism**, an interdisciplinary research field that studies the complex interplay between digital technologies and humans.

These themes are closely related to two research priorities being pursued in Vienna and Austria: the Bilateral AI Cluster of Excellence (https://www.bilateral-ai.net/) and the Digital Humanism initiative (https://caiml.org/dighum/).

*Course Categories*

We invite courses that will consist of **4 lectures of 90 minutes (one lecture per day, 6 hours of teaching in total)** in the week the school takes place (alternative course durations can be considered if they are well-motivated). Every course proposal should belong to one of the following two categories:

* **Introductory courses** are intended to introduce an AI research area to students, young researchers, and other non-specialists and to foster a sound understanding of basic methods and techniques. Such courses should enable researchers from related disciplines to develop some comfort and competence in the topic considered. Introductory courses in a cross-disciplinary area may assume general knowledge of the related disciplines.

* **Advanced courses** are targeted primarily to graduate students who wish to acquire a level of comfort and understanding of current research in an area of AI.

While introductory courses will typically focus on one subarea of AI only, advanced courses are encouraged to present a broader perspective on AI, and they should be of interest beyond a single specific area. The course proposals will be reviewed by a Program Committee covering all the research areas presented above, which will select the courses to be taught by the school.

*Submission Instructions*

A course proposal consists of the following:

(A) An abstract of approximately 150 words (aimed at Program Committee members)

(B) A single PDF document containing:

1. Contact information for each proposer (name, affiliation, address, email, web page)
2. Information on the course content (up to two pages):
* Course title and category (Introductory or Advanced)
* Motivation and description of course content
* Tentative outline and teaching concept (including a distribution of teaching material over the 4 x 90 min lectures)
* Expected student level and prerequisites. Proposals for introductory courses should indicate the intended level, for example, as it relates to standard textbooks and monographs in the area. Proposals for advanced courses should specify the prerequisites in detail.
* Target audience, including whether and how the course will appeal to students beyond the main subarea of the course
* If applicable, information on where the course has already been taught and in which venue
* Relevant references (e.g., textbooks, monographs, proceedings, surveys, a link to lecture slides if already available)
3. Information about the proposer(s):
* Short CVs of the proposer(s)
* Evidence that the proposer(s) are excellent lecturers with relevant teaching experience, particularly in delivering intensive interdisciplinary courses
* Courses should normally have no more than two lecturers. For courses with more than two lecturers, the role of each lecturer should be explained

Your course proposal should be submitted using the CMT system (the link is available at https://essai2026.eu).

*Contact*

Questions regarding this call can be sent to the email address essai2026-pc-chairs@list.tuwien.ac.at

*Participation*

All lecturers named in the proposal are expected to teach in person at the school. To keep registration fees to a minimum and facilitate the participation of more students, all instructional and organisational work for ESSAI is carried out on a voluntary basis. The registration fees of instructors will be waived. In addition, and where appropriate and possible, ESSAI will seek to partially reimburse travel and accommodation expenses; typically, the support can only be given to one lecturer per course. If lecturers can cover their travel and accommodation expenses from other sources, this is greatly appreciated.

#### Organizers

*General Chair*

Vida Groznik, University of Ljubljana

*Local Organizers*

* Kees van Berkel, TU Wien
* Thomas Eiter, TU Wien
* Jan Maly, WU Wien
* Magdalena Ortiz, TU Wien
* Marta Sabou, WU Wien
* Leyli Slavata, TU Wien

*Program Chairs*

* Luc De Raedt, KU Leuven and Örebro University
* Mantas Šimkus, TU Wien

*ESSAI Steering Committee*

* Giuseppe De Giacomo, University of Oxford
* Vida Groznik, University of Ljubljana
* Brian Logan, University of Aberdeen & Utrecht University
* Magdalena Ortiz, TU Wien

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