A5102718872- Space exploration and regulation
- Fault Detection and Control Systems
- Spacecraft Design and Technology
- Space Science and Extraterrestrial Life
- Real-Time Systems Scheduling
- Adversarial Robustness in Machine Learning
- Distributed systems and fault tolerance
- Machine Fault Diagnosis Techniques
- Network Time Synchronization Technologies
- Oil and Gas Production Techniques
- Reliability and Maintenance Optimization
- Bacillus and Francisella bacterial research
- Time Series Analysis and Forecasting
- Satellite Communication Systems
- Cybersecurity and Cyber Warfare Studies
- Opportunistic and Delay-Tolerant Networks
Cornell University
2024
Accenture (Switzerland)
2020
Accenture (Italy)
2019
The increased utilization of small satellites, particularly CubeSats, has been propelled by technological advancements and the widespread incorporation Commercial Off-The-Shelf (COTS) components. This transition ushered in a paradigm faster more cost- effective missions, giving rise to novel trends such as Internet Space Things (IoST) Service (SaaS) space domain. However, this shift comes with concomitant spacecraft architecture complexity, expanding attack surface for potential cyber...
Abstract Predictive Maintenance concerns the smart monitoring of machine to avoid possible future failures, since because it is better intervene before damage occurs, saving time and money. In this paper, a methodology based on Machine learning approach presented applied real cutting machine, woodworking machinery in industrial group, producing accurate estimations. This kind strategy important deal with maintenance problems given ever increasing need reduce downtime associated costs. The...
Spacecraft are among the earliest autonomous systems. Their ability to function without a human in loop have afforded some of humanity's grandest achievements. As reliance on autonomy grows, space vehicles will become increasingly vulnerable attacks designed disrupt processes-especially probabilistic ones based machine learning. This paper aims elucidate and demonstrate threats that adversarial learning (AML) capabilities pose spacecraft. First, an AML threat taxonomy for spacecraft is...
The New Space era exacerbates the precarious cybersecurity conditions of space systems. An intrusion detection strategy that leverages a spacecraft's physics emerges as defense against evolving cyberthreats, aiming to secure assets with an innovative, resource-constrained approach.
Condition-based monitoring is a key element to minimize plant upsets and production losses, guaranteeing at the same time safety asset integrity, with final goal of improving operational excellence. A challenge for this purpose capability anticipate unexpected behaviors, such as undesired trends or spikes in sensor measurements, temperatures vibrations, which might lead equipment failures. For goal, we implemented some innovative Deep Learning algorithms predict future trend variables...