Cima, L., Miaschi, A., Trujillo, A., Avvenuti, M., Dell'Orletta, F., & Cresci, S. (2025, April). Contextualized counterspeech: Strategies for adaptation, personalization, and evaluation. In Proceedings of the ACM on Web Conference 2025

AI-generated counterspeech offers a promising and scalable strategy to curb online toxicity through direct replies that promote civil discourse. However, current counterspeech is one-size-fits-all, lacking adaptation to the moderation context and the...

A. Gentili, M. Bresciani, F. Ruscio, S. Tani, A. Caiti and R. Costanzi “Detection and classification of man-made objects for the autonomy of underwater robots”. IFAC-PapersOnLine, 56(2), 5741-5746.

Recent developments in marine technologies allow underwater vehicles to perform survey missions for data collection in an automatic way. The scientific community is now focusing on endowing these vehicles with strong perception capabilities, aiming at...

F. Ruscio, S. Tani, A. Gentili, G. Liverani, A. Bucci, A. Topini, A. Ridolfi and R. Costanzi "Towards Multi-Class Segmentation of Seafloor Images with Posidonia Oceanica." OCEANS 2025 Brest. IEEE, 2025.

Posidonia oceanica meadows are key components of the Mediterranean marine ecosystem, offering crucial ecological services such as carbon sequestration, sediment stabilization, and habitat for diverse marine species. Increasing anthropogenic pressures...

A. Gentili, E. D’Agostino, C. Pieri, M. Telesca, L. Pollini, A. Caiti and R. Costanzi “A Multi-Beam Forward-Looking Sonar simulator based on Unity3D”. In: 2024 IEEE International Workshop on Metrology for the Sea; Portorose, Slovenia, 2024, pp. 558

The development and testing of robust underwater acoustic technologies for applications such as environmental monitoring, inspection of underwater structures, as well as applications in the fields of geology and marine biology, typically require large...

A. Gentili, F. Cagol, F. Ruscio and R. Costanzi “Comparison of Deep Learning strategies for the identification of artificial objects in underwater environment”. OCEANS 2024 - Halifax, Halifax, NS, Canada, 2024, pp. 01-06.

In the last decades, the development of Autonomous Underwater Vehicles (AUVs) has advanced significantly, focusing on their ability to autonomously navigate and collect data in underwater environments. However, these tasks are often predefined and...

Toward Bio-Inspired Autonomous Navigation: Long-Range Marine AUV Navigation

Tireless travellers: sea turtles swim continuously during homing movements

C. Sandri, R. Di Rienzo, F. Baronti, R. Roncella, R. Saletti, "Electrochemical Impedance Spectroscopy of Commercial Sodium-Ion Batteries", ApplePies 2025, presented, to be published

Sodium-ion batteries are gaining attention as an alternative to lithium-ion batteries, because of the more abundant and less toxic ma- terials used for their construction. However, this technology is novel and requires extensive experimental research...

C. Bua, F. Fiorini, D. Adami, S. Giordano, M. Pagano: "Fuzzy-Augmented Neural Network for Reducing Computational Complexity: A Demonstration in Microclimate Prediction for Smart Agriculture", IEEE Internet of Things Journal, June 2025.

Climate change poses significant challenges, particularly in agriculture, where extreme weather events demand more efficient and resilient systems, such as smart greenhouses. These controlled environments require predictive solutions to optimize...

C. Bua, L. Borgianni, D. Adami, S. Giordano: “Reinforcement Learning-Driven Digital Twin for Zero-Delay Communication in Smart Greenhouse Robotics”, Agriculture 2025, June 2025.

This study presents a networked cyber-physical architecture that integrates a Reinforcement Learning-based Digital Twin (DT) to enable zero-delay interaction between physical and digital components in smart agriculture. The proposed system allows...

C. Bua, F. Fiorini, M. Pagano, D. Adami, S. Giordano: “Low-Complexity Microclimate Classifica-tion in Smart Greenhouses: A Fuzzy-Neural Approach”, Future Internet 2025, May 2025.

Maintaining optimal microclimatic conditions within greenhouses represents a significant challenge in modern agricultural contexts, where prediction systems play a crucial role in regulating temperature and humidity, thereby enabling timely...

C. Bua, D. Adami, S. Giordano: “What Is the Optimal Sampling Time of Environmental Parameters? Fourier Analysis and Energy Harvesting to Reduce Sensors Consumption in Smart Greenhouses”, AgriEngineering 2025, March 2025.

Smart greenhouses offer crucial solutions for reducing our atmospheric impact and resource waste. However, two fundamental challenges persist in their implementation, massive energy consumption and a high level of human intervention, particularly for...

C. Bua, L. Borgianni, D. Adami, S. Giordano: "Digital Twin for Remote Control of Robotic Arm via Wearable Glove in Smart Agriculture", 2025 IEEE Wireless Communications and Networking Conference (WCNC), March 2025.

Smart agriculture is experiencing rapid transformation through innovative Agritech solutions. Robotic Arms (RAs) and Sensor-equipped Wearable Gloves (SWGs) are critical tools for performing high-precision tasks in controlled environments like...

C. Bua, F. Fiorini, D. Adami, S. Giordano: “Cloud-Trained Neural Networks on Microcontrollers for IoT Applications: an Educational Perspective with LittleBits”, IEEE Symposium on Computers and Communications (ISCC), July 2025.

The integration of machine learning on microcontrollers at the extreme edge of the network is gaining significance for various Internet of Things applications. This paradigm shift enables real-time data processing and decisionmaking directly on the...

F. Fiorini, R. G. Garroppo, M. Pagano, "Quantum Repeaters to Extend the Communication Range: Present and Future Perspectives", IEEE Communications Magazine 2025

Long-distance quantum communication faces significant challenges due to photon loss and operational errors in fiber optic channels. Quantum repeaters (QRs) offer a promising solution by extending the communication range and enabling secure exchange of...

F. Perrone, L. Lemmi, C. Puliafito, A. Virdis and E. Mingozzi, "A Computing-Aware Framework for Dynamic Traffic Steering in the Edge-Cloud Computing Continuum," 2025 34th International Conference on Computer Communications and Networks (ICCCN)

The rise of technologies like AI and IoT has increased the need for high-performance, low-latency computing. Edge computing addresses this by extending cloud resources closer to client applications. Effective workload distribution across this...

Mystkowska, G., Monopoli, M., Nannipieri, P., Zulberti, L., Codinachs, D. M., & Fanucci, L. (2025). Hardware Platforms Enabling Edge AI for Space Applications: A Critical Review. IEEE Access, vol. 13, pp. 143939-143956.

Abstract: Artificial Intelligence is an emerging technology in the space industry as it enables real-time data processing and autonomous navigation. We aim to facilitate mission development by providing an extensive state-of-the-art review. We analyze...

Monopoli, M., Biondi, M., Moranti, S., Nannipieri, P., & Fanucci, L. (2025). Toward Reliable Onboard AI in Space: A Fault-Tolerant Soft GPU-Based System-on-Chip. IEEE Transactions on Very Large Scale Integration (VLSI) Systems.

Abstract: Artificial intelligence (AI) is becoming increasingly relevant for space applications, reducing reliance on high-bandwidth downlinks. Its use, however, has primarily been demonstrated in low Earth orbit (LEO) using commercial off-the-shelf...

Pavirani, L., Bove, P., & Coro, G. (2025, June). "Ecosystem Risk Assessment Through Stressor Concurrency Identification: A Comparative Analysis". In OCEANS 2025 Brest (pp. 1-6). IEEE.

In Marine Science, ecosystem risk assessment is a process that integrates data to estimate the potential impact of harmful and fragile forces (stressors) on the ecosystem. Nowadays, the management of marine ecosystems is increasingly complex due to...

Pavirani, L., Bove, P., & Coro, G. (2025, June). "Ecosystem Risk Assessment Through Stressor Concurrency Identification: A Comparative Analysis". In OCEANS 2025 Brest (pp. 1-6). IEEE.

In Marine Science, ecosystem risk assessment is a process that integrates data to estimate the potential impact of harmful and fragile forces (stressors) on the ecosystem. Nowadays, the management of marine ecosystems is increasingly complex due to...