Prof. Alessandro Di Nuovo is Professor of Machine Intelligence at the Department of Computing, Sheffield Hallam University. He is the leader of AI, Robotics and Digital for the Advanced Well-being Research Institute. He is the funder and leader of the Smart Interactive Technologies (SIT) Research Laboratory, which has cutting-edge facilities and equipment for advanced machine learning and human-robot interaction experiments.

Prof. Di Nuovo is leading several collaborative research projects in fundamental and applied topics in AI and Robotics, funded by public (European Union, UKRI), private (IBM, NVIDIA) and charities (Sheffield Children Hospital Trust).

His research specialises in cognitive mechatronics and its application to health and wellbeing.

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 by various funders, including UKRI and the European Commission. 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.

Specialist Areas of Interest:

Artificial Intelligence and Robotics