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I am an information engineer/computer scientist with 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 15 years of industrial experience in mechatronics and optimization applied to logistics, scheduling, and engineering problems.

I am an Associate Professor at the Department of Information Engineering and Computer Science (DISI), University of Trento, Italy, where I lead the Distributed Intelligence and Optimization Lab (DIOL). 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), and AI in Medicine. Since October 2024, I am the coordinator of the Master's Degree in Computer Science. 

My research profiles are available on Google Scholar, Scopus,  ORCID, DBLP, SemanticScholar, ResearchGate, WoS, LinkedIn, and Twitter.

My university profile is available on the University of Trento website.

News

2024

• September: New paper accepted on Transactions on Evolutionary Computation. Preprint: Evolutionary Computation and Explainable AI: A Roadmap to Transparent Intelligent Systems.

• September: Two papers accepted at NeurIPS 2024 and one paper accepted at SenSys 2024!

• July: Five papers presented 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 preprint posted. Frustratingly Easy Test-Time Adaptation of Vision-Language Models.

• May: New paper accepted at PPSN. Preprint: Influence Maximization in Hypergraphs using Multi-Objective Evolutionary Algorithms.

• April: New paper accepted on Transactions on Machine Learning Research! Understanding Sparse Neural Networks from their Topology via Multipartite Graph Representation. 

• April: Four papers accepted 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: Two papers accepted at EvoStar 2024. Low-Memory Matrix Adaptation Evolution Strategies Exploiting Gradient Information and Lévy Flight and 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: Two papers accepted at the European Robotics Forum 2024. One preprint available here.

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: A population-based approach for multi-agent interpretable reinforcement learning. Preprint available here.

• July: New work accepted at the 1st International Workshop on Machine Learning for Autonomic System Operation in the Device-Edge-Cloud Continuum (MLSysOps), part of EWSN 2023.

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

• June: Hyuno Mo successfully defended his PhD in Industrial Innovation!

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

• May: New preprint posted. Peeking inside Sparse Neural Networks using Multi-Partite Graph Representations.

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

• April: Leonardo Lucio Custode is the first PhD graduate (cum laude) from my group at the University of Trento!

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

• March: New paper accepted at GECCO. Self-Building Neural Networks. Preprint 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: New paper accepted at the 3rd Sparse Neural Networks workshop at ICLR 2023. Pruning and initialization vs. random pruning: Do they produce topologically different sparse neural networks? The poster is available here.

• 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.

2022

• December: ACM SAC paper accepted. Preprint available here.

• December: New paper published. Multi-objective automatic analysis of lung ultrasound data from COVID-19 patients by means of deep learning and decision trees.

• December: New paper published. Evolving Hebbian Learning Rules in Voxel-based Soft Robots. Preprint available here.

• December: New paper published. High Frame Rate Ultrasound Imaging by Means of Tensor Completion: Application to Echocardiography.

• December: New paper published. A single-solution–compact hybrid algorithm for continuous optimization

• December: New paper published. An improved Jaya optimization algorithm with ring topology and population size reduction.

• November: New paper published. A single-solution–compact hybrid algorithm for continuous optimization.

• November: New paper published. High Frame Rate Ultrasound Imaging by Means of Tensor Completion: Application to Echocardiography.

• November: Three papers presented at BIOMA, on interpretable policies for multi-agent reinforcement learning, accelerated NAS for RUL prediction, and genetic improvement of TCP congestion avoidance.

• August: New paper published.  Online Distributed Evolutionary Optimization of Time Division Multiple Access Protocols.

• August: New preprint posted. The emergence of division of labor through decentralized social sanctioning.

• June: I am co-editor of the Special Issue on Best Practices in Neural Architecture Search on MDPI Applied Sciences.

• June: PPSN paper accepted. Large-scale multi-objective influence maximisation with network downscaling. Preprint available here.

• April: Looking forward to giving an invited talk on real-world applications of Evolutionary Computation at the Evolutionary Computation in Practice track at GECCO 2022!

• April: Looking forward to giving an invited talk on XAI and Evolutionary Computation at WIVACE 2022!

• April: One GECCO poster, three GECCO workshop papers, and one ALIFE paper accepted.

• April: New preprint posted. Interpretable AI for policy-making in pandemics.

• March: I am co-editor of the Special Issue on Explainable AI in Evolutionary Computation on ACM Transactions on Evolutionary Learning and Optimization.

• March: I am co-editor of the Research Topic Artificial Living Beings: Field “Cross-Fertilization” on Frontiers Robotics and AI. 

• March: My lab is one of the available hosts for the SPECIES scholarships. Please find more info here.

• February: New preprint posted. Interpretable pipelines with evolutionarily optimized modules for RL tasks with visual inputs.

• January: Two papers were accepted at Evostar 2022 (and Hyunho Mo was nominated outstanding student).

2021

• December: New paper published. Optimizing the Sensory Apparatus of Voxel-based Soft Robots through Evolution and Babbling.

• November: Workshop on Evolutionary Computation and XAI (ECXAI) hosted at GECCO 2022. Check the workshop website.

• November: I joined the ELLIS (European Laboratory for Learning and Intelligent Systems) Society.

• November: New paper published. On the use of single non-uniform mutation in lightweight metaheuristics.

• November: New paper published. Cluster-centroid-based mutation strategies for Differential Evolution.

• October: Three papers accepted at IEEE Symposium Series on Computational Intelligence (SSCI) 2021.

• September: Special Session on Applications of Bioinspired Techniques on Social Networks will be hosted at Evostar 2022. You can find the flyer here.

• August: New paper published. A Compact Compound Sinusoidal Differential Evolution Algorithm for Solving Optimisation Problems in Memory-Constrained Environments.

• May: New paper published. Evolutionary Neural Architecture Search for Remaining Useful Life Prediction.

• April: Two more workshop papers and one hot-off-the-press paper accepted at GECCO 2021.

• March: Three papers accepted at GECCO 2021.

• March: Hyunho Mo received the Industrial Innovation PhD best presentation award at ICT Days 2021.

• March: New paper published. Genetic Improvement of Routing Protocols for Delay Tolerant Networks.

• February: Special Session on Bio-inspired approaches for modular robotics hosted at ALIFE 2021.

2020

• December: New paper published. Evolving Plasticity for Autonomous Learning under Changing Environmental Conditions.

• December: New paper published. Distributed Embodied Evolution over networks.