Meet: Dr Antonio Forte

Antonio’s academic journey began in Lecce, a city in southern Italy, where he studied at the University of Salento for his Bachelor and MSc in Mechanical Engineering, and a Master’s in Signal Processing. After completing his Masters, he was drawn to London by a desire to explore music and art. ‘I have always loved the arts, and London is a vibrant place, full of it.’

As part of his move to London, Antonio also chose to pursue a PhD in Mechanical Engineering at Imperial College London. The idea was that by doing a PhD, he would be able to pay his rent whilst having some flexibility to also dedicate some time to learn and absorb all the city had to offer on the artistic side. Having moved to London with a love for creativity, Antonio also developed a very strong love for science during his PhD, where he was investigating the biomechanics of the human brain. Afterwards, he chose to further pursue a scientific career.  

Though he likes to keep his world of work and creativity relatively separate, Antonio is still active on both sides. For example, he is still a musician and maintains his love of music as a composer, multi-instrumentalist and sound engineer. After having gigged extensively around the UK, Europe and the US (eg at SXSW 2017), he currently performs in a new project with his wife. He has also pulled together colleagues to form the Engineering Band (more information on that soon!). Furthermore, he is curious about what cutting edge AI models can produce in the arts, including in music, but also in mechanics and robotics, as an inspiring and complementary tool. 

His first encounter with machine learning methods came as Post-Doctoral Researcher in the Bioengineering Department at Imperial College London where he trained as a neuroscientist. Interest in sound took on a professional, scientific turn as Antonio explored at how humans perceive and decode sound, especially in noisy environments. He found machine learning to be an invaluable tool in categorizing the extremely noisy and weak EEG and EMG signals, and it allowed him to dig into the data more powerfully. Reflecting on the AI influence in his post-doctoral work, ‘it came because we needed it. There was no other way to analyse the data… It came as an aid to my research, and I lived with it, I used it in many other ways.’ 

Antonio was awarded the Global Marie Curie Fellowship and moved to Harvard University for three years to join the Bertoldi Group. His research focus returned to mechanical topics, including mechanical metamaterials and soft robotics. He transferred his expertise with AI from his time at Imperial to mechanics, finding that it helped help to speed up certain processes and solve ill-posed, inverse design problems, mainly on robotic matter that can shape morph. For example, he demonstrated how an extremely simple Neural Network architecture, trained on a small subset of finite element simulations, can solve a large (2^100 possible designs) inverse problem, and provide optimal designs to fabricate inflatable soft membranes that can shape shift when pressurised. These are then used for mechanotherapy applications, to help people recovering faster after a surgical operation by massaging the tissue around the scar, which enhances healing. Another example is a project where he used greedy algorithms to optimise the design of soft origami actuators, which would then reach multiple targets in space with no external motors or cables, only geometrical features instructed by computers.

At the end of his Fellowship in Harvard, he returned to London in late 2021 to join King’s College London and lead the RADlab (Reconfigurable and Adaptive Designs Lab). The focus of the lab is to create disruptive, innovative designs that solve real world problems: from novel robotic grippers to wearable robots.

Antonio has been awarded the UKRI Future Leaders Fellowship, which he spotlights as the biggest achievement of his career so far. The award, which started in June 2024, will support Antonio and his team to work on NARMM – Neural-drive, active, and reconfigurable mechanical metamaterials. NARMM aims to create the first generation of reconfigurable robotic matter that can shape shift on command, guided by human signals. This will be used to create wearable robots that are soft and lightweight, can be seamlessly integrated in garments, improving acceptance and privacy, and are person-specific and customisable. Artificial intelligence will play an important role in the project, helping solve inverse design problems in 3D active mechanical systems for the first time. 

He solidifies the importance of not losing the physical knowledge we have of systems, but suggests we shouldn’t be so close-minded about using new things. They don’t exclude each other; they can be complementary.

‘AI is relatively a new tool in the study of mechanical systems and many in the field look at AI as at an inelegant shortcut to reach a solution. Classically, there is beauty in unravelling the physics behind a phenomenon. That’s an amazing thing, which I fully support and pursue myself everyday. However, I also believe that AI can be used creatively: it can help scientists with alternative solutions, speed up calculations, and create scenarios that are sometimes unthinkable. All this is great, and we should learn to see AI as an ally rather than a competitor. This has the potential to open new paths onto untapped territories.’

• Dr Forte is a Lecturer in Engineering at King’s College and recent recipient of the UKRI Future Leaders Fellowship