[DL] ESSAI 2025 CALL FOR COURSE PROPOSALS - extended deadline

[Manolis Koubarakis]

(apologies for multiple postings)

ESSAI 2025 CALL FOR COURSE PROPOSALS - extended deadline


The 3rd European Summer School on Artificial Intelligence - ESSAI 2025

June 30 to July 4, 2025

Bratislava, Slovakia


https://essai2025.eu/ <https://essai2025.eu/>


IMPORTANT DATES:

January 8, 2025 (AoE): Full course proposal submission

January 31, 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 January 8, 2025 (AoE): Proposer(s) should upload a PDF with the full 
course proposal as detailed above.


By January 31, 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 
<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
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