[PlanetKR] Call for courses ESSAI 2023 - 1st European Summer School in Artificial Intelligence
magdalena.ortiz at umu.se
Fri Dec 2 15:27:32 UTC 2022
24-28 July 2023
*CALL FOR COURSE PROPOSALS*
The 1st European Summer School in Artificial Intelligence - ESSAI 2023 24-28 July, 2023 at the University of Ljubljana, Faculty of Computer and Information Science, Ljubljana, Slovenia
24 Jan 2023: Course Title submission deadline (mandatory)
31 Jan 2023: Final submission
28 Feb 2023: Notification
The European Summer School in Artificial Intelligence (ESSAI) is a new annual summer school held under the auspices of the European Association for Artificial Intelligence (EurAI). The ambition of ESSAI is to become the central meeting place for students and young researchers in Artificial Intelligence to discuss current research and share knowledge.
ESSAI 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. The format of ESSAI is analogous to the European Summer School in Logic, Language and Information (ESSLLI) which has been running since 1989. Courses will consist of five 90 minute sessions, offered daily (Monday-Friday) in a single week, to allow students to develop in-depth knowledge of a topic.
The first ESSAI will be held in Ljubljana, Slovenia in between the 24th and 28th of July 2023. ESSAI 2023 aims to attract around 400 participants from all parts of Europe, as well as from North and Latin America, and Asia.
TOPICS AND FORMAT
ESSAI aims to cover all subdisciplines of AI and the interactions between them.
Proposals for courses at ESSAI 2023 are invited in all areas of Artificial Intelligence, including but not limited to the following:
* Agent-based and Multi-agent Systems (MAS)
* Ethics, Legal Issues, Explainable and Trustworthy AI (XAI)
* Knowledge Representation and Reasoning (KR)
* Natural Language Processing (NLP)
* Neuro-Symbolic Learning and Reasoning (NeSy)
* Planning & Strategic Reasoning (PLAN)
* Reinforcement Learning (RL)
* Robotics (ROB)
* Search & Optimization (SO)
* Supervised and Unsupervised Learning (ML)
* Vision (VIS)
Each course will consist of five 90 minute lectures, offered daily (Monday-Friday) in a single week.
While foundational courses will typically focus on one subarea of AI, introductory and advanced courses are encouraged to present a broader perspective on AI, and should be of interest beyond one specific area.
Each proposal should fall under one of the following categories.
* FOUNDATIONAL COURSES *
Foundational courses present the basics of a research area to students with no prior knowledge in that area. They should be at an elementary level, without prerequisites in the course's topic, though possibly assuming a level of general scientific maturity in the relevant discipline. They should enable researchers from related disciplines to become comfortable with the fundamental concepts and techniques of the course topic, thereby contributing to the interdisciplinary nature of our research community.
* INTRODUCTORY COURSES *
Introductory courses are central to ESSAI's mission. They are intended to introduce a research field to students, young researchers, and other non-specialists, and to foster a sound understanding of its basic methods and techniques. Introductory courses should enable researchers from related disciplines to become competent in the course topic. Introductory courses that are cross-disciplinary may presuppose general knowledge of the relevant disciplines.
* ADVANCED COURSES *
Advanced courses are targeted primarily at graduate students who wish to acquire an understanding of current research in a field of Artificial Intelligence.
To be considered, course proposals should closely adhere to the following guidelines:
Course proposals can be submitted by no more than two lecturers, and courses must be presented by lecturers who submitted the proposal. All lecturers must possess a PhD or equivalent degree by the submission deadline for course proposals.
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.
Proposals must be submitted in PDF format via:
and include all of the following:
a. Personal information for each proposer: Name, affiliation, contact address, email, homepage (optional)
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)
Expected level and prerequisites
Appropriate references (e.g. textbooks, monographs, proceedings, surveys)
d. Information about the proposer(s) and course:
Whether the course will appeal to students outside of the main discipline of the course
Proposer(s)’s experience of delivering courses in an intensive one-week interdisciplinary setting
Evidence that the proposer(s) is an excellent lecturer
To keep participation fees to a minimum, all the instructional and organizational work of ESSAI is performed on a completely voluntary basis. However, the registration fees of organizers and instructors will be waived, and travel and accommodation expenses will be reimbursed up to a level which will be communicated along with the proposal notification. ESSAI can only guarantee reimbursement for at most one course lecturer, and can not guarantee full reimbursement of travel costs for lecturers from outside of Europe. The organizers of ESSAI would appreciate any help in reducing the School's expenses by seeking partial or complete coverage of travel and accommodation expenses from other sources.
By Jan 24, 2023:
Proposers must submit on EasyChair at least the name(s) of the lecturers(s), the ESSAI area+course level and a short abstract.
By Jan 31, 2023:
Submission must be completed by uploading a PDF with the actual proposal as detailed above.
Please submit your proposals to
Aleksander Sadikov (University of Ljubljana)
Vida Groznik (University of Primorska, University of Ljubljana)
Sašo Džeroski (Jožef Stefan Institute)
Jure Žabkar (University of Ljubljana)
Magdalena Ortiz (Umeå University), chair
Sašo Džeroski (Jožef Stefan Institute), local program co-chair
Brian Logan (University of Aberdeen), associate chair
Area chairs will be announced on the school website
EurAI Board Representative
Giuseppe De Giacomo (Sapienza University of Rome)
(Maria Magdalena Ortiz de la Fuente)
Associate Professor for Knowledge Representation and Reasoning
Department of Computing Science
magdalena.ortiz at umu.se<mailto:magdalena.ortiz at umu.se>
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