Projects

Multi-Objective Dynamics of Learning

A research line that studies learning as an inherently multi-objective process, seeking to understand how objectives compete and cooperate while a representation is being…

Mechanistic Interpretability and Latent Controllability in Large Language Models

2026 – ongoing

Mechanistic Interpretability

Representation Engineering

Large Language Models

Research on mechanistic interpretability, representation engineering (RepE), and attention steering in foundation models — investigating internal activation geometry to…

Long-Term Impacts of Machine Learning-Supported Decisions

2026 – ongoing

Responsible AI

Long-Term Fairness

Sequential Decision-Making

Multi-Objective Optimization

Offline Reinforcement Learning

Contextual Bandits

Performative Prediction

A two-stage sequential decision-making framework combining offline reinforcement learning, contextual bandits, and multi-objective optimization to eliminate harmful feedback…

AI for Finance - HIAAC

The goal of this research line is to develop robust and transparent AI models for credit analysis and similar problems in the financial sector, such as fraud detection.

Applied Deep Learning for Specialized Domains

2018 – ongoing

Deep Learning

Computer Vision

Applied Machine Learning

Collaborative Research

Collaborations applying deep learning methods to specific, real-world domain problems — from ecological image classification to medical imaging and code generation.

Multi-objective Optimization and Ensemble Learning for Machine Learning Models

2014 – 2025

Multi-objective Optimization

Continuous Optimization

Mathematical Programming

Ensemble Learning

Algorithmic Fairness

Machine Learning

Research on continuous and many-objective optimization techniques (NISE/MONISE) applied to regularized machine learning, model selection, ensemble generation, and…