As a Lead Robotics Engineer at Baker Hughes, I apply my expertise in robotics, computer vision, machine learning, data analysis, and data engineering to develop innovative solutions for the energy technology sector. Currently, I lead the Robotics and Control Chapter of the Artificial Intelligence Team at Baker Hughes. I have more than 15 years of experience as a roboticist and AI researcher, working on various projects and challenges in the fields of robotics and control, computer vision, defect detection, multimedia forensics, natural language processing, and remote sensing – and in the industrialization of AI products.

Prior to joining Baker Hughes, I worked as a Scientific Project Officer at the Joint Research Centre of the European Commission, based in Ispra (VA), Italy, where I investigated machine learning and computer vision techniques for multimedia forensics to fight organised cyber crimes.

I am a former EU-FP7 and EU-H2020 Marie Skłodowska Curie Fellow. I was awarded with an Individual Fellowship by the EU-H2020 Research and Innovation programme (“Predictive Robots”, 2019-2021), hosted by Prof. Cecilia Laschi at the BioRobotics Institute of the Scuola Superiore Sant’Anna (Pisa, Italy).

My first Marie Curie fellowship (EU-FP7 Marie Curie Initial Training Network INTRO, “Interactive Robotics”, 2010-2013) was hosted by Prof. Verena V. Hafner at the Adaptive Systems Group, Computer Science Department of the Humboldt-Universität zu Berlin. During my PhD studies within this Marie Curie ITN, I spent a secondment at Umeå University, Sweden. My background is on Computer Engineering (Università degli Studi di Palermo, Italy; Erasmus M.Sc. student at: ETSIIT, Universidad de Granada, Spain). I have been awarded with a Humboldt Post-Doc Scholarship from the Humboldt Graduate School in 2013-2014, and have been working as a post-doctoral researcher at the HU-Berlin from 2014 to 2019 in different EU and German projects.

My academic background focused on the investigation of learning architectures and computational models for artificial systems inspired on infant development and on human brain functioning. I researched a variety of machine learning techniques for implementing these models, including deep neural networks and probabilistic models. I am particularly interested in online learning and reinforcement learning techniques, multi-modal integration, perception and predictive processes. I have worked with different sensing technologies, including standard, multi-spectral and depth cameras, thermal cameras, microphone arrays, IMUs, motion amplification systems for vibration analysis, gas leakage sensors, and non-conventional sensors such as artificial whiskers which I prototyped.

In robotics, I research, apply and productise advanced mechanisms for perception and control on a variety of robotic platforms in industrial settings. My academic research in robotics contributed to the understanding and implementation of capabilities like behaviour recognition and arbitration, tool-use, curiosity-driven exploration behaviours and perception in artificial systems. My  studies on predictive and sensory attenuation processes aimed also at providing insights in the understanding of subjective experiences typical of humans, such as self-awareness, self-other distinction, sense of agency and sense of object permanence, and in the possibility of implementing an artificial Self into robots. My industrial research generates from proof-of-concepts to prototypes of robotics and artificial intelligence tools for various applications, such as robotic inspection for the energy industry and manufacturing industry, internet-of-robotic-things (IoRT), digital twin generation and asset monitoring and maintenance.

I have worked with several robotic platforms, such as quadruped and crawler robots, humanoid robots, mobile platforms, drones, manipulators and micro-farming robots. I designed and developed electronics and hardware of custom underwater and marine drones.

During the last years, I have had the opportunity to collaborate with a wide variety of stakeholders: policy makers, law-enforcement agencies, energy and manufacturing industries, academics from several disciplines, including computer science, mechanical science, engineering, agricultural science, earth observation science, psychologists and cognitive science, philosophy.