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CfCourses: ESSAI 2025 : The 3rd European Summer School on Artificial Intelligence - ESSAI 2025, June 30 to July 4, 2025, Bratislava (Slovakia)
(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 unde
r the auspices of the European Association for Artificial Intelligence (Eur
AI).
ESSAI 2025 will provide an interdisciplinary setting in which courses are o
ffered in all areas of Artificial Intelligence and also from wider scientif
ic, historical, and philosophical perspectives. ESSAI is a central meeting
place for students and young researchers in Artificial Intelligence to disc
uss 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 exc
ellent 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-F
riday) 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 stu
dents, young researchers, and other non-specialists and to foster a sound u
nderstanding of its basic methods and techniques. Such courses should enabl
e researchers from related disciplines to develop some comfort and competen
ce in the topic considered. Introductory courses in a cross-disciplinary ar
ea may presuppose general knowledge of the related disciplines.
*Advanced Courses*
Advanced courses are targeted primarily to graduate students who wish to ac
quire a level of comfort and understanding of current research in an area o
f AI.
While introductory courses will typically focus on one subarea of AI only,
advanced courses are encouraged to present a broader perspective on AI, an
d they should be of interest beyond a single specific area.
COURSE PROPOSAL GUIDELINES
To be considered, course proposals should closely adhere to the following g
uidelines.
Courses must be presented by lecturers who submitted the proposal. For cour
ses with more than two lecturers, the role of each lecturer should be clear
ly explained and justified in the proposal.
Course proposals should explicitly state the intended course category. Prop
osals for introductory courses should indicate the intended level, for exam
ple, as it relates to standard textbooks and monographs in the area. Propos
als 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, sur
veys)
* Whether the course will appeal to students outside of the main area o
f the course.
d. Information about the proposer(s):
* Short CVs of the proposer(s)
* Evidence that the proposer(s) are excellent lecturers with relevant t
eaching experience, particularly in delivering intensive interdisciplinary
courses.
The course proposals will be reviewed by a Program Committee covering all t
he research areas presented above.
PARTICIPATION
To keep registration fees to a minimum, all ESSAI's instructional and organ
izational work is performed completely voluntarily. However, the registrati
on fees of organizers and instructors will be waived. In addition and where
appropriate and possible, ESSAI will seek to partially reimburse travel an
d 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 le
vel, and a short abstract.
By December 15, 2024: The submission must be completed by uploading a PDF w
ith the full course proposal as detailed above.
By January 24, 2025, Proposer(s) will be notified whether their proposal ha
s 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 Drotr
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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