I have had a distinguished academic career in the field of machine intelligence and technological innovation. In my career, as evidenced in the following paragraphs, I have accumulated unique scientific expertise and experience that provides me with a unique multi-disciplinary position focused on developing novel approaches in machine intelligence to fit their application in other areas and sectors, particularly in health and wellbeing.

I am Professor of Machine Intelligence at Sheffield Hallam University. My role include the leadership of the AI, Robotics and Digital research theme at the Advanced Wellbeing Research Institute. I am based in the Department of Computing, where I am leading the Smart Interactive Technologies (SIT) Research Laboratory, which is conducting internationally renowned research in interdisciplinary applications of machine intelligence, including healthcare and well-being.

My research endeavours have been supported with over £2.7 million by various funders. The main research projects are summarised in the following to evidence my ability to independently conduct ground-breaking research, leadership, capacity to manage large funding and execute interdisciplinary research projects, and a worldwide network of multidisciplinary scientific and industrial collaborators.

My projects can be categorised into two main research and innovation streams: Neuro-developmental Robotics, which is an area of fundamental research on how machines can learn by simulating child-like brains that can be embodied into humanoid robots and then educated and develop their cognitive skills like children; Socially Assistive Robotics, which is an area of societal impact of artificial intelligence and robotics that aims at supporting healthcare and social workers in the care of children, older adults and disabled.

I successfully coordinated a proposal that combines both research streams: the Horizon Europe project “Performance in Robots Interaction via Mental Imagery” (PRIMI), which was awarded €7.3 million for 50 months, from 2023-2027. PRIMI beneficiaries include 4 universities, a research institute and 2 companies, which include leaders in neurophysiology, psychology, machine intelligence, cognitive mechatronics, neuromorphic engineering, and humanoid robotics. The ambitious PRIMI research will realise my vision of a new unifying concept for the next generation of autonomous interaction technologies, capable of more autonomous, faster, safer, and precise interaction with real-time learning and adaptation, thanks to the integration of the capabilities to mentally represent themselves, the physical and social worlds, resemble experiences and simulate actions. As a proof-of-principle of the technological advancement in a relevant scenario, PRIMI will create prototypes of neuromorphic humanoid robots that will be validated in clinical pilot studies of robot-led physical rehabilitation of stroke survivors.

In the neuro-developmental robotics stream, I am the PI of the EPSRC project (202k, 2023-2025) on Autonomous Learning and Development in Embodied Neuromorphic Systems (ALDENS). The ALDENS project aims to establish a novel developmental neuromorphic paradigm by combining developmental robotics and neuromorphic computing. This synergy will overcome the limitations of each paradigm individually. Developmental robotics will provide missing learning mechanisms for neuromorphic spiking neural networks, while neuromorphic computing will offer efficient brain-like resources with an accurate representation of the real world. The project will develop and validate methodologies to create an autonomous, flexible, and scalable artificial brain architecture. Previously, I was PI of the EPSRC project NUMBERS (£101k, 2017-20), which delivered a proof-of-concept of a robot that can learn like children by creating a developmental neurorobotics model of number cognition by imitating human-like learning approaches for recognising number digits.

In the Socially Assistive Robotics stream, I am the PI of the EPSRC project (2022-2024, £400k) I’M-ACTIVE: Intelligent Multimodal Assessment and Coaching Through Identification of Vulnerabilities in older pEople. IMACTIVE aims to create a user-friendly platform for older adults at risk of frailty by integrating machine intelligence and healthcare sensor technologies to tailor the service to the unique needs of older adults, addressing cognitive and physical barriers to increase its acceptability and usage among this population. The project’s focus is on co-designing a smart integrated system that provides continuous, personalized support to help older adults maintain an active and healthy lifestyle. I am a lead scientist of the H2020 project on PErsonalized Robotics as SErvice Oriented applications (PERSEO, €4m, 2021-24), a European doctoral training network to train the new generation of interdisciplinary researchers in intelligent personal robotics. PERSEO academic and industrial partners integrate machine intelligence, computer science, engineering, philosophy, law, and psychology to tackle the technical, social, legal and ethical challenges concerning the creation of personal service robots with a high level of personalisation with respect to each user’s needs and preferences. I am a Co-I of the EPSRC NetworkPlus EMERGENCE (£700k, 2022-25), which is facilitating the creation of a sustainable healthcare robotics eco-system connecting researchers, industry and healthcare providers, in order to build the infrastructure and systems to drive world-class advances in healthcare robotics research and development to support people living with frailty within communities in the UK. Previously, I was the coordinator of the H2020 MSCA-IF CARER-AID (£183k, 2017-2019) that co-created and validated an intelligent robotic solution for the training of children with autism and intellectual disability. A specialised Research and Healthcare institute in Italy (IRCCS Oasi) hosted clinical studies with hospitalised children. The children benefitted from the integration of a robot-assisted training session, learning new skills, which were maintained after 3 months in the follow-up evaluation. Therapists recognised that the robot could reduce their workload while maintaining the efficacy of the intervention. The potential impact of the research was evidenced also by the selection for publication on the EU research website (CORDIS), with results translated into six languages for greater dissemination throughout Europe.