I am an Associate Professor in the Department of Information Engineering and Computer Science (DISI) at the University of Trento, Italy, where I lead the Distributed Intelligence and Optimization Lab (DIOL). I have a dual interest in fundamental and applied research. My main research areas are machine learning and optimization, explainable AI, and distributed systems. Moreover, I have over 15 years of industrial experience in mechatronics and optimization applied to engineering, logistics, and scheduling.
I have been the General Chair of the International Conference on Parallel Problem Solving From Nature (PPSN) 2026. Since 2026, I am also the chair of the PPSN Steering Committee (other members: Michael Affenzeller, Thomas Bäck, Carlos Fonseca, Emma Hart).
I am the Coordinator of the Master's Degree in Computer Science and the Deputy Director of the Information Engineering and Computer Science Doctoral School.
I teach (or have taught) courses on:
Computer Architectures (Bachelor's level)
Introduction to Machine Learning (Bachelor's level)
Bio-Inspired Artificial Intelligence (Master's level)
Optimization Techniques (Master's level)
AI in Medicine (Medical School)
My research profiles are available on Google Scholar, Scopus, ORCID, DBLP, SemanticScholar, ResearchGate, and WoS.
My university profile is available on the University of Trento website.
The CFP for the Special Session on Opinions and Trends in Evolutionary Computation, part of EvoStar 2027, is out!
October: Stefano Giampiccolo completed the PhD (cum laude) in Industrial Innovation!
September: I've been appointed Chair of the PPSN Steering Committee.
September: PPSN 2026 has wrapped up! Find the proceedings here.
July: New paper published: Evolutionary Algorithm-Based Ensemble of Aggregation Strategies in Federated Learning.
July: New preprint posted. PesTwin: A modular agent-based framework for pest and vector population control.
June: New paper published: INSTANT: Inference-Aware Fast Feedforward Networks.
June: New preprint posted. From Layers to Submodules: Rethinking Granularity in Replacement-Based LLM Compression.
May: New paper published. A novel approach to quantify out-of-distribution uncertainty in Neural and Universal Differential Equations. Preprint available here.
May: Giulia Buzzetti completed the PhD in Industrial Innovation! The PhD thesis is available here.
May: Michele Rossi completed the PhD as part of the Italian National Ph.D. Program in Artificial Intelligence! The PhD thesis is available here.
May: New preprint posted. Hallucination as an Anomaly: Dynamic Intervention via Probabilistic Circuits.
March: Mir Hassan completed the PhD in Information Engineering and Computer Science! The PhD thesis will be made available here.
March: New preprint posted. Frequency Matters: Fast Model-Agnostic Data Curation for Pruning and Quantization.
February: New paper published. A Machine Learning Pipeline for Wafer Shape Prediction in Diamond Coated Wire Slicing, Materials Today Communications.
February: Our publication Totipotent Neural Controllers for Modular Soft Robots: Achieving Specialization in Body-Brain Co-Evolution through Hebbian Learning received the ISAL Award for Outstanding Student Publication.
January: Six papers accepted at EvoStar 2026! More info to come.
November: New paper published. Advancing guitar emotion recognition through audio data augmentation to enhance smart musical instruments.
November: New paper published. Zeroth-Order Adaptive Neuron Alignment Based Pruning without Re-Training. Preprint available here.
October: I've been appointed Associate Editor for Applied Intelligence.
October: New paper published. An intelligent Digital Twin based on machine learning for interpretable decision-making in manufacturing.
August: New paper published. 2SSP: A Two-Stage Framework for Structured Pruning of LLMs. Preprint available here.
June: I've been appointed Associate Editor for Evolutionary Intelligence.
June: New paper published. Model-Free-Communication Federated Neuroevolution.
May: I'm happy to announce the first Workshop on Awareness and Consciousness in Artificial Intelligence (ACAI), part of the ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp). More info available here.
March: ACM TELO Special Issue on Explainable AI in Evolutionary Computation (part 2) published. Editorial available here.
April: The research that we are conducting within the framework of the EIC PATHFINDER project SUSTAIN has been acknowledged as a Key Innovation by the EU Innovation Radar (see here and here). Within this project, we are developing ultra-fast inference algorithms and advanced, self-adaptive Federated Learning algorithms.
April: New papers published at EvoStar 2025:
A Genetic Algorithm-Based Parameter Selection for Communication-Efficient Federated Learning
Multi-Objective Evolutionary Optimization of Virtualized Fast Feedforward Networks
Evolutionary Reinforcement Learning for Interpretable Decision Making for the Supply Chain
A Coach-Based Quality-Diversity Approach for Multi-Agent Interpretable Reinforcement Learning
March: Andrea Ferigo completed the PhD in Information Engineering and Computer Science! The PhD thesis is available here.
March: Two papers presented at ICLR 2025 Workshop on Sparsity in LLMs:
March: I've been appointed Editorial Board Member for Memetic Computing.
February: New paper published (in collaboration with MyAv). A customer behavior-driven clustering method in the planogram design domain
February: New paper published at AAAI 2025. SMoSE: Sparse Mixture of Shallow Experts for Interpretable Reinforcement Learning in Continuous Control Tasks. Preprint available here.