Month: May 2025

[rede.APPIA] DaSSWeb – Data Science and Statistics Webinar – 20 May – Aurea Grané – Robust Distances for Mixed-type Data

MC

DaSSWeb- Data Science and Statistics Webinar

Tuesday, 20 May, 14:30 (WEST)

 

Speaker

Aurea Grané

Universidad Carlos III de Madrid, Spain
Title
Robust distances for mixed-type data
Abstract
Data scientists address real-world problems using multivariate and heterogeneous datasets, characterized by multiple variables of different natures. Selecting a suitable distance function between units is crucial, as many statistical techniques and machine learning algorithms depend on this concept. Traditional distances, like classical Gower’s or Euclidean, are unsuitable for mixed-type data when underlying correlation or outlying observations are present, and often lead to suboptimal results. In this talk robust distances for mixed-type data will be explored, like robust Generalized Gower’s and robust Related Metric Scaling, as well as their performance in clustering and prediction problems.

pdf icon DaSSWeb-AureaGrane-20May2025.pdf

[rede.APPIA] DeepLearn 2025: early registration April 20

MC

Dear Colleagues,

Following the success of DeepLearn 2024, where 380 participants from 39 countries engaged with Jiawei Han, Katia Sycara, and 16 other AI experts, we are pleased to announce DeepLearn 2025, taking place July 21-25 in Maia, Portugal (https://deeplearn.irdta.eu/2025/).

This year's focus is on Large Language Models, Foundation Models, and Generative AI, complemented by lectures on agentic applications, explainable AI (xAI), real-time AI, multimodal AI, graph networks, and more. Our two distinguished keynote speakers will be Yonina Eldar and Manuela Veloso, alongside 18 leading AI experts delivering in-depth sessions (more details below).

We believe DeepLearn 2025 offers a unique opportunity to engage with top researchers and advance your expertise in AI. We would be delighted to welcome you to this event!

Best regards,
José Paulo Marques dos Santos, Luís Paulo Reis, and José Luís Reis

———- Forwarded message ———
From: IRDTA <irdta@irdta.eu>
Date: Thu, 3 Apr 2025 at 11:27
Subject: DeepLearn 2025: early registration April 20
To: <jpsantos@umaia.pt>

*To be removed from our mailing list, please respond to this message with UNSUBSCRIBE in the subject line*

———-

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12th INTERNATIONAL SCHOOL ON DEEP LEARNING
(with a 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 & University of Porto

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

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Early registration: May 19, 2025

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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 – Castlo 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:

Yonina Eldar (Weizmann institute of Science), Model Based Deep Learning: Applications to Imaging and Communications

Manuela Veloso (JPMorganChase), The Journey of Humans and AI: Insights from AI in Robotics and AI in Finance

PROFESSORS AND COURSES:

Pierre Baldi (University of California Irvine), [intermediate/advanced] From Deep Learning and Transformers to AI Risks and Safety

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

Xavier Bresson (National University of Singapore), [intermediate/advanced] Graph Transformers, Graph Generative Models and Large Language Models

Nello Cristianini (University of Bath), [introductory] Machina Sapiens – Towards More General Forms of AI

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

Samira Ebrahimi Kahou (University of Calgary), [intermediate/advanced] Explainability in Machine Learning

Elena Giusarma (Michigan Technological University), [introductory/intermediate] Machine Learning at the Frontier of Astrophysics: Simulating the Universe

Shih-Chieh Hsu (University of Washington), [intermediate/advanced] Real-Time Artificial Intelligence for Science and Engineering

Xia “Ben” Hu (Rice University), [introductory/advanced] Efficient LLM Serving: Algorithms and Systems

Lu Jiang (ByteDance & Carnegie Mellon University), [introductory/intermediate] Transformers for Image and Video Generation: Fundamentals, Design, and Innovations

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

Chen Change Loy (Nanyang Technological University), [intermediate/advanced] Harnessing Prior for Content Enhancement and Creation

Fenglong Ma (Pennsylvania State University) & Cao (Danica) Xiao (GE HealthCare), [introductory/intermediate] Transforming Healthcare and Drug Development through Multimodal AI with LLMs and Generative AI Technologies

Evan Shelhamer (DeepMind), [intermediate] Test-Time Adaptation for Updating on New and Different Data

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/sponsors/

ORGANIZING COMMITTEE:

Samuel Anjos (Maia, social networks)
Sergei V. Gleyzer (Tuscaloosa, hackathon chair)
José Paulo Marques dos Santos (Maia, local chair)
Carlos Martín-Vide (Tarragona, program chair)
Santiago Montes (Tarragona, webpage)
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 are available 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

Goreti Marreiros

ISEP | Instituto Superior de Engenharia do Porto
Rua Dr. António Bernardino de Almeida, 431
4249-015 Porto – PORTUGAL
tel. +351 228 340 500 | fax +351 228 321 159
mail@isep.ipp.pt | www.isep.ipp.pt

[rede.APPIA] AmIA@EPIA2025 – CALL FOR PAPERS

MC
[Our Apologies if you receive multiple copies of this CFP]

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CALL FOR PAPERS
 
We invite all members of the international AI research and industry communities to submit their high-quality, previously unpublished papers to:
 
Ambient Intelligence and Affective Environments
Thematic track of the 24th Portuguese Conference on Artificial Intelligence
(EPIA 2025)
October 1-3, 2025
University of Algarve, Faro, Portugal, Faro, Portugal
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This track provides a forum to discuss and present emerging topics, new projects, and ideas on how AI can contribute to the field of Ambient Intelligence.
Ambient Intelligence (AmI) is a paradigm emerging from Artificial Intelligence (AI), where computers are used as proactive tools assisting people with their day-to-day activities, increasing human experiences.
Affect and social behaviour play an important role in the development of Ambient Intelligent Environments. Consideration of aspects like emotions, mood, personality traits, and attitudes in human-computer, human-robot, and human-environment interaction, especially insofar, as they provide better or more “natural” support for humans. These environments should be aware of the people’s needs, customizing requirements and forecasting behaviours.
AmI environments may be highly diverse, such as homes, offices, meeting rooms, schools, hospitals, control centres, transport facilities, tourist attractions, stores, sport installations, or music devices, among others.
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IMPORTANT DATES
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– Paper submission deadline: May 23, 2025 (AoE)
– Notification of paper acceptance: July 4, 2025
– Camera-ready papers: July 14, 2025 (AoE)
– Conference dates: October 1-3, 2025

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TOPICS OF INTEREST
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In the thematic track on AmIA Environments we intend to bring together researchers from the different addressed fields, discussing issues under the Artificial Intelligence topics included in the context of Ambient Intelligence and Affective Environments. Researchers are welcome to present both theoretical and practical works as well as the lessons learned with their application in the varied range of domains. Emphasis will be placed on the presentation of concrete systems, discussion of implementation and development challenges, and sharing of relevant results and conclusions.
To fulfil these objectives, submissions of substantial, original, and previously unpublished work are invited in all areas of Ambient Intelligence and Affective Environments.
The topics of interest include, but are not limited to:
 
– Applications 
– Ambient Assisted Living
– Ubiquitous Computing
– Artificial Intelligence for AmI
– Intelligent Environments
– Pervasive Computing
– Context Aware Computing
– Agent & Multi-Agent Systems for AmI
– Mobile Computing 
– Sentient Computing
– e-Health
– Context Modelling
– AmI for e-Learning
– On-line Dispute Resolution
– Memory Assistant
– Computational models of emotions
– Group Emotion
– Affect and learning
– Artificial characters
– Affect and emotion recognition
 
 
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PAPER SUBMISSION
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* All papers should be submitted in PDF format through the EPIA 2025 EasyChair submission page.
* The papers should be prepared according to the Springer LNAI format, with a maximum of 12 pages. However, you should consider any track-specific details in your submission.
* Accept papers will be included in the conference proceedings as long as at least one author is registered in EPIA 2025 by the early bird registration deadline.
* EPIA 2025 proceedings are indexed in Thomson Reuters ISI Web of Science, Scopus, DBLP, and Google Scholar.
 
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ORGANIZING COMMITTEE
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Manuel Rodrigues, University of Minho, ALGORITMI \ LASI,  PT
Luís Conceição, Polytechnic Institute of Porto, PT
Sara Rodríguez, University of Salamanca, Spain
Peter Mikulecky, University of Hradec Kralove, Czech Republic
Goreti Marreiros, Polytechnic Institute of Porto, PT
Paulo Novais, University of Minho, ALGORITMI \ LASI , PT

Best regards,

Luís Conceição

Assistant Professor

Graphical user interface, text, application Description automatically generatedA picture containing text Description automatically generated

Rua Dr. António Bernardino de Almeida, 431

4249-015 Porto

Portugal

Phone: +351 228 340 511 (ext. 1821)

Email: msc@isep.ipp.pt

http://www.gecad.isep.ipp.pt 

 

 

Best Regards,
Luís Conceição
Assistant Professor
Department of Informatics Engineering
GECAD – Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development

ISEP | Instituto Superior de Engenharia do Porto
Rua Dr. António Bernardino de Almeida, 431
4249-015 Porto – PORTUGAL
tel. +351 228 340 500 | fax +351 228 321 159
mail@isep.ipp.pt | www.isep.ipp.pt

[rede.APPIA] LUHME@ECAI 2025 | Call for Papers: 2nd Workshop on Language Understanding in the Human-Machine Era (LUHME)

MC

Call for Papers: 2nd Workshop on Language Understanding in the Human-Machine Era (LUHME)

The LUHME 2025 workshop Language Understanding in the Human-Machine Era is part of the 28th European Conference on Artificial Intelligence, ECAI 2025 (https://ecai2025.org/).

Workshop description

Large language models (LLMs) have revolutionized the development of interactional artificial intelligence (AI) systems by democratizing their use. These models have shown remarkable advancements in various applications, such as conversational AI and machine translation, marking the undeniable advent of the human-machine era. However, despite their significant achievements, state-of-the-art systems still exhibit shortcomings in language understanding, raising questions about their true comprehension of human languages.

The concept of language understanding has always been contentious, as meaning-making depends not only on form and immediate meaning but also on context. Therefore, understanding natural language involves more than just parsing form and meaning; it requires access to grounding for true comprehension. Equipping language models with linguistics-grounded capabilities remains a complex task, given the importance of discourse, pragmatics, and social context in language understanding.

Assessing whether LLMs understand language is a doubly challenging task, as it necessitates not only grasping the intrinsic capabilities of LLMs but also examining their impact and requirements in real-world applications. While LLMs have shown effectiveness in various applications, the lack of supporting theories raises concerns about ethical implications, particularly in applications involving human interaction.

The “Language Understanding in the Human-Machine Era” (LUHME) workshop aims to reignite the debate on the role of understanding in natural language use and its applications. It seeks to explore the necessity of language understanding in computational tasks like machine translation and natural language generation, as well as the contributions of language professionals in enhancing computational language understanding.

Topics of Interest

Topics of interest include, but are not limited to:

  • Language understanding in LLMs

  • Language grounding

  • Psycholinguistic approaches to language understanding

  • Discourse, pragmatics and language understanding

  • Intent detection

  • Evaluation of language understanding

  • Human vs. machine language understanding

  • Machine translation/interpreting and language understanding

  • Multimodality and language understanding

  • Socio-cultural aspects in understanding language

  • Effects and risks of language misunderstanding

  • Manifestations of language (mis)understanding

  • Natural language understanding and toxic content

  • Ethical issues in language misunderstanding

  • Distributional semantics and language understanding

  • Linguistic theory and language understanding by machines

  • Linguistic, world, and commonsense knowledge in language understanding

  • Role of language professionals in the LLMs era

  • Understanding language and explainable AI

Ethics Statement

Research reported at ECAI and at the LUHME workshop should avoid harm, be honest and trustworthy, fair and non-discriminatory, and respect privacy and intellectual property. Where relevant, authors can include in the main body of their paper, or on the reference page, a short ethics statement that addresses ethical issues regarding the research being reported and the broader ethical impact of the work. Reviewers will be asked to flag possible violations of relevant ethical principles. Such flagged submissions will be reviewed by a senior member of the programme committee. Authors may be required to revise their paper to include a discussion of possible ethical concerns and their mitigation.

Submission Instructions

Papers must be written in English, be prepared for double-blind review using the ECAI LaTeX template, and not exceed 7 pages (not including references). The ECAI LaTeX Template can be found at https://ecai2025.org/wp-content/uploads/2025/04/ecai-template.zip. Papers should be submitted via EasyChair: https://easychair.org/conferences?conf=luhme2025

Excessive use of typesetting tricks to make things fit is not permitted. Please do not modify the style files or layout parameters. You can resubmit any number of times until the submission deadline. The workshop papers will be published in the proceedings (further information will be provided soon).

Proceedings

As in the first edition of the LUHME workshop, we intend to publish accepted papers with ACL Anthology (https://aclanthology.org/volumes/2024.luhme-1/).

Important Dates

  • Paper submission: 31 May 2025

  • Notification of acceptance: 15 July 2025

  • Camera-ready papers: 31 July 2025

  • LUHME workshop: 25 or 26 October 2025

Confirmed Invited Speakers

  • Chloé Clavel, INRIA Paris

Workshop Organizers

  • Henrique Lopes Cardoso (University of Porto, Portugal)

  • Rui Sousa-Silva (University of Porto, Portugal)

  • Maarit Koponen (University of Eastern Finland, Finland)

  • Antonio Pareja-Lora (Universidad de Alcalá, Spain)

Web Master

  • Felermino Ali (University of Porto, Portugal)

Program Committee

  • Aida Kostikova (Bielefeld University)

  • António Branco (University of Lisbon)

  • Barbara Lewandowska-Tomaszczyk (University of Applied Sciences in Konin)

  • Belinda Maia (University of Porto)

  • Bram van Dijk (Leiden University)

  • Chaya Liebeskind (Jerusalem College of Technology)

  • Efstathios Stamatatos (University of the Aegean)

  • Ekaterina Lapshinova-Koltunski (University of Hildesheim)

  • Eliot Bytyçi (Universiteti i Prishtinës “Hasan Prishtina”)

  • Federico Ruggeri (University of Bologna)

  • Lynne Bowker (University of Ottawa)

  • Nataša Pavlović (University of Zagreb)

  • Sule Yildirim Yayilgan (Norwegian University of Science and Technology)

  • Tharindu Ranasinghe (Lancaster University)

For further information, please visit https://luhme.up.pt/ or contact hlc@fe.up.pt