Kevin Michalewicz

Kevin Michalewicz

Research Postgraduate

Imperial College London

Biography

I am currently a PhD student at Imperial College London under the supervision of Barbara Bravi and Mauricio Barahona. In particular, I have the privilege of being a President’s PhD scholar at the Department of Mathematics.

I obtained my engineering degree at the French Grande École IMT Atlantique and my Master’s degree in signal processing (SISEA) at Université de Rennes I in the context of a double degree agreement with Argentina. There I studied electronic engineering at the Faculty of Engineering of the University of Buenos Aires. I also taught two physics courses: Electricity and Magnetism for two years and Quantum Mechanics for half a year.

In my last work experience I have been a gravitational lens deconvolution and PSF intern working at LASTRO (Laboratory of Astrophysics, École Polytechnique Fédérale de Lausanne, Switzerland) under the supervision of Frédéric Courbin and Cecilia Galarza.

Furthermore, I did an internship at CEA Paris-Saclay (Alternative Energies and Atomic Energy Commission) in the CosmoStat Laboratory in 2021. My project was about the study of astrophysical image reconstruction using neural networks.

Download my curriculum vitae.

Interests
  • Machine/Deep Learning
  • Antibody design
  • Signal Processing
  • Astrophysics
Education

  • PhD in Mathematics, 2022–Present

    Imperial College London

  • MSc in Signal Processing (SISEA), 2021–2022

    Université de Rennes I

  • Engineer’s Degree, 2020–2022

    IMT Atlantique

  • Electronic Engineering Degree, 2017–2022

    Universidad de Buenos Aires

Experience

 
 
 
 
 
Graduate Teaching Assistant (GTA)
Imperial College London
Jan 2023 – Present London, United Kingdom
  • Tutorial leader in Data Analysis Tools for MRes students (Autumn 2023).
  • Teaching Assistant in Statistics A and Introduction to Computation (Autumn 2023).
  • Script marking and exam invigilation in subjects of the Department of Mathematics.
 
 
 
 
 
Gravitational Lens Deconvolution & PSF Intern
EPFL
Apr 2022 – Sep 2022 Switzerland
My Master’s final internship was focused on gravitational lens deconvolution & PSF generation. I worked at EPFL’s Laboratory of Astrophysics (LASTRO). My supervisors were Frédéric Courbin (EPFL) and Cecilia Galarza (FIUBA).
 
 
 
 
 
Deep Learning Intern
CEA
Apr 2021 – Jul 2021 Paris, France
The internship took place in the CosmoStat laboratory at CEA, an interdisciplinary research group at the interface between cosmology and statistical methods. My supervisors were Jean-Luc Starck and Zaccharie Ramzi. I studied and implemented different types of neural networks such as Learnlets and U-nets for astrophysical image reconstruction. In particular, the generalisation problem was addressed.
 
 
 
 
 
Student Teaching Assistant
Facultad de Ingeniería - Universidad de Buenos Aires
Mar 2018 – Oct 2020 Buenos Aires, Argentina
I taught the subjects Physics II (Electricity, magnetism and thermodynamics) and Physics III (Quantum physics, statistical mechanics and semiconductor theory).

Awards

President’s Scholarship
Imperial College London Oct 2022
The President’s PhD Scholarships allow students to undertake a research project of their choosing with the support of an excellent supervisor, alongside cohort-building opportunities with other President’s PhD Scholars. This competitive scheme has higher than usual eligibility requirements, attracting candidates that show excellent academic performance and promising research potential. We accept applications from talented candidates from Imperial College London, the UK and worldwide.
Eiffel Excellence Scholarship 2020 (Master)
Campus France (French Government) Apr 2020
The Eiffel Excellence Scholarship program is a system developed by the Ministry of Foreign Affairs in order to enable French higher education institutions to attract the best international students to their degree programs at Master or Doctorate level.
Distinguished Student (2015, 2017, 2022 & 2023)
Universidad de Buenos Aires (UBA) Nov 2015 – Nov 2023
This award is given annually by the University of Buenos Aires (UBA) to students who have been recognised for their outstanding academic work and performance by entities outside the University; who have received awards, honours or recognition from other university institutions, organisations, academics, national, foreign or international bodies of the highest prestige. In this way, the aim is to stimulate the development of the members of the community of the University of Buenos Aires.

Projects

*
All Antibody Design Deep Learning Signal Processing Embedded Systems
ANTIPASTI
ANTIPASTI is a Python Deep Learning method that predicts the binding affinity of antibodies from their three-dimensional structure.
Code Website Paper (Michalewicz et al. 2023)
STARRED
STARlet REgularized Deconvolution (STARRED) is a Python two-channel deconvolution method powered by Starlet regularization and JAX automatic differentiation. It uses a Point Spread Function (PSF) narrower than the original one as kernel.
Code Science cases Website Paper (Michalewicz et al. 2023) Paper (Millon et al. 2024)
Everyday life audio stream detector
Model for domestic sounds classification. Third year project of the engineering degree at IMT Atlantique.
Code
Learnlets
Comparison between Learnlets, a neural network that learns filter banks in a denoising setting with backpropagation and gradient descent, and U-nets.
Code Paper (Ramzi et al. 2022) Paper (Akhaury et al. 2022)
Class-D Amplifier
Design and validation of a Class-D audio amplifier.
PDF (Spanish)
3D printing filament drying system
Academic project in Argentina. Design and construction of a functional humidity sensor.
Code

Recent Publications

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Martin Millon, Kevin Michalewicz, Frédéric Dux, Frédéric Courbin, Philip J. Marshall (2024). Image deconvolution and PSF reconstruction with STARRED: a wavelet-based two-channel method optimized for light curve extraction.

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Kevin Michalewicz, Mauricio Barahona, Barbara Bravi (2023). ANTIPASTI: interpretable prediction of antibody binding affinity exploiting Normal Modes and Deep Learning.

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Kevin Michalewicz, Martin Millon, Frédéric Dux, Frédéric Courbin (2023). STARRED: a two-channel deconvolution method with Starlet regularization. Journal of Open Source Software.

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Utsav Akhaury, Jean-Luc Starck, Pascale Jablonka, Frédéric Courbin, Kevin Michalewicz (2022). Deep Learning-based galaxy image deconvolution. Frontiers in Astronomy and Space Sciences - Astrostatistics.

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Zaccharie Ramzi, Kevin Michalewicz, Jean-Luc Starck, Thomas Moreau, Philippe Ciuciu (2022). Wavelets in the deep learning era. Journal of Mathematical Imaging and Vision.

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