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cv.yaml
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name: "Auguste Baum"
label: "MSc graduate from EPFL: ML, InfoSec, Software engineering"
image: "assets/noir2-lowqual.jpg"
email: "auguste.baum@pm.me"
phone: "+33 6 42 89 41 43"
url: "augustebaum.github.io"
github: "augustebaum"
linkedin: "auguste-baum"
work:
- date: Dec.~2023---Now
role: |
Full-stack developer
place: |
#link("https://resilio-solutions.com/")[Resilio], Paris (remote)
description: |
- Investigated performance issues in Resilio's infrastructure, improving request-response time by a factor of 2.
- Improved Resilio's testing infrastructure, cutting backend test time by a factor of 15.
- date: July~2023---Nov.~2023
role: |
Participant in #link("https://discourse.nixos.org/t/summer-of-nix-2023/27067")[Summer of Nix 2023]
place: |
#link("https://opencollective.com/nixos")[NixOS Foundation], Paris (remote)
description: |
- Developed #link("https://nixos.org/")[Nix] package and module for open-source projects, of which #link("https://github.com/ngi-nix/ngipkgs/issues/2")[Pretalx] and #link("https://github.com/ngi-nix/ngipkgs/issues/6")[Rosenpass].
- Discovered #link("https://www.remotemobprogramming.org/")[mob programming], a low-latency work technique enabling fast skill improvement.
- date: Sept.~2022---March~2023
role: AI research intern
place: |
#link("https://research.swisscom.ai/")[Swisscom Digital Lab], Lausanne
description: |
- Conducted research project on explainability of AI for big-data tabular datasets.
- Developed reproducible research pipeline using #link("https://pytask-dev.readthedocs.io/")[`pytask`].
- date: 2021---2022
role: Co-founder & CTO
place: |
#link("https://resilio-solutions.com/")[Resilio], Lausanne
description: |
Built the backend of #link("https://resilio-solutions.com/services/tech/")[Resilio Tech], an LCA tool for digital sobriety consultancy, in Django.
- date: 2020---2021
role: |
#link("https://theshiftproject.org/en/article/lean-ict-our-new-report/")[Digital Sobriety] consultant
place: Zero Emission Group, EPFL, Lausanne
description: |
- Developed automatic PowerPoint pipeline in Python, speeding up the auditing process by 30%.
- Co-authored reports on environmental impact of digital technology in multinational companies.
education:
- date: 2020---2023
role: MSc Data Science
place: EPFL, Lausanne
description: |
ML, information security and big data methods. MSc thesis on Explainable AI.
- date: 2017---2020
role: BSc Mathematics & Statistics and Physical Chemistry
place: UCL, London
description: |
First class Honours. Dissertation on Machine Learning for chemical property prediction.
- date: 2016---2017
role: |
#link("https://en.wikipedia.org/wiki/Classe_pr%C3%A9paratoire_aux_grandes_%C3%A9coles")[Classe préparatoire]
place: Lycée Saint-Louis, Paris
description: |
Admitted in PC#super[\*]. Foundations of Physics, Chemistry, Mathematics and Computer science.
projects:
- date: 2022---2023
role: |
MSc project: "Path regularization for continuous counterfactual explanations"
place: Swisscom & EPFL, Lausanne
description: |
Developed an AI regularization technique to produce high-quality explanations of neural network predictions. Supervised by #link("https://www.epfl.ch/labs/lts4/people/people-current/frossard/")[Prof.~Pascal Frossard] and #link("https://www.researchgate.net/profile/Daniel-Dobos-2")[Dr~Daniel Dobos].
- date: "2022"
role: |
Semester project: "D-voting"
place: DEDIS lab, EPFL, Lausanne
description: |
Contributed to #link("https://github.com/dedis/d-voting")[d-voting], a blockchain-based electronic voting system.
- date: "2021"
role: |
Machine learning project: #link("https://github.com/CS-433/cs-433-project-2-vortexnco")["Automatic detection of available area for rooftop solar panel installations"]
place: EPFL, Lausanne
description: |
Built a neural network model to detect the empty space on rooftops in satellite images.
- date: "2020"
role: |
BSc project: "Machine Learning methods for Property Prediction"
place: UCL, London
description: |
Reviewed recent approaches to chemical property prediction with machine learning.
skills:
- name: Functional programming
level: Know the basics
keywords: ["Haskell", "Scala"]
- name: Object-oriented programming
keywords: ["Python", "Java"]
- name: ML / Data
keywords: ["PyTorch"]
- name: Big data
keywords: ["Spark"]
- name: Software development
keywords: ["Nix", "Docker", "Git", "Vim", "Rust", "Go"]
- name: Scientific computing
keywords: ["Matlab", "Mathematica", "Sage"]
- name: Web development
keywords: ["HTML", "CSS", "Django", "React"]
# - name: Miscellaneous
# keywords: ["Vim", "Rust", "Go"]
languages:
- language: English
fluency: native
- language: French
fluency: native
- language: Spanish
fluency: B2
- language: Japanese
fluency: basic