Author: MC

[rede.APPIA] ECMLPKDD 2025: List of Available Workshops You Can Participate In

MC
————————————- List of Workshops at ECMLPKDD 2025 ————————————-
European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases – ECMLPKDD 2025 will be held in Porto, Portugal, from 15th and 19th of September of 2025
Conference website: ecmlpkdd.org/2025/
ECMLPKDD 2025 includes many workshops where participants can discuss current and emerging machine learning and data mining topics. Please check below the list of workshops we offer this year and participate!
Paper submission deadline: June 14th, 2025 (Check the web page of the workshop for up-to-date information)
——————————————————————— 9th Interactive Adaptive Learning Workshop
ial-workshop.github.io/ial2025/ ——————————————————————— Deep Learning meets Neuromorphic Hardware
sites.google.com/view/dl-meets-nh-25 ——————————————————————— Machine Learning for Cybersecurity (MLCS 2025)
mlcs.lasige.di.fc.ul.pt/ ——————————————————————— AI for Safety-Critical Infrastructures (AI-SCI)
sites.google.com/view/ai-sci-workshop/ ——————————————————————— 5th Workshop on Bias and Fairness in AI
sites.google.com/view/bias-2025-ecmlpkdd/ ———————————————————————
10th Workshop on Advanced Analytics and Learning on Temporal Data (AALTD 2025)
ecml-aaltd.github.io/aaltd2025/ ——————————————————————— MACLEAN: MAChine Learning for EArth ObservatioN
sites.google.com/view/maclean25 ——————————————————————— MLG: Mining and Learning with Graphs
mlg-europe.github.io/2025/ ——————————————————————— 2nd TempXAI Workshop for Explainable AI in Time Series and Data Streams
lamarr-institute.github.io/tempxai25/ ————————————————————– Workshop on Innovations, Privacy-preservation, and Evaluations Of machine Unlearning Techniques (WIPE-OUT 2025)
aiimlab.org/short/WIPE-OUT_2025 ————————————————————— New Frontiers in Mining Complex Patterns
nfmcpworkshop.github.io/ ——————————————————————— Machine Learning for Sustainable Power Systems (ML4SPS)
sites.google.com/view/ml4sps/ml4sps/ecml-pkdd-2025-porto?authuser=0 ——————————————————————— SoGood 2025 – 10th Workshop on Data Science for Social Good
sites.google.com/view/sogood-2025/ ——————————————————————— International Workshop on Learning from Small Data (LFSD 2025)
sites.google.com/view/lfsd2025/home ——————————————————————— ML4ITS2025 – Machine Learning for Irregular Time Series
ml4its.github.io/ml4its2025/ ——————————————————————— Workshop on Machine Learning and Data Mining for Sports Analytics (MLSA)
dtai.cs.kuleuven.be/events/MLSA25/ ——————————————————————— Learning to Quantify: Methods and Applications (LQ 2025)
lq-2025.github.io/ ——————————————————————— Advances in Interpretable Machine Learning and Artificial Intelligence (AIMLAI)
project.inria.fr/aimlai/ ——————————————————————— Human-Centered Data Mining Workshop (HuMine 2025)
humine2025.liacs.nl ——————————————————————— DEARING 2025: 2nd International Workshop on Data-cEntric ARtIficial iNtelliGence + Tutorial: AI’s Secret Key: The Power of High-Quality Data
dearing-workshop.github.io ——————————————————————— Towards Hybrid Human-Machine Learning and Decision Making (HLDM)
sml.disi.unitn.it/hldm25.html ——————————————————————— AI4WORK: International Workshop on AI for Human Resources and Public Employment Services
ai4work.github.io/ecmlpkdd2025/ ——————————————————————— Third Workshop on Machine Teaching for Humans (MT4H)
xai.w.uib.no/mt4h/ ——————————————————————— Interactive eXplainable AI – Theory and Practice (IXAIT)
IXAIT.geist.re ——————————————————————— Workshop on Responsible Healthcare using Machine Learning 2025
rhcml.github.io/ ——————————————————————— IoT, Edge, and Mobile for Embedded Machine Learning
www.item-workshop.org/ ——————————————————————— SynDAiTE – Synthetic Data for AI Trustworthiness and Evolution
aiimlab.org/events/ECML_PKDD_2025_SynDAiTE_Synthetic_Data_for_AI_Trustworthiness_and_Evolution.html ——————————————————————— MIDAS – The 10th Workshop on MIning DAta for financial applicationS
midas.portici.enea.it/ ——————————————————————— AIDEM 2025: International Tutorial and Workshop on Artificial Intelligence, Data Analytics and Democracy
aidem2025.isti.cnr.it/ ——————————————————————— XKDD 2025 and Beyond: 7th International Workshop on eXplainable Knowledge Discovery in Data Mining and Unlearning Through XAI
xkdd2025.isti.cnr.it ——————————————————————— 5th Machine Learning for Pharma and Healthcare Applications
sites.google.com/view/pharml2025/home ——————————————————————— WAFL – 3rd Workshop on Advancements in Federated Learning
wafl2025.di.unito.it ——————————————————————— Data Science Meets Optimization
sites.google.com/view/dso-workshopecml-pkdd-2025 ——————————————————————— MED-TIME: Learning on Real and Synthetic Medical Time Series Data
med-time2025.blogs.dsv.su.se/ ———————————————————————
For additional information, please check the webpage: ecmlpkdd.org/2025/submissions-workshop-track/ or sent an email to ecml-pkdd-2025-workshops-track@googlegroups.com
Carlos Ferreira
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
— Esta mensagem foi enviada para a rede APPIA, que engloba os associados da APPIA. Se desejar deixar de receber este tipo de mensagens, p.f. envie um email para appia [at] appia [ponto] pt

[rede.APPIA] DaSSWeb – Data Science and Statistics Webinar – 22 April – Donato Malerba – Data-Centric AI

MC
DaSSWeb- Data Science and Statistics Webinar

 

Tuesday, 22 April, 14:30 (WEST)

 

Speaker

Donato Malerba

Dept. of Computer Science

University of Bari “Aldo Moro”, Italy


Title

Data-Centric AI

Zoom link

Abstract

Artificial Intelligence (AI) has historically relied on two key elements: data and algorithms.

However, the traditional Model-Centric AI paradigm has typically emphasized algorithms, often handling data as static entities.

Data are typically gathered, pre-processed, and kept unchanged, with significant efforts focused on refining learned models.

This conventional approach has led to the development of increasingly complex and opaque decision models, requiring substantial effort in data training.

On the other hand, the emerging Data-Centric AI (DCAI) paradigm focuses on the systematic and algorithmic generation of optimal data to fuel Machine Learning (ML) and Deep Learning (DL) techniques.

The primary aim of the DCAI paradigm is to improve data quality, thereby achieving model accuracy deemed unattainable levels through model-centric techniques alone.

In this talk we will discuss the transformative effects of recent advancements in the DCAI paradigm on the future use of AI, ML and DL in data science.

The objective is to inspire further innovations in DCAI research, ultimately influencing the future landscape of in data science applications.

 

Main reference:

Donato Malerba, Vincenzo Pasquadibisceglie: Data-Centric AI. Journal of Intelligent Information Systems 62(6): 1493-1502 (2024)

pdf icon DaSSWeb-DonatoMalerba-22April2025.pdf

[rede.APPIA] AI-AEC@EPIA 2025

MC
CALL FOR PAPERS

AI for Architecture, Engineering and Conservation (AI-AEC)

We are pleased to invite you to submit your work to the EPIA 2025 thematic track “AI for Architecture, Engineering and Conservation (AI-AEC)”, to be held October 1–3, 2025, at the University of Algarve, Faro, Portugal.

Track webpage: https://epia2025.ualg.pt/tt-ai-for-architecture-engineering-and-conservation/

Important Deadlines
Paper submission deadline: May 23rd, 2025 (AoE)
Notification of acceptance: July 4th, 2025
Final paper submission deadline: July 14th, 2025 (AoE)
Conference dates: October 1st–3rd, 2025

About the thematic track
This track aims to highlight the transformative impact of Artificial Intelligence within the fields of architecture, engineering, and conservation, fostering innovations that include, among others, the following aspects:

  • Customized foundational models and AI frameworks applied to infrastructure resilience and structural monitoring;
  • Computer vision techniques, object detection, predictive modeling, and feature extraction essential for identifying and addressing defects in infrastructure, cultural heritage, and environmental systems;
  • AI applications for the three-dimensional reconstruction of historical artifacts and predictive maintenance of pavements, water supply systems, and other critical infrastructures;
  • Use of generative AI to support architectural design, urban planning, and the development of sustainable materials;
  • Leveraging data from satellites, drones, IoT sensors, and global collaborations, which are revolutionizing the analysis and understanding of large-scale datasets.

Publication and Presentation

Accepted papers will be included in the conference proceedings published in Springer’s Lecture Notes on Artificial Intelligence (LNAI) series. Selected high-quality papers may also be invited for extended versions to be published in a special virtual issue of the Journal of Cultural Heritage.

Why Submit?

Participating in this track will enable you to present your work to an international audience composed of researchers, professionals, and industry experts, contributing to advancements in AI applications in sectors critical to sustainability, innovation, and heritage preservation.

We look forward to your contribution to enrich this forum for discussion and knowledge sharing. For further details and to submit your paper, please visit the official conference website: https://epia2025.ualg.pt/