Thomas Gaudelet

About me

Hello and welcome!

Let's start off with a few things about me. First fact, I was born near Bordeaux in France, close to the ocean and in the middle of wine vineyards, and I am the second of four siblings. I grew up in various places such as Montauban, Mende, and Perpignan as my parents's professions led us to move regularly. After Highschool, I took an intensive course in Mathematics and Physics in Toulouse at the Lycée Pierre de Fermat. I then entered in one of the top engineering school in France, Ecole Centrale Lyon, while my family was moving to Neuilly-sur-Seine, next to Paris.

After a gap year that notably led me to spend seven months in Japan at the University of Keio, I decided to do my last year of study abroad at the University of Oxford. I have now graduated from Ecole Centrale de Lyon as an engineer and from the University of Oxford with a Master of Science in Applied Mathematics.

My interests lie within the fields of mathematics and computing. I am currently a Ph.D Candidate in Bioinfomatics at University College of London supervised by Professor Natasa Przulj. I investigate biological networks on a topological level aiming to link structure and function using tools from graph theory and machine learning approaches.

Resume

Education

  • 2016-
    Present

    Ph.D Candidate
    University College of London

    Department of Computer Science.
    Supervised by Natasa Przulj
    Title to be set.
  • 2014-
    2015

    Master of Science
    University of Oxford

    Mathematical Modelling and Scientific Computing
    Dissertation: investigated and implemented pattern recognition using multi-layer neural networks, highlighting their robustness.
  • 2011-
    2016

    MEng General Engineering
    Ecole Centrale Lyon

    Developed a software designed to read multimedia files during the first year project. During the second year, studied a solution to optimise the shape of vehicle components based on the level-set method.
  • 2008-
    2011

    Intensive Preparatory Courses
    Lycée Pierre de Fermat, Toulouse

    Grandes Ecoles entry exam preparatory courses: Mathematics, Physics, Computer Science.

Work experience

  • 2016

    R&D Intern
    Fuel3D Technologies

    Investigated and implemented algorithms, using Matlab and C++, to improve on the quality of the reconstruction of three dimensional surfaces using Vision and Photometric Stereo.
  • 2014

    Development Intern
    PathControl

    Developed the user interface of the software of passive magnetic ranging created by PathControl. It involved mainly Matlab and the associated GUI Toolbox.
  • 2013-
    2014

    Research Intern
    Keio University, Tokyo

    Investigated the condensation behaviour of water on PTFE-based coating. The objective was to enhance heat exchanges through the surface. We presented the results at the JSAP conference in Tokyo.
  • 2013

    Trainee
    EDF

    Examined the interest of nanofilms/nanoparticles in energy generation and safety.

Projects

Fuel3D Internship
2016

Three-source Photometic Stereo.
(Report confidential)

Abstract

We investigate different leads to improve photometric stereo for the reconstruction of three-dimensional shape based on a set of input pictures captured with Fuel3D Technologies Limited scanner SCANIFY®.

MSc Dissertation
2015

Short-range Impact of Damage on Object Recognition in a trained Neuronal Network.

Abstract

We investigate the impact of damage on a neuronal network trained to recognise objects. A neuronal network is formed by a set of nodes that represent neurons, and edges that represent the connections between the neurons. To set the stage, we review some existing models that describe the dynamics of individual neurons. We then focus on Integrate-and-Fire (IF) models that we use for this project. We then discuss the numerical method that we use for our model of interacting IF neurons. We then construct our network using a multilayer-network formalism. We consider a simple multilayer network architecture that represents the interactions between the retina and the primal visual cortex (V1) in the brain. We train the system to recognise objects and differentiate between them using the "continuous transformation learning rule", which is based on relative spike times of pre-synaptic and post-synaptic neurons. To highlight the robustness and stability of the trained neuronal network, we simulate damage affecting the connections in the network and measure the performance of the deteriorated systems. A network has good performances if the neurons in the V1 representation differentiate successfully between different objects. In this situation, a subset of the neurons responds strongly to the stimuli corresponding to one object and weakly to the other. Our study provides preliminary insights on the impact of damage on connections between two neuronal subsystems.

Pathcontrol Internship
2014

GUI Development for Passive Magnetic Ranging.
(Report confidential)

Abstract

The Passive Magnetic Ranging, or PMR, is a detection method based on the magnetic field produced by an object one tries to locate. The idea is to drive a magnetic object into the ground and to monitor its magnetic field. Then using the magnetic interferences produced by the target one can calculate its position relatively to the measurement devices. In our case, this allows the user to control the borehole's trajectory in order to achieve, for instance, the interception of the second well. The work entails developping the graphical user interface for PathControl's PMR software. It also involve detailing the method used as well as the software layout and how to use it.

Internship Research
2014

Investigation of Condensation Mode on PTFE-based Coating.

Abstract

The enhancement of heat transfers during condensation is at the core of numerous researches as it will lead to increased efficiencies and productivities for various fields especially for power generation. One of the main solutions explored at the current time is to engineer a surface coating in order to promote dropwise condensation, in opposition of the filmwise condensation generally observed in actual condensing systems. With this goal in mind, we investigate the use of polytetrafluoroethylene-coated (PTFE) surfaces to improve heat transfers.

EDF Internship
2014

Nanotechnologies in Energy Production.
(Report confidential)

Abstract

We present the interest of superhydrophobic and superhydrophilic surfaces for the enhancement of heat transfers. For this purpose, we review the literature on the subject and investigate the impact of these surfaces for two applications: improvement of energy production and improvement of cooling methods. Furthermore, we evaluate different hydrophobic products proposed on the market and try to make out which ones would suit EDF best. Finally, we conduct and expose the results of a study on the effect of a magnetite deposit on a surface's wettability.

Research Project
2013

Shape Optimisation of Vehicle Components using the Level-Set Method.
(Report in french)

Abstract

We investigate shape and topologic optimisation based on the Level-Set method developed by the mathematicians J.A. Sethian adn S. Osher. We start by detailing the theory and the optimisation algorithm. We then illustrate how the method works on a simple 2D case. The algorithm is implemented combining Matlab and Code Aster.

Group project
2012

Creation of a Smart Multimedia Files Manager.
(Report in french)

Abstract

This study project has for goal the development of a multimedia software, that we baptised Tag'n'Link. The project was proposed by the laboratory LIRIS of Ecole Centrale Lyon. LIRIS stands for Computer Science Laboratory for Image Processing and Information Systems (Laboratoire d'Informatique en Image et Systèmes d'Information). LIRIS was developing algorithms to detect concepts and emotions in pictures or music files. An emotion being defined by a degree of positivity (joy/sadness) and a level of activity. A concept is for instance a word or an object, for instance a car in a picture. The idea of the projects was to use these algorithms as a black box and to develop a software around them in order to exploit them. The main noveltie was to use both the algorithm and user tags associated to the media files in order to easily generate playlists, slideshows, and combinations of the two according to a certain degree of similarity.

Get in touch