Computational aesthetics: Coming from a computer and cognitive science background, my research interest has drifted towards Neuroaesthetics and applications of its finding to artificial intelligence. My goal is to improve our understanding of what is seen as beautiful to the human visual system. Considering beauty as a physiological reaction triggered by aesthetically pleasant visual information, I hope to define factors which could allow to predict aesthetic pleasantness for a given population. I consider my work as highly inter-disciplinary, as I take into consideration results from neuroscience, psychophysics, computer vision and also expertise in visual arts.
Smartphones & wearable techs: As an undergraduate student in computer science, my first development project was for the first wave of Android phones, which was already so promising in its infancy. More recently, I have ported my research findings about aesthetic classification of photos into a prototype app embedding Tensorflow deep neural networks for Qualcomm AI developers contest. With smartphones gaining significantly processing power, I am hoping to see more artificial intelligent systems running directly on the phones so they can be companions that improve users’ lives without compromising their privacy by sending their data to a third party.
I completed an undergraduate degree in Computer Science at Université du Havre, France before pursuing my studies in Software Development (BSc Hons) at IT Carlow, Ireland. The latter gave me an insight into Artificial Intelligence which led me to a Master’s degree in Cognitive Science at University College Dublin, Ireland.
While my undergraduate training focused on software development and theoretical computer science, I have worked on research projects on linguistics, gestural behavior and the different effects of multilingualism during my MSc. The previous experiments also had for purpose to use novel ways to measure gesture using a Microsoft Kinect camera, in order to make the experimental setup lighter and reduce the effect on partcipants’ behaviour. My PhD work has involved extensive mining of online data to study visual preferences in several internet communities, to develop an AI that learns those visual preferences and reproduce aesthetic judgements across different visual media.
My every day programming language is Python, that I have used to develop desktop software on both front and back-end. My previous employment involved developing web applications using Django, JavaScript, jQuery… Nowadays, I primarily use Python to write scripts for my research work and extensively exploit the main scientific libraries such as OpenCV, SciPy, Tensorflow for feature extraction on images and machine learning.
I am also experienced in Java, whether it is the traditional version or for Android. I have been taught programming in Java and worked on several Android projects.
Beside those two languages, I have also robust notions of C, PHP, Lisp and Prolog.
