Data Research Meetup by MagIC - 4th Edition

About the Event

The 4^th edition of the Data Research Meetup by MagIC will focus on the theme “Beyond the Black Box: Understanding, Interpreting and Explaining AI.”

As artificial intelligence systems become increasingly present in research, organizations, and society, the need to understand how these systems work, how they make decisions, and how their outputs can be interpreted has become a central topic in Data Science and AI research.

Organized by MagIC – Information Management Research Center, this event will bring together researchers, faculty, students, and invited experts to discuss current challenges and research opportunities in Data Science and Management in the areas of Explainable and Interpretable AI.

The meetup aims to create a space for scientific exchange, discussion, and networking, contributing to a broader reflection on how AI systems can become more transparent, interpretable, and useful across different contexts.

Participation is free of charge, but prior registration is required. Complete the form below to secure your place.

Program

9:30 AM – Registration

10:00 AM – Welcome Notes
Professor Leonardo Vanneschi | Director of the MagIC Research Center

10:20 AM – Keynote: “We Built AI, But Can We Understand It? The Explainability Imperative”
Professor Luca Longo | Associate Professor, Director of the Artificial Intelligence and Cognitive Load Research Lab, University College Cork

11:20 AM – Coffee Break & Networking

11:40 AM – Roundtable: “The Future of AI Transparency”

Moderator: Professor Vitor Santos | Associate Professor, NOVA IMS

Speakers:

Professor Luca Longo | Associate Professor, Director of the Artificial Intelligence and Cognitive Load Research Lab, University College Cork
Professor Catarina Barata | Assistant Professor at Instituto Superior Técnico and Researcher at ISR-Lisboa, LARSyS
Professor Nuno Lourenço | Associate Professor at the University of Coimbra and Researcher at CISUC
Professor Cátia Pesquita | Associate Professor at the University of Lisbon, Vice-Director of LASIGE Research Centre

12:40 PM – Lunch & Poster Session

2:30 PM – MagIC’s Research in Data Science

“Interpretability in Machine Learning: Solving a Problem We Haven’t Defined”
Karina Brotto Rebuli | Postdoctoral Fellow, NOVA IMS

“Unlocking the Next Wave of AI”
Vitor Duarte Santos | Associate Professor, NOVA IMS

3:30 PM – Coffee Break & Networking

4:00 PM – MagIC’s Research in Data Science

“SLIM_GSGP: A Journey into Interpretable Symbolic Regression”
Sofia Alves Pereira | Adjunct Lecturer and PhD Student, NOVA IMS

“Ready or Not? Transparency and Digital Skills as Foundations for AI in European E-Government”
Mijail Naranjo | Assistant Professor, NOVA IMS

5:00 PM – Awards Ceremony for the Best PhD Poster
Professor Miguel de Castro Neto | Dean of NOVA IMS

5:20 PM – Wrap-up and Closing Remarks
Professor Miguel de Castro Neto | Dean of NOVA IMS

Speakers

Luca Longo

Associate Professor and Director of the AI and Cognitive Load Research Lab at University College Cork
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Catarina Barata

Assistant Professor at Instituto Superior Técnico and Researcher at ISR-Lisboa, LARSyS
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Nuno Lourenço

Associate Professor at the University of Coimbra and Researcher at CISUC
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Vítor Duarte Santos

Associate Professor at NOVA IMS
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Sofia Alves Pereira

Adjunct Lecturer at NOVA IMS
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Mijail Naranjo

Assistant Professor at NOVA IMS
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Karina Rebuli

Professor of the Practice and Postdoc fellow at NOVA IMS
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Registration Form

Registration for this event is now closed.

Keynote Address

Beyond the Black Box: Understanding, Interpreting and Explaining AI

Speaker: Professor Luca Longo
Associate Professor, Director of the Artificial Intelligence and Cognitive Load Research Lab, University College Cork

As part of the 4^th edition of the Data Research Meetup by MagIC, we will welcome Professor Luca Longo, whose work lies at the intersection of Explainable AI, Deep Learning, and human cognition.

His keynote address will explore the importance of moving beyond the use of AI systems as “black boxes,” highlighting the need to better understand, interpret, and explain the processes behind their outputs and decisions. The session will address the relevance of Explainable AI in scientific, organizational, and social contexts, as well as the challenges involved in developing intelligent systems that are more transparent, interpretable, and aligned with human understanding.

With an international career in Explainable Artificial Intelligence and Cognitive Load, Professor Luca Longo will bring a perspective on how AI can be designed, studied, and communicated in ways that make it more understandable to different audiences.

Poster Session

As part of the Data Research Meetup by MagIC, NOVA IMS PhD students are invited to submit a scientific poster presenting their ongoing research.

The poster session offers an opportunity to showcase research projects, receive feedback from experienced researchers, and engage with national and international experts attending the event.

Submissions are open to PhD students conducting research in Data Science, Management, or related interdisciplinary fields. At this stage, applicants are required to submit a short abstract (up to 300 words) describing the proposed poster.

Selected participants will receive a poster template and support for poster printing at no cost.

A Best Poster Award of €1,000 will be presented during the event.

Key dates

Abstract submission deadline: 15 June
Notification of acceptance: within one week after the deadline
Final poster submission: 6 July

To submit your proposal, please complete the Call for Proposals form.

3rd Edition Wrap Up

Take a look back at the key moments from the 3^rd edition of the Data Research Meetup.

Funding support

This work was supported by national funds through FCT,I.P. (Fundação para a Ciência e a Tecnologia,I.P.), under the project - UID/04152/2025 - Centro de Investigação em Gestão de Informação (MagIC)/NOVA IMS (DOI: 10.54499/UID/04152/2025, and by the European Union – NextGenerationEU under the project UID/PRR/04152/2025 (DOI: 10.54499/UID/PRR/04152/2025).