Call for Fall 2024 International AI Doctoral Academy (AIDA) course proposals

Dear Al Professors, Postdocs or Senior AI researchers,

 

in the framework of the AI4Media EU project funded under the European Union’s Horizon 2020, together with the ICT48 projects ELISE, VISION, HumanE AI NET and TAILOR, we have organized the International AI Doctoral Academy (AIDA) aiming to become a reference initiative for AI education in Europe and implement mechanisms for inter-university sharing of AI educational assets at PhD-level. As part of the program, AIDA offers a series of courses on Artificial Intelligence and related fields given by distinguished lecturers.

 

We invite you to contribute to this initiative for the definition of the AIDA Fall semester program (from Sept 1st, 2024, to January 31st, 2025)

 

You can participate in the AIDA program by offering new or opening-up existing courses targeted to AIDA students* or other students worldwide according to the participation terms of your own organization. Short/Very Short course formats (5-16 hours) are typically encouraged, while semester courses, or asynchronous mode web courses will be considered as well. Accepted courses will be listed on AIDA website (https://www.i-aida.org/) and will be advertised for free with the support of AIDA dissemination channels. Proposals for courses for the AIDA Fall semester program should be sent to: Prof. Stefano Berretti stefano.berretti@unifi.it, and Ms. Efi Patmanidou epatmanidou@iti.gr  and will be evaluated by the AIDA Committee.

 

Any qualified Al Professor/Postdoc or Senior AI researcher (PhD holder) can apply to offer a course, no matter if she/he belongs to a host University that is an AIDA member or not. The course lecturer(s) and heir host University/Institution

define course fees and other course-related issues.  

 

Proposals for AIDA Courses should include (please find the AIDA Course Application Form here):

Course title:

Lecturer name & affiliation:

Host Institution:

Content and organization: Course details about the content. 1 paragraph

Level: (Undergraduate/Postgraduate)

Course Duration: Hours

Course Type: (Short/Semester/Lecture series/Seasonal School)

Participation terms: Registration fee policy for external (non-AIDA) students, e.g., free of charge or fee of ??? Euros. Special terms for AIDA students, e.g., discount 50% or free for X number of AIDA students. Add text for a) non-AIDA student registration and AIDA student registration/enrollment, as in (6) below.

Lectures plan: Days/time

Proposed schedule: Start date – End date

Language: English/Other

Modality: Online/in person

Notes: Are there exams? Details on how to successfully complete the course. 1-2 sentences.

Course Link: 

 

*AIDA students may be PhD students, post-doc researchers, possibly qualified MSc students or professionals of AIDA Members

 

Best regards,

Prof. Ioannis Pitas (on behalf of Prof. Berretti)

AIDA Chair


DeepLearn 2025

12th INTERNATIONAL SCHOOL ON DEEP LEARNING
(with special focus on Large Language Models, Foundation Models and Generative AI)

DeepLearn 2025

Porto – Maia, Portugal

July 21-25, 2025

https://deeplearn.irdta.eu/2025/

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Co-organized by:

University of Maia

Institute for Research Development, Training and Advice – IRDTA
Brussels/London

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Early registration: September 29, 2024

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SCOPE:

DeepLearn 2025 will be a research training event with a global scope aiming at updating participants on the most recent advances in the critical and fast developing area of deep learning. Previous events were held in Bilbao, Genova, Warsaw, Las Palmas de Gran Canaria, Guimarães, Las Palmas de Gran Canaria, Luleå, Bournemouth, Bari, Las Palmas de Gran Canaria and Porto.

Deep learning is a branch of artificial intelligence covering a spectrum of current frontier research and industrial innovation that provides more efficient algorithms to deal with large-scale data in a huge variety of environments: computer vision, neurosciences, speech recognition, language processing, human-computer interaction, drug discovery, biomedicine and health informatics, medical image analysis, recommender systems, advertising, fraud detection, robotics, games, business and finance, biotechnology, physics experiments, biometrics, communications, climate sciences, geographic information systems, signal processing, genomics, materials design, video technology, social systems, earth and sustainability, etc. etc.

The field is also raising a number of relevant questions about robustness of the algorithms, explainability, transparency, interpretability, as well as important ethical concerns at the frontier of current knowledge that deserve careful multidisciplinary discussion.

Most deep learning subareas will be displayed, and main challenges identified through 18 four-hour and a half courses, 2 keynote lectures, 1 round table and a hackathon competition among participants. Renowned academics and industry pioneers will lecture and share their views with the audience. The organizers are convinced that outstanding speakers will attract the brightest and most motivated students. Face to face interaction and networking will be main ingredients of the event. It will be also possible to fully participate in vivo remotely.

DeepLearn 2025 will place special emphasis on large language models, foundation models and generative artificial intelligence.

ADDRESSED TO:

Graduate students, postgraduate students and industry practitioners will be typical profiles of participants. However, there are no formal pre-requisites for attendance in terms of academic degrees, so people less or more advanced in their career will be welcome as well.

Since there will be a variety of levels, specific knowledge background may be assumed for some of the courses.

Overall, DeepLearn 2025 is addressed to students, researchers and practitioners who want to keep themselves updated about recent developments and future trends. All will surely find it fruitful to listen to and discuss with major researchers, industry leaders and innovators.

VENUE:

DeepLearn 2025 will take place in Porto, the second largest city in Portugal, recognized by UNESCO in 1996 as a World Heritage Site. The venue will be:

University of Maia
Avenida Carlos de Oliveira Campos – Castêlo da Maia
4475-690 Maia
Porto, Portugal

https://www.umaia.pt/en

STRUCTURE:

3 courses will run in parallel during the whole event. Participants will be able to freely choose the courses they wish to attend as well as to move from one to another.

All lectures will be videorecorded. Participants will be able to watch them again for 45 days after the event.

An open session will give participants the opportunity to present their own work in progress in 5 minutes. Also companies will be able to present their technical developments for 10 minutes.

The school will include a hackathon, where participants will be able to work in teams to tackle several machine learning challenges.

Full live online participation will be possible. The organizers highlight, however, the importance of face to face interaction and networking in this kind of research training event.

KEYNOTE SPEAKERS: (to be completed)

Manuela Veloso (JPMorganChase), AI, Humans, and Robots for Task Solving

PROFESSORS AND COURSES: (to be completed)

Sean Benson (Amsterdam University Medical Center), [intermediate] Digital Twins and Generative AI for Personalised Medicine

Mark Derdzinski (Dexcom), [introductory] From Prototype to Production: Evaluation Strategies for Agentic Applications

Elena Giusarma (Michigan Technological University), tba

Hayit Greenspan (Tel Aviv University), tba

Jayashree Kalpathy-Cramer (University of Colorado), [introductory/intermediate] Multimodal AI for Healthcare

Yingbin Liang (Ohio State University), [intermediate/advanced] Theory on Training Dynamics of Transformers

Evan Shelhamer (DeepMind), tba

Atlas Wang (University of Texas Austin), [intermediate] Low Rank Strikes Back in the Era of Large Language Models

Xiang Wang (University of Science and Technology of China), [advanced] Large Language Models for User Behavior Modeling: Cross-Modal Interpretation, Preference Optimization, and Agentic Simulation

Rex Ying (Yale University), [intermediate/advanced] Multimodal Foundation Models for Graph-Structured Data: Framework and Scientific Applications

OPEN SESSION:

An open session will collect 5-minute voluntary oral presentations of work in progress by participants.

They should submit a half-page abstract containing the title, authors, and summary of the research to david@irdta.eu by July 13, 2025.

INDUSTRIAL SESSION:

A session will be devoted to 10-minute demonstrations of practical applications of deep learning in industry.

Companies interested in contributing are welcome to submit a 1-page abstract containing the program of the demonstration and the logistics needed. People in charge of the demonstration must register for the event.

Expressions of interest have to be submitted to david@irdta.eu by July 13, 2025.

HACKATHON:

A hackathon will take place, where participants can work in teams to tackle several machine learning challenges. They will be coordinated by Professor Sergei V. Gleyzer (University of Alabama). The challenges will be released 2 weeks before the beginning of the school. A jury will judge the submissions and the winners of each challenge will be announced by August 25, 2025. The winning teams will receive a modest monetary prize and the runners-up will get a certificate.

SPONSORS:

Companies/institutions/organizations willing to be sponsors of the event can download the sponsorship leaflet from

https://deeplearn.irdta.eu/2025/sponsoring/

ORGANIZING COMMITTEE:

Sergei V. Gleyzer (Tuscaloosa, hackathon chair)
José Paulo Marques dos Santos (Maia, local chair)
Carlos Martín-Vide (Tarragona, program chair)
Sara Morales (Brussels)
José Luís Reis (Maia)
Luís Paulo Reis (Porto)
David Silva (London, organization chair)

REGISTRATION:

It has to be done at

https://deeplearn.irdta.eu/2025/registration/

The selection of 6 courses requested in the registration template is only tentative and non-binding. For logistical reasons, it will be helpful to have an estimation of the respective demand for each course.

Since the capacity of the venue is limited, registration requests will be processed on a first come first served basis. The registration period will be closed and the on-line registration tool disabled when the capacity of the venue will have got exhausted. It is highly recommended to register prior to the event.

FEES:

Fees comprise access to all program activities and lunches.

There are several early registration deadlines. Fees depend on the registration deadline.

The fees for on site and for online participation are the same.

ACCOMMODATION:

Accommodation suggestions will be available in due time at

https://deeplearn.irdta.eu/2025/accommodation/

CERTIFICATE:

A certificate of successful participation in the event will be delivered indicating the number of hours of academic activities. This should be sufficient for those participants who plan to request ECTS recognition from their home university.

QUESTIONS AND FURTHER INFORMATION:

david@irdta.eu

ACKNOWLEDGMENTS:

Universidade da Maia

Universidade do Porto

Universitat Rovira i Virgili

Institute for Research Development, Training and Advice – IRDTA, Brussels/London

IEEE SSCI 2025 Title Abstract Deadline This Sunday (22 September)

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IJCNN 2025: Call for Papers!

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Call for Papers
Submission Deadline: 15 January 2025
Important Dates:
15 January 2025: Regular Paper Submission
17 March 2025: Acceptance Notification
1 May 2025: Final Camera Ready Paper
The International Joint Conference on Neural Networks, (IJCNN) is the premier international conference in the area of neural networks theory, analysis and applications. Whether you are presenting your latest work, learning from experts, or networking with peers, IJCNN 2025 promises to be an unforgettable experience that will inspire and propel the AI and neural network community forward. We look forward to welcoming you in Rome!
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Topics of Interest
Papers for IJCNN 2025 will be reviewed by experts in the fields and ranked based on the criteria of originality, significance, quality, and clarity. Prospective authors are invited to submit complete papers of no more than eight (8) pages in IEEE two-column conference proceedings format. Authors should submit their papers in PDF through the online submission system, which will be available at https://2025.ijcnn.org/.
Topics of interest include but are not limited to:
  • AI for Critical Infrastructures
  • AI for Education
  • AI for Neural Engineering
  • Brain-Machine Interfaces
  • Cognitive Models
  • Collective & Ensemble Intelligence
  • Computational Neuroscience
  • Dynamic Neural Networks
  • Efficient and Tiny Neural Networks
  • Ethics and Regulation in AI
  • Generative AI Models
  • Graph Neural Networks
  • Interpretable and Explainable AI
  • Large Language Models
  • Large-Scale Neural Networks
  • Mixture of Experts
  • Modular Neural Networks
  • Neural Engineering
  • Neural Network Applications
  • Neural Networks for Sciences
  • Neuromorphic Systems
  • Neurosymbolic AI
  • Perceptual Neural Networks
  • Quantum Neural Networks
  • Reinforcement Learning
  • Representation & Reasoning
  • Reservoir & Echo-State Networks
  • Spiking Neural Networks
  • Theory of Neural Networks
  • Transformer Networks
  • Trustworthy and Reliable AI
  • Unsupervised Learning
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Conference Sponsor

Jornada de CyT y Posgrado: Depto ISI

Estimados 

En el marco de las jornadas de Ciencia, Tecnología y Posgrado invitamos a toda la comunidad UTN a participar del ciclo de charlas organizadas por el Depto.De Ingeniería en Sistemas de Información. Las mismas son abiertas, gratuitas y sin inscripción previa. 
Se adjunta el cronograma. 
👉 Lunes 23 de septiembre
👉 18:00 hs. 
👉 Aula 78
Los esperamos!
Cordialmente, Patricia  
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