🏆 Best PhD Thesis in Artificial Intelligence in Portugal 2025!! 🏆
I am thrilled to share that I have received the 2025 Best PhD Thesis in Artificial Intelligence Award from APPIA, recognising doctoral research of outstanding merit in AI carried …
Solving MaxSAT Problems from Natural Language Descriptions with LLMs and PySAT @ LLM-Solve @ FLoC 2026
In this talk, we will present a framework for solving MaxSAT problems expressed in natural language by combining large language models with the PySAT toolkit. We will show how LLMs …
📄🤖 2 Papers accepted @ EPIA 2026!! 🎉🎉
Excited to share that two of our papers have been accepted at EPIA 2026, covering the robustness of LLMs for code understanding and neuro-symbolic feedback for Vision-Language …
📄📄📄 3 Papers accepted @ FLoC 2026!! 🎉🎉🎉
Excited to share that three of our papers have been accepted at FLoC 2026, covering automated feedback for Prolog education, data-driven mutation testing for Prolog, and …
Solving MaxSAT Problems from Natural Language Descriptions with LLMs and PySAT
In this paper, we study a neuro-symbolic approach in which an LLM translates a natural language description of an optimisation problem into executable Python code using PySAT. The …
Sherlock4Py
🔎🐛 Sherlock4Py 🐍 MaxSAT-Based Misbehaviour Verification and Localisation Framework for Python Sherlock4Py is a research project investigating how formal reasoning and Large …
MENTOR: Fixing Introductory Programming Assignments With Formula-Based Fault Localization and LLM-Driven Program Repair @ INESC-ID
In this talk, I will present my PhD work on MENTOR, a semantic automated program repair framework designed to provide meaningful feedback for introductory programming assignments.
Honored to Receive the INESC-ID Best PhD Student 2025 Award!! 🏆
I am thrilled to share that I was the recipient of the INESC-ID Best PhD Student 2025 Award, which recognises my PhD research conducted at INESC-ID (2020 -- 2024).
Neuro-Symbolic AI for Reliable Reasoning
Modern foundation models, including Large Language Models (LLMs) and Vision-Language Models (VLMs), have remarkable capabilities for understanding natural language, code, and …
From Logic to Learning: Rethinking Programming for the AI Era @ DEI, IST-UL
In this talk, I will present approaches that leverage the precision of formal logic and the adaptability of learning-based models to enable intelligent code generation, automated …
Counterexample Guided Program Repair Using Large Language Models and MaxSAT-based Fault Localization @ IIIA-CSIC
In this talk I will present a hybrid method to automated repair of C code, using Maximum Satisfiability (MaxSAT)-based fault localization, CFaults, to localize bugs and LLMs to …
MENTOR: Automated Feedback for Introductory Programming Exercises @ FCT-UNL
In my talk, I will present MENTOR, a semantic automated program repair (APR) framework designed to provide Automated Feedback for Introductory Programming Exercises.
MENTOR: Feedback Automático para Exercícios Introdutórios de Programação (Portuguese) @ VoA 2025
Nesta palestra, irei apresentar o sistema MENTOR, uma ferramenta de reparação automática de programas orientada para fornecer feedback automatizado para exercícios introdutórios de …
🏆 Honored to Receive the Vencer o Adamastor (VoA) Award 2025!! 🏆
I am thrilled to share that I was the recipient of the Vencer o Adamastor 2025 prize, which acknowledges innovative contributions by young scientists in Portugal. 🎉 🎉
MENTOR: Automated Feedback for Introductory Programming Exercises
This PhD thesis presents MENTOR, a semantic automated program repair (APR) framework designed to provide Automated Feedback for Introductory Programming Exercises.
Counterexample Guided Program Repair Using Zero-Shot Learning and MaxSAT-based Fault Localization @ OutSystems
In this talk I will present our novel approach that combines the strengths of both FM-based fault localization and LLMs, via zero-shot learning, to enhance Automated Program …