| 2026 |
|---|
| S Barcellona, L Codecasa, S Colnago, L Cannelli, C Laurano, G Maroni, Capacity estimation of Lithium-ion batteries through a Machine Learning approach , Mathematics and Computers in Simulation, 2026, link. |
| 2025 |
|---|
| S Barcellona, L Cannelli, L Codecasa, S Colnago, L Cristaldi, C Laurano, G Maroni, Investigation of the Relationship between High and Low Frequency Resistances of Li-ion Batteries: A Machine Learning Approach , 2025 IEEE International Conference on Metrology for eXtended Reality, 2025, link. |
| S Hayat, M Schranz, L Cannelli, Neural Network-Enhanced Self-Organization for Efficient Resource Allocation in Distributed Edge Computing Environments , 2025 IEEE 9th International Conference on Fog and Edge Computing (ICFEC), 2025, link. |
| F Gioia, F Pura, A Greco, D Piga, A Merla, M Forgione, Contactless Estimation of Respiratory Frequency Using 3D-CNN on Thermal Images , IEEE Journal of Biomedical and Health Informatics, 2025, link. |
| G Maroni, L Cannelli, D Piga, Gradient-based bilevel optimization for multi-penalty Ridge regression through matrix differential calculus , European Journal of Control, volume 81, 2025, link. |
| 2024 |
|---|
| G Maroni, L Cannelli, D Piga, Differentiable multi-ridge regression for system identification , IFAC-PapersOnLine, voulme 58, issue 15, 187-192, 2024, link. |
| RG Cestari, G Maroni, L Cannelli, D Piga, S Formentin, Split-Boost Neural Networks , IFAC-PapersOnLine, volume 58, issue 15, 241-246, 2024, link. |
| D Piga, M Rufolo, G Maroni, M Mejari, M Forgione, Synthetic data generation for system identification: leveraging knowledge transfer from similar systems , 63rd IEEE Conference on Decision and Control (CDC), 2024, link. |
| M Forgione, M Mejari, D Piga, Model order reduction of deep structured state-space models: A system-theoretic approach , 63rd IEEE Conference on Decision and Control (CDC), 2024, link. |
| R Busetto, V Breschi, M Forgione, D Piga, In-context learning of state estimators , 20th IFAC Symposium on System Identification, 2024, link. |
| D Piga, F Pura, M Forgione, On the adaptation of in-context learners for system identification , 20th IFAC Symposium on System Identification, 2024, link. |
| A Uwadukunze, X Bombois, M Forgione, M Gilson, M Albisser, Identification for Feedforward Control of Wiener Systems , 4th IFAC Conference of Modelling, Identification and Control of Nonlinear Systems, 2024, link. |
| F Venturini, S Fluri, M Mejari, M Baumgartner, D Piga, U Michelucci, Shedding light on the ageing of extra virgin olive oil: Probing the impact of temperature with fluorescence spectroscopy and machine learning techniques , LWT 191, 115679, 2024, link. |
| G Maroni, F Stojceski, L Pallante, MA Deriu, D Piga, G Grasso, LightCPPgen: An Explainable Machine Learning Pipeline for Rational Design of Cell Penetrating Peptides , arXiv preprint arXiv:2406.01617, 2024, link. |
| G Onori, AA Shahid, F Braghin, L Roveda, Adaptive optimization of hyper-parameters for robotic manipulation through evolutionary reinforcement learning , Journal of Intelligent & Robotic Systems 110 (3), 108, 2024, link. |
| AA Shahid, Y Narang, V Petrone, E Ferrentino, A Handa, D Fox, ..., Scaling Population-Based Reinforcement Learning with GPU Accelerated Simulation , arXiv preprint arXiv:2404.03336, 2024, link. |
| S Barcellona, L Cannelli, L Codecasa, S Colnago, L Cristaldi, C Laurano, G Maroni, Temperature-Dependent State of Charge Estimation for Electric Vehicles Based on a Machine Learning Approach , 2024 IEEE International Conference on Metrology for eXtended Reality …, 2024, link. |
| 2023 |
|---|
| M Forgione, A Muni, D Piga, M Gallieri, On the adaptation of recurrent neural networks for system identification , Automatica 155, 111092, 2023, link. |
| L Roveda, P Veerappan, M Maccarini, G Bucca, A Ajoudani, D Piga, A human-centric framework for robotic task learning and optimization , Journal of Manufacturing Systems 67, 68-79, 2023, link. |
| P Franceschi, M Maccarini, D Piga, M Beschi, L Roveda, Human Preferences Optimization in pHRI Collaborative tesks , 2023 20th international conference on ubiquitous robots (UR), 693-699, 2023, link. |
| L Roveda, L Mantovani, M Maccarini, F Braghin, D Piga, Optimal physical human–robot collaborative controller with user-centric tuning , Control Engineering Practice 139, 105621, 2023, link. |
| LA Dao, L Roveda, M Maccarini, ML Nicora, M Mondellini, MM Falerni, ..., Experience in Engineering Complex Systems: Active Preference Learning with Multiple Outcomes and Certainty Levels , arXiv preprint arXiv:2302.14630, 2023, link. |
| M Maccarini, AA Shahid, D Piga, L Roveda, Self-Modulated Adaptive Robotic Deposition: an Application to the Aerospace Industry , 2023 International Conference on Electrical, Computer and Energy …, 2023, link. |
| M Forgione, F Pura, D Piga, From system models to class models: An in-context learning paradigm , IEEE Control Systems Letters, 2023, link. |
| M Forgione, F Pura, D Piga, In-context learning for model-free system identification , arXiv preprint arXiv:2308.13380, 2023, link. |
| A Gupta, M Mejari, P Falcone, D Piga, Computation of parameter dependent robust invariant sets for LPV models with guaranteed performance , Automatica 151, 110920, 2023, link. |
| M Mejari, A Gupta, D Piga, Data-driven computation of robust invariant sets and gain-scheduled controllers for linear parameter-varying systems , IEEE Control Systems Letters, 2023, link. |
| N Rubattu, G Maroni, G Corani, Electricity Load and Peak Forecasting: Feature Engineering, Probabilistic LightGBM and Temporal Hierarchies , International Workshop on Advanced Analytics and Learning on Temporal Data …, 2023, link. |
| SM Savaresi, A Buzzetti, NGU Valerio, M Campana, F Previdi, G Maroni, ..., Head-counter device and method for processing digital images , US Patent 11,663,844, 2023, link. |
| L Cannelli, G Nuti, M Sala, O Szehr, Hedging using reinforcement learning: Contextual k-armed bandit versus Q-learning , The Journal of Finance and Data Science 9, 100101, 2023, link. |
| L Cannelli, M Zhu, F Farina, A Bemporad, D Piga, Multi-agent active learning for distributed black-box optimization , IEEE Control Systems Letters 7, 1488-1493, 2023, link. |
| S Barcellona, L Cannelli, S Colnago, C Laurano, L Piegari, Cycle Aging Effect on Lithium-ion Battery Resistance: a Machine Learning Approach , 2023 IEEE International Conference on Metrology for eXtended Reality …, 2023, link. |
| ÖE Dural, AA Shahid, G Gioioso, D Prattichizzo, F Braghin, L Roveda, Evaluation of Tactile Feedback for Teleoperated Glove-Based Interaction Tasks , International Workshop on Human-Friendly Robotics, 79-93, 2023, link. |
| M Maccarini, AA Shahid, D Piga, L Roveda, Self-Modulated Adaptive Robotic Deposition: an Application to the Aerospace Industry , 2023 International Conference on Electrical, Computer and Energy …, 2023, link. |
| AA Shahid, M Forgione, M Gallieri, L Roveda, D Piga, Robotics Benchmark on Transfer Learning: a Human-Robot Collaboration Use Case , IFAC-PapersOnLine 56 (2), 8351-8356, 2023, link. |
| 2022 |
|---|
| AA Shahid, D Piga, F Braghin, L Roveda, Continuous control actions learning and adaptation for robotic manipulation through reinforcement learning , Autonomous Robots 46 (3), 483-498, 2022, link. |
| AA Shahid, D Piga, F Braghin, L Roveda, Continuous control actions learning and adaptation for robotic manipulation through reinforcement learning , Autonomous Robots 46 (3), 483-498, 2022, link. |
| L Roveda, A Testa, AA Shahid, F Braghin, D Piga, Q-Learning-based model predictive variable impedance control for physical human-robot collaboration , Artificial Intelligence 312, 103771, 2022, link. |
| M Forgione, M Mejari, D Piga, Learning neural state-space models: Do we need a state estimator? , arXiv preprint arXiv:2206.12928, 2022, link. |
| M Mejari, B Mavkov, M Forgione, D Piga, Direct identification of continuous-time LPV state-space models via an integral architecture , Automatica 142, 110407, 2022, link. |
| M Maccarini, F Pura, D Piga, L Roveda, L Mantovani, F Braghin, Preference-based optimization of a human-robot collaborative controller , IFAC-PapersOnLine 55 (38), 7-12, 2022, link. |
| L Pozzi, M Gandolla, F Pura, M Maccarini, A Pedrocchi, F Braghin, D Piga, ..., Grasping learning, optimization, and knowledge transfer in the robotics field , Scientific Reports 12 (1), 4481, 2022, link. |
| L Roveda, G Farinella, M Maccarini, F Pura, N Castaman, B Spahiu, ..., Multi-Objects Robotic Grasping Optimization Employing a 2D camera , 2022 International Conference on Electrical, Computer, Communications and …, 2022, link. |
| M Maccarini, F Pura, D Piga, L Roveda, L Mantovani, F Braghin, Preference-based optimization of a human-robot collaborative controller , IFAC-PapersOnLine 55 (38), 7-12, 2022, link. |
| L Pozzi, M Gandolla, F Pura, M Maccarini, A Pedrocchi, F Braghin, D Piga, ..., Grasping learning, optimization, and knowledge transfer in the robotics field , Scientific Reports 12 (1), 4481, 2022, link. |
| L Roveda, G Farinella, M Maccarini, F Pura, N Castaman, B Spahiu, ..., Multi-Objects Robotic Grasping Optimization Employing a 2D camera , 2022 International Conference on Electrical, Computer, Communications and …, 2022, link. |
| M Mejari, B Mavkov, M Forgione, D Piga, Direct identification of continuous-time LPV state-space models via an integral architecture , Automatica 142, 110407, 2022, link. |
| G Maroni, L Pallante, G Di Benedetto, MA Deriu, D Piga, G Grasso, Informed classification of sweeteners/bitterants compounds via explainable machine learning , Current Research in Food Science 5, 2270-2280, 2022, link. |
| M Mazzoleni, G Maroni, S Formentin, F Previdi, A kernel-based control approach for multi-period assets allocation based on lower partial moments , Engineering Applications of Artificial Intelligence 110, 104659, 2022, link. |
| K Slavakis, GN Shetty, L Cannelli, G Scutari, U Nakarmi, L Ying, Kernel regression imputation in manifolds via bi-linear modeling: The dynamic-MRI case , IEEE Transactions on Computational Imaging 8, 133-147, 2022, link. |
| AA Shahid, D Piga, F Braghin, L Roveda, Continuous control actions learning and adaptation for robotic manipulation through reinforcement learning , Autonomous Robots 46 (3), 483-498, 2022, link. |
| L Roveda, A Testa, AA Shahid, F Braghin, D Piga, Q-Learning-based model predictive variable impedance control for physical human-robot collaboration , Artificial Intelligence 312, 103771, 2022, link. |
| L Roveda, M Maroni, L Mazzuchelli, L Praolini, AA Shahid, G Bucca, ..., Robot end-effector mounted camera pose optimization in object detection-based tasks , Journal of Intelligent & Robotic Systems 104 (1), 16, 2022, link. |
| A Formenti, G Bucca, AA Shahid, D Piga, L Roveda, Improved impedance/admittance switching controller for the interaction with a variable stiffness environment , Complex Engineering Systems 2 (3), 1-18, 2022, link. |
| L Roveda, G Farinella, M Maccarini, F Pura, N Castaman, B Spahiu, ..., Multi-Objects Robotic Grasping Optimization Employing a 2D camera , 2022 International Conference on Electrical, Computer, Communications and …, 2022, link. |
| 2021 |
|---|
| F D Ascenzo, O De Filippo, G Gallone,G Mittone,MA Deriu,..., Machine learning-based prediction of adverse events following an acute coronary syndrome (PRAISE): a modelling study of pooled datasets , The Lancet 397 (10270), 199-207, 2021, link. |
| M Forgione, D Piga, Continuous-time system identification with neural networks: Model structures and fitting criteria , European Journal of Control 59, 69-81, 2021, link. |
| L Roveda, M Magni, M Cantoni, D Piga, G Bucca, Human–robot collaboration in sensorless assembly task learning enhanced by uncertainties adaptation via Bayesian Optimization , Robotics and Autonomous Systems 136, 103711, 2021, link. |
| G Halasz, M Sperti, M Villani, U Michelucci, P Agostoni, A Biagi, L Rossi, ..., A machine learning approach for mortality prediction in COVID-19 pneumonia: development and evaluation of the Piacenza score , Journal of Medical Internet Research 23 (5), e29058, 2021, link. |
| L Roveda, M Magni, M Cantoni, D Piga, G Bucca, Human–robot collaboration in sensorless assembly task learning enhanced by uncertainties adaptation via Bayesian Optimization , Robotics and Autonomous Systems 136, 103711, 2021, link. |
| S Dalla Gasperina, L Roveda, A Pedrocchi, F Braghin, M Gandolla, Review on patient-cooperative control strategies for upper-limb rehabilitation exoskeletons , Frontiers in Robotics and AI 8, 745018, 2021, link. |
| G Halasz, M Sperti, M Villani, U Michelucci, P Agostoni, A Biagi, L Rossi, ..., A machine learning approach for mortality prediction in COVID-19 pneumonia: development and evaluation of the Piacenza score , Journal of Medical Internet Research 23 (5), e29058, 2021, link. |
| L Roveda, D Piga, Sensorless environment stiffness and interaction force estimation for impedance control tuning in robotized interaction tasks , Autonomous Robots 45 (3), 371-388, 2021, link. |
| M Forgione, D Piga, Continuous-time system identification with neural networks: Model structures and fitting criteria , European Journal of Control 59, 69-81, 2021, link. |
| M Forgione, D Piga, dynoNet: A neural network architecture for learning dynamical systems , International Journal of Adaptive Control and Signal Processing 35 (4), 612-626, 2021, link. |
| G Halasz, M Sperti, M Villani, U Michelucci, P Agostoni, A Biagi, L Rossi, ..., A machine learning approach for mortality prediction in COVID-19 pneumonia: development and evaluation of the Piacenza score , Journal of Medical Internet Research 23 (5), e29058, 2021, link. |
| G Halasz, M Sperti, M Villani, U Michelucci, P Agostoni, A Biagi, L Rossi, ..., A machine learning approach for mortality prediction in COVID-19 pneumonia: development and evaluation of the Piacenza score , Journal of Medical Internet Research 23 (5), e29058, 2021, link. |
| L Roveda, AA Shahid, N Iannacci, D Piga, Sensorless optimal interaction control exploiting environment stiffness estimation , IEEE Transactions on Control Systems Technology 30 (1), 218-233, 2021, link. |
| L Roveda, B Maggioni, E Marescotti, AA Shahid, AM Zanchettin, ..., Pairwise preferences-based optimization of a path-based velocity planner in robotic sealing tasks , IEEE Robotics and Automation Letters 6 (4), 6632-6639, 2021, link. |
| AA Shahid, JSV Sesin, D Pecioski, F Braghin, D Piga, L Roveda, Decentralized multi-agent control of a manipulator in continuous task learning , Applied sciences 11 (21), 10227, 2021, link. |
| 2020 |
|---|
| L Roveda, M Forgione, D Piga, Robot control parameters auto-tuning in trajectory tracking applications , Control Engineering Practice 101, 104488, 2020, link. |
| A Lucchini, S Formentin, M Corno, D Piga, SM Savaresi, Torque vectoring for high-performance electric vehicles: an efficient MPC calibration , IEEE Control Systems Letters 4 (3), 725-730, 2020, link. |
| L Roveda, J Maskani, P Franceschi, A Abdi, F Braghin, L Molinari Tosatti, ..., Model-based reinforcement learning variable impedance control for human-robot collaboration , Journal of Intelligent & Robotic Systems 100 (2), 417-433, 2020, link. |
| L Roveda, M Forgione, D Piga, Robot control parameters auto-tuning in trajectory tracking applications , Control Engineering Practice 101, 104488, 2020, link. |
| L Roveda, L Savani, S Arlati, T Dinon, G Legnani, LM Tosatti, Design methodology of an active back-support exoskeleton with adaptable backbone-based kinematics , International Journal of Industrial Ergonomics 79, 102991, 2020, link. |
| AA Shahid, L Roveda, D Piga, F Braghin, Learning continuous control actions for robotic grasping with reinforcement learning , 2020 IEEE International Conference on Systems, Man, and Cybernetics (SMC …, 2020, link. |
| F Vicentini, N Pedrocchi, M Beschi, M Giussani, N Iannacci, P Magnoni, ..., Piros: Cooperative, safe and reconfigurable robotic companion for cnc pallets load/unload stations , Bringing innovative robotic technologies from research labs to industrial …, 2020, link. |
| L Roveda, M Forgione, D Piga, Robot control parameters auto-tuning in trajectory tracking applications , Control Engineering Practice 101, 104488, 2020, link. |
| M Forgione, D Piga, A Bemporad, Efficient calibration of embedded MPC , IFAC-PapersOnLine 53 (2), 5189-5194, 2020, link. |
| M Forgione, D Piga, Model structures and fitting criteria for system identification with neural networks , 2020 IEEE 14th International Conference on Application of Information and …, 2020, link. |
| B Mavkov, M Forgione, D Piga, Integrated neural networks for nonlinear continuous-time system identification , IEEE Control Systems Letters 4 (4), 851-856, 2020, link. |
| L Roveda, M Forgione, D Piga, Two-stage robot controller auto-tuning methodology for trajectory tracking applications , IFAC-PapersOnLine 53 (2), 8724-8731, 2020, link. |
| M Mejari, VV Naik, D Piga, A Bemporad, Identification of hybrid and linear parameter‐varying models via piecewise affine regression using mixed integer programming , International Journal of Robust and Nonlinear Control, 2020, link. |
| M Mejari, V Breschi, D Piga, Recursive bias-correction method for identification of piecewise affine output-error models , IEEE Control Systems Letters 4 (4), 970-975, 2020, link. |
| V Breschi, M Mejari, Shrinkage strategies for structure selection and identification of piecewise affine models , 2020 59th IEEE Conference on Decision and Control (CDC), 1626-1631, 2020, link. |
| M Mejari, V Breschi, VV Naik, D Piga, A bias-correction approach for the identification of piecewise affine output-error models , IFAC-PapersOnLine 53 (2), 1096-1101, 2020, link. |
| G Maroni, Optimal Asset Allocation, a Data-Driven Feedback Control Approach , Università degli studi di Bergamo, 2020, link. |
| G Maroni, F Previdi, V Uberto, M Emidoro, SM Savaresi, M Campana, ..., Dispositivo contateste e metodo di processamento di immagini digitali , , 2020, link. |
| L Cannelli, F Facchinei, V Kungurtsev, G Scutari, Asynchronous parallel algorithms for nonconvex optimization , Mathematical Programming 184 (1), 121-154, 2020, link. |
| L Cannelli, F Facchinei, G Scutari, V Kungurtsev, Asynchronous optimization over graphs: Linear convergence under error bound conditions , IEEE Transactions on Automatic Control 66 (10), 4604-4619, 2020, link. |
| AA Shahid, L Roveda, D Piga, F Braghin, Learning continuous control actions for robotic grasping with reinforcement learning , 2020 IEEE International Conference on Systems, Man, and Cybernetics (SMC …, 2020, link. |