Nicola Russo

Nicola Russo PhD

PhD Candidate at University of West London, working on the application of Spiking Neural Networks in Neuromorphic Robotics. The project aims to incorporate a reward signal in a Robotic Goalkeeper System, to reinforce the prediction of an incoming ball in case of success. The prediction is made using a visual input from a Dynamic Video Sensor, connected to a SpiNNaker board where the SNN is running. The reward signal is used to fix the successful weights of the previous ball trajectory in case the ball is blocked the robotic arm, where the touch sensor is placed.

BSc in Computer Science at University of Molise, Italy, 2014. MSc in Security of Software Systems at University of Molise, Italy (First Class Honours) 2019.

Previously working on Knowledge Transfer Partnership project on NLP and AI technologies for Q&A services at Middlesex University London, cooperating with Kare Knowledgeware Ltd (2019).

BSc Thesis: Human Faces Pattern Recognition for kinship recognition in a set of human faces. The project aimed build a Neural Network to recognise kinship in a set of high quality pictures of people, having the same ethnicity (Albanian) and living in a small city of south Italy.

MSc Thesis: Gender Discrimination and Privacy Violation on Twitter. In this project, controlled Twitter Users with different features in the profile (gender, nation, ethnicity, age) received different advertisements that was used to train a classifier to choose the kind of ads to present (replication of the Twitter classifier) with the purpose to verify the Twitter algorithm transparency for Privacy and Discrimination.

Publications

Russo, N.; Madsen, T.; Nikolic, K. “An Implementation of Communication, Computing and Control Tasks for Neuromorphic Robotics on Conventional Low-Power CPU Hardware”. Electronics 2024, 13, 3448.
DOI: 10.3390/electronics13173448

Russo, N.; Yuzhong, W.; Madsen, T.; Nikolic, K. “Pattern Recognition Spiking Neural Network for Classification of Chinese Characters”. European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN 2023)
DOI: 10.14428/esann/2023.ES2023-174

Russo, N.; Huang, H.; Donati, E.; Madsen, T; Nikolic, K. “An Interface Platform for Robotic Neuromorphic Systems”. Chips (2023), 2, 20-30.
DOI: 10.3390/chips2010002

Russo, N.; Huang, H.; Nikolic. K. “Live Demonstration: Neuromorphic Robot Goalie Controlled by Spiking Neural Network”. IEEE Biomedical Circuits and Systems Conference (BioCAS 2022).
DOI: 10.1109/BioCAS54905.2022.9948668

Other Collaborations

Ivanova, M.L.; Russo, N.; Djaid, N.; Nikolic, K. “Application of machine learning for predicting G9a inhibitors”. Digit. Discov. 2024, 3, 2010-2018.
DOI: 10.1039/D4DD00101J

Donati, E.; Chousidis C.; de Melo Ribeiro H.; Russo, N. “Classification of speaking and singing voices using bioimpedance measurements and deep learning”. Engineering Applications of Artificial Intelligence, (2023).
DOI: 10.1016/j.jvoice.2023.03.018