Research Assistant

ger

Department of Bioengineering
Imperial College London
White City Campus
W12 0BZ London, UK
Office: 419 UREN - Sir Michael Uren Building
Email: gerolamo.carboni16@imperial.ac.uk

MSc in Biomedical Engineering (Bioinformatics), Università Campus Bio-Medico di Roma
BSc in Industrial Engineering , Università Campus Bio-Medico di Roma

 

About me

My name is Gerolamo Carboni and I am currently working as Research Assistant in the Department of Bioengineering of Imperial College London, as part of the Human-Robotics Group (HRG). I am passionate about science and strongly believe that, along with technological innovation, scientific progress can drastically improve human’s quality of life. I am particularly fascinated by advancements in human-machine interfacing and robotics, which open up possibilities to restore or augment human sensory and motor functions, and to implement humanlike capabilities in robots.

These interests have led me first to study Industrial Engineering (for the Bachelor Degree) and then Biomedical Engineering, where I obtained an MSc cum laude from Campus Bio-Medico University in Roma, a university with special strength in Biomedical Engineering. During these studies I specialised in Robotics, Machine Learning, Healthcare Technologies and Neuroscience.

During these years working as RA in the HRG I implemented a game theory framework for reactive control to assist humans in physical training: a robot equipped with the proposed adaptive game-theory based control both provides optimal assistance to the human partner in training arm reaching movements and adapts its assistance by seamlessly identifying this partner’s level of effort. More importantly, I was able to  participate in the EPSRC MOTION, EU 2020 COGIMON and PH-Coding projects, getting increasingly interested in human motor control, multisensory integration and human-human/robot interaction.

My current research

I want to investigate whether and how humans can modulate their mechanics (e.g. through muscle co-contraction) in order to improve their sensing, and how this influences human motor control. This important morphological computation aspect of neuromechanics has been little studied. It will bring important insight into human sensorimotor learning and control, and may yield critical inputs to robotics research. I want to elucidate the mechanisms by which humans use mechanical impedance and specific movements during haptic exploration in order to identify the environment’s physical features efficiently.

I am  further developing computational modelling to study how humans modify their exploratory strategies as a function of the sensory information originating from the interaction with the object being manipulated. These computational algorithms can be implemented on robot manipulators in order to efficiently identify objects’ features, with potential cutting-edge applications in robot-assisted diagnostics and surgery.

ResearchGate profile: https://www.researchgate.net/profile/Gerolamo_Carboni

Awards

• “CityNext Microsoft Country Partner of the Year Award 2014 – Italy” for SIM (Sviluppo Integrazione Multimediale) project.

Teaching experiences

• Human Neuromechanical Control and Learning, Imperial, instructor: Prof. E. Burdet (Spring 2017 & 2018)
• Introduction to Robotics, Imperial, instructor: Prof. E. Burdet & Prof. P. Kormushev (Autumn 2017 & 2018)Teaching experiences

Selected publications

Differential game theory for versatile physical human–robot interaction, Y Li, G Carboni, F Gonzalez, D Campolo, E Burdet, Nature Machine Intelligence, 2019 1 (1), 36-43
 
For motion assistance humans prefer to rely on a robot rather than on an unpredictable human, E Ivanova, G Carboni, J Eden, J Krüger, E Burdet, IEEE Open Journal of Engineering in Medicine and Biology, 2020, 1, 133-139.
 
Improving Tracking through Human-Robot Sensory Augmentation, Y Li, J Eden, G Carboni, E Burdet, IEEE Robotics and Automation Letters, 2020, 5 (3), 4399-4406.
 
Short time delay does not hinder haptic communication benefits, E Ivanova, J Eden, S Zhu, G Carboni, A Yurkewich, E Burdet, IEEE Transactions on Haptics, 2021, 
14(2), 322-327.