[DL] ESSAI 2025 Last Call for Course Proposals - European Summer School on AI 2025

[Ortiz de la Fuente, Maria Magdalena]

(apologies for multiple postings)
ESSAI 2025 CALL FOR COURSE PROPOSALS

The 3rd European Summer School on Artificial Intelligence - ESSAI 2025
June 30 to July 4, 2025
Bratislava, Slovakia

https://essai2025.eu/

IMPORTANT DATES:
December 8, 2024: Course preliminary details (mandatory)
December 15, 2024: Full course proposal submission
January 26, 2025: Notification of acceptance or rejection

ESSAI SUMMER SCHOOLS
ESSAI 2025 is the third edition of the annual summer school on AI held under the auspices of the European Association for Artificial Intelligence (EurAI).

ESSAI 2025 will provide an interdisciplinary setting in which courses are offered in all areas of Artificial Intelligence and also from wider scientific, historical, and philosophical perspectives. ESSAI is a central meeting place for students and young researchers in Artificial Intelligence to discuss current research and share knowledge.

The first edition of  ESSAI was held in Ljubljana, Slovenia, and the second one in Athens, Greece. Both editions were very successful and received excellent feedback from the student and lecturer participants. We look forward to a third edition of ESSAI, which we believe will be  very successful as well.

TOPICS AND FORMAT OF COURSES
ESSAI aims to cover subdisciplines of AI and the interactions between them. Proposals for courses at ESSAI 2024 are invited in all areas of Artificial Intelligence, including but not limited to the following:
* Autonomous Agents  and Multi-agent Systems (MAS)
* Causality and Causal Learning (CL)
* Ethical, Legal and Social Aspects of AI (ELS)
* Foundation Models (FM)
* Knowledge Representation and Reasoning (KR)
* Learning Theory (LT)
* Natural Language Processing (NLP)
* Neuro-Symbolic Learning and Reasoning (NSLR)
* Planning & Strategic Reasoning (PLAN)
* Reinforcement Learning (RL)
* Robotics (ROB)
* Safe, Explainable and Trustworthy AI (SET)
* Search & Optimization (SO)
* Supervised and Unsupervised Learning (ML)
* Vision (VIS)
* Human-In-The-Loop AI  (HLAI)
* AI for Social Good (A4SG)
* Quantum Machine Learning (QML)

Each course will consist of five 90-minute lectures offered daily (Monday-Friday) in the week the school takes place.

COURSE CATEGORIES
Each proposal should fall under one of the following two categories.

*Introductory Courses*
Introductory courses are intended to introduce a research area of AI to students, young researchers, and other non-specialists and to foster a sound understanding of its 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 presuppose general knowledge of the related disciplines.

*Advanced Courses*
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.

COURSE PROPOSAL GUIDELINES
To be considered, course proposals should closely adhere to the following guidelines.

Courses must be presented by lecturers who submitted the proposal. For courses with more than two lecturers, the role of each lecturer should be clearly explained and justified in the proposal.

Course proposals should explicitly state the intended course category. 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.

Submitted proposals should include all of the following:
a. Contact information for each proposer: Name, affiliation, address, email, web page
b. General proposal information: Title, category
c. Information about the course content:
* Abstract of up to 150 words
*  Motivation and description (up to two pages)

  *
Tentative outline
  *
Expected level and prerequisites
  *
Appropriate references (e.g., textbooks, monographs, proceedings, surveys)
  *
Whether the course will appeal to students outside of the main area of the course.

d. 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.

The course proposals will be reviewed by a Program Committee covering all the research areas presented above.

PARTICIPATION
To keep registration fees to a minimum, all ESSAI's instructional and organizational work is performed completely voluntarily. However, the registration fees of organizers and instructors will be waived. In addition and where appropriate and possible, ESSAI will seek to partially reimburse travel and accommodation expenses associated with delivering a course. If lecturers can cover their travel and accommodation expenses from other sources, this is greatly appreciated.


SUBMISSION INFORMATION
By December 8,  2024: Proposers must submit on Microsoft CMT the name(s) of the lecturers(s), the course title, the ESSAI area targeted, the course level, and a short abstract.

By December 15, 2024: The submission must be completed by uploading a PDF with the full course proposal as detailed above.

By January 24, 2025, Proposer(s) will be notified whether their proposal has been accepted or not.

SUBMISSION PORTAL
Please submit your proposals as a single PDF file to
https://cmt3.research.microsoft.com/User/Login?ReturnUrl=%2FESSAI2025

ESSAI 2025 ORGANIZERS
General Chair
Vida Groznik
University of Ljubljana

Program Chairs
Manolis Koubarakis
National and Kapodistrian University of Athens

Fabrizio Silvestri
Sapienza University of Rome

Local Chair
Peter Drotár
Technical University of Kosice

ESSAI Steering Committee Members
Giuseppe De Giacomo (Chair, EurAI Board representative)
University of Oxford

Brian Logan
University of Aberdeen & Utrecht University

Magdalena Ortiz
Technical University of Vienna










-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://mailman.zih.tu-dresden.de/pipermail/dl/attachments/20241205/715ac51c/attachment-0001.htm>