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I am an Associate Professor at the Department of Information Engineering and Computer Science (DISI) of 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 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.

Call for Papers

• CFP for Parallel Problem Solving from Nature (PPSN). Deadline 28 March 2026.

• CFP for the Special Issue on Interpretable Reinforcement Learning on Applied Soft Computing (Q1). Deadline 31 December 2025.

• CFP for the Special Session on Opinions and Trends in Evolutionary Computation at EvoStar 2026. Deadline 1 November 2025.

News

2025

• 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), which will be part of the ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp). More info available here.

• April: New papers published at EvoStar 2024:

  • Addressing Radiotherapy Scheduling with a Bin Packing Problem Formulation - A Comparative Study of Exact Solvers and Genetic Algorithms

  • 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

  • Social Interpretable Reinforcement Learning

• March: Andrea Ferigo successfully defended his PhD in Information Engineering and Computer Science! The PhD thesis is available here.

• March: Two papers accepted at ICLR 2025 Workshop on Sparsity in LLMs:

  • 2SSP: A Two-Stage Framework for Structured Pruning of LLMs

  • Zeroth-Order Adaptive Neuron Alignment Based Pruning without Re-Training

• 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.

2024

• December: I've been appointed chair of PPSN 2026, to be held in Trento in 2026! More info here.

• November: New preprint posted. Zeroth-Order Adaptive Neuron Alignment Based Pruning without Re-Training

• November: New paper published. Totipotent neural controllers for modular soft robots: Achieving specialization in body–brain co-evolution through Hebbian learning

• November: New paper published at SenSys 2024. Fast-Inf: Ultra-Fast Embedded Intelligence on the Batteryless Edge

• November: New paper published at NeurIPS 2024. Frustratingly Easy Test-Time Adaptation of Vision-Language Models

• November: New paper published at NeurIPS 2024. Diffusion-based Curriculum Reinforcement Learning

• September: New paper published.  Evolutionary Computation and Explainable AI: A Roadmap to Understandable Intelligent Systems. Preprint available here.

• July: New papers published at GECCO 2024 workshops:

  • The Effect of Training Schedules on Morphological Robustness and Generalization

  • Balancing human livability and bumblebee population in urban green areas via Agent-Based Model and Evolutionary Algorithms

  • Accelerating GP Genome Evaluation Through Real Compilation with a Multiple Program Single Data Approach

  • An investigation on the use of Large Language Models for hyperparameter tuning in Evolutionary Algorithms

  • Comparing Large Language Models and Grammatical Evolution for Code Generation

• July: New paper published. A co-evolutionary algorithm with adaptive penalty function for constrained optimization

• July: We won the Interpretable Control Competition - Continuous Track at GECCO 2024!

• May: New paper published at PPSN 2024. Influence Maximization in Hypergraphs Using Multi-Objective Evolutionary Algorithms. Preprint available here.

• April: New paper published. Understanding Sparse Neural Networks from their Topology via Multipartite Graph Representation. Preprint available here. 

• April: Four papers published at GECCO 2024:

  • Neuron-centric Hebbian Learning (oral)

  • NEvoFed: A Decentralized Approach to Federated NeuroEvolution of Heterogeneous Neural Networks (oral)

  • Multi-Objective Evolutionary Hindsight Experience Replay for Robot Manipulation Tasks (oral)

  • Many-Objective Evolutionary Influence Maximization: Balancing Spread, Budget, Fairness, and Time (poster)

• April: Hyunho Mo got the Best PhD Award 2023 in Industrial Innovation!

• March: New paper published. Curriculum learning for robot manipulation tasks with sparse reward through environment shifts

• March: New papers published at EvoStar 2024:

  • Low-Memory Matrix Adaptation Evolution Strategies Exploiting Gradient Information and Lévy Flight

  • Hindsight Experience Replay with Evolutionary Decision Trees for Curriculum Goal Generation

• March: ACM TELO Special Issue on Special Issue on Explainable AI in Evolutionary Computation published. Editorial available here.

• February: New papers published at the European Robotics Forum (ERF) 2024

  • Awareness in robotics: An early perspective from the viewpoint of the EIC Pathfinder Challenge "Awareness Inside''. Preprint available here.

  • A Reinforcement Learning method to minimize the damage on a falling Ballbot

2023

• December: I've been appointed Associate Editor for IEEE Transactions on Evolutionary Computation.

• November: New paper published.  Quality-Diversity Optimization of Decision Trees for Interpretable Reinforcement Learning

• November: New paper published. Metaheuristics in the balance: a survey on memory-saving approaches for platforms with seriously limited resources

• August: New paper published. A population-based approach for multi-agent interpretable reinforcement learning. Preprint available here.

• June: Our work on Evolutionary Computation and XAI, and Leonardo Lucio Custode's PhD work are on the SIGEVO newsletter

• June: Hyunho Mo successfully defended his PhD in Industrial Innovation! The PhD thesis is available here.

• May: It's been a pleasure to give a public outreach talk on Generative AI at the Cremona Art Week! Kudos to our great students!

• May: New paper published at GECCO 2023 Workshop on Industrial Applications of Metaheuristics. Evolutionary F1 Race Strategy

• April: Leonardo Lucio Custode successfully defended his PhD (cum laude) in Information Engineering and Computer Science! The PhD thesis is available here.

• April: New paper published. Evolutionary Neural Architecture Search on Transformers for RUL Prediction.

• March: New paper published at GECCO 2023. Self-Building Neural Networks. Preprint available here. Medium story (written by an external researcher) available here.

• March: I've been appointed Editorial Board Member for Applied Soft Computing.

• March: New paper published. Evolutionary Optimization of Convolutional Extreme Learning Machine for Remaining Useful Life Prediction.

• March: It's a great honor to host as visiting guest lecturer Prof. Marjan Mernik from the University of Maribor, Slovenia. Inspiring talk on Exploration and Exploitation in Evolutionary Algorithms: Recent Developments.

• February: I've been elevated to the grade of IEEE Senior member.

• January: New paper published.  Evolutionary learning of interpretable decision trees. Preprint available here. Code available here, featured in PwC newsletter.