Researcher | Trustworthy AI

SnT

Biography

I defended my Ph.D. at FCUP in Computer Science with a research focus on data privacy and utility preservation of machine learning models. My work centers on developing and evaluating methods that enable the responsible use of AI, with a particular interest in privacy-preserving techniques and regulatory compliance. Passionate about trustworthy AI, I’m committed to advancing technologies that are not only private but also fair and explainable.

Education

  • PhD in Computer Science, 2025

    Faculty of Sciences, University of Porto

  • MSc in Network and Information Systems Engineering, 2019

    Faculty of Sciences, University of Porto

Experience

 
 
 
 
 
Research and Development Specialist
Interdisciplinary Centre for Security, Reliability and Trust (SnT)
Apr 2025 – Present Luxembourg

Research topics include:

  • Quality Assurance
  • Trustworthiness
  • Foundation Models
  • Counterfactual Explanations
 
 
 
 
 
Data Science Researcher
TekPrivacy
Feb 2020 – Apr 2025 Porto

Research topics:

  • Federated Learning
  • De-identification Process
  • Privacy Enhancing Technologies (PETs)
  • Privacy-Utility Trade-off
  • Meta-learning
  • LLMs
 
 
 
 
 
Visiting Researcher
Lucy Family Institute for Data and Society | University of Notre Dame
Mar 2023 – Jun 2023 Indiana, Unitate States

Developed projects:

 
 
 
 
 
Data Scientist Trainee
NOS
Oct 2018 – Sep 2019 Porto

MSc thesis - Antecipation of Services Perturbance

  • Classification tasks
  • Imbalance domains
  • Sliding windows
  • Big data

Interests

Machine Learning

  * Supervised Learning
  * Federated Learning
  * Meta-learning
  * Generative AI
  * Foundation Models

Open Data

  * EDA
  * Record Linkage
  * Privacy-Utility trade off
  * Secure Data Sharing

Data Privacy

* De-identification
* Privacy-preserving techniques
* Synthetic Data
* Privacy risks

Accomplish­ments

Best Paper Award
22nd Portuguese Conference on Artificial Intelligence (EPIA 2023) Sep 2023
With the paper A Three-Way Knot: Privacy, Fairness, and Predictive Performance Dynamics

Projects

ε-PrivateSMOTE

ε-PrivateSMOTE

Differentially-Private Data Synthetisation for Efficient Re-Identification Risk Control

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Hands-on data de-identification

Hands-on data de-identification

Practical course covering the basic principles of the data de-identification process.

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Publications

Pedro Santos, Tânia Carvalho, Filipe Magalhães, Luís Antunes (2025). Secure Visual Data Processing via Federated Learning. In ICISSP.

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Tânia Carvalho, Luís Antunes, Cristina Costa, Nuno Moniz (2025). Empowering Open Data Sharing for Social Good: A Privacy-Aware Approach. In Scientific Data (Nature).

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Filipa Lopes, Carolina Trindade, Tânia Carvalho, Maria Almeida, Ana Sofia Carvalho (2024). Developing Project-Specific Consent Documents: A Registered Report for a Multistep Approach Using LLMs. In Drug Repurposing.

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Carolina Trindade, Luís Antunes, Tânia Carvalho, Nuno Moniz (2024). Synthetic Data Outliers: Navigating Identity Disclosure. In International Conference on Privacy in Statistical Databases.

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Tânia Carvalho, Nuno Moniz, Luís Antunes (2024). Automated Privacy-Preserving Techniques via Meta-Learning. In arxiv (Under review in Information Fusion SI - Explainable AI in Industry 4.0 and 5.0).

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Filipa Lopes, Carolina Trindade, Tânia Carvalho, Maria Almeida, Ana Sofia Carvalho (2024). Developing Project-Specific Informed Consent Forms: A Multi-Step Approach within the REPO4EU Framework. In RExPO24.

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Tânia Carvalho, Nuno Moniz, Luís Antunes (2023). A Three-Way Knot: Privacy, Fairness, and Predictive Performance Dynamics. In EPIA Conference on Artificial Intelligence.

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Tânia Carvalho, Nuno Moniz, Pedro Faria, Luís Antunes (2023). Towards a Data Privacy-Predictive Performance Trade-off. In ESwA.

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Tânia Carvalho, Nuno Moniz, Pedro Faria, Luís Antunes (2023). Survey on Privacy-Preserving Techniques for Data Publishing. In ACM Computing Surveys.

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Tânia Carvalho, Nuno Moniz, Pedro Faria, Luís Antunes, Nitesh Chawla (2022). Privacy-Preserving Data Synthetisation for Secure Information Sharing. In arXiv (Revisions Decision in Machine Learning).

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Tânia Carvalho, Nuno Moniz, Pedro Faria, Luís Antunes (2021). Fundamental privacy rights in a pandemic state. In PLoS ONE.

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Tânia Carvalho, Nuno Moniz (2021). The Compromise of Data Privacy in Predictive Performance. In Symposium on Intelligent Data Analysis.

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Collaborations

Business Mentor
I was a mentor at the 7th Hack a City event, where I provided guidance and support to participants to improve the city of Porto’s data safely. I was also responsible for the prior de-identification of such data.
Nov 1, 2024
Hackacity
Business Mentor
Collaborator
I investigated the use of LLMs to assist in the creation of information sheets and informed consent forms for clinical trials. This study is conducted within the context of the research project REPO4EU (Precision drug REPurpOsing For EUrope and the world).
Jun 1, 2024
RePo4EU
Collaborator

Supervision

Current
Oct 2024 – Oct 2025
  • Carolina Trindade (PhD) - Automated Reconstruction Attacks
  • Cristina Pêra (MSc) - Membership Inference Attacks: Evaluation and Defenses
  • Tiago Eusébio (MSc) - Automatic Detection of Personal Information in Tabular Data
Alumni
Oct 2023 – Sep 2024
  • Miguel Ramos (MSc) - Advancements in Vertical Federated Learning: Utility Preservation with a Lightweight Model
  • Pedro Santos (MSc) - AI-Powered visual Privacy and Labeling
Oct 2022 – Sep 2023
  • Carolina Trindade (MSc) - Identity Disclosure in Synthetic Data
  • Gustavo Pereira (MSc) - Automated Algorithm for Privacy Preservation of Data

Contact