Achille Salaün
Achille Salaün

PhD in Computational Mathematics

Visual Meaning

Bonjour!

My name is Achille, I am French, and throughout my career, I have been committed to developing interpretable AI solutions for real-world problems. Precisely, I aim to build tools that are directly applicable by domain experts, tailored to their practical needs. In particular, I believe that meaningful innovation emerges from interdisciplinary collaboration. New discoveries and ideas hide in the interstices between expert communities and bridging them is essential! Finally, interpretable AI is essential for breaking down technical silos and empowering users with understanding and trust.

For any question or enquiry, feel free to reach out to me at .

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Interests
  • Artificial Intelligence
  • Knowledge Graphs
  • Interpretability
Education

  • PhD in Computational Mathematics

    Institut Polytechnique de Paris

  • Diplôme d'ingénieur (Master)

    Télécom Paris

  • Master's specialisation in Data Science and Engineering

    EURECOM

  • Classe Préparatoire aux Grandes Écoles (MPSI/MP)

    Lycée du Parc

Experience

  1. Consultant

    Visual Meaning (Start-up)
    Bridging the gap between developers and non-technical consultants, I design and prototype software solutions to transform complex corporate data into accessible knowledge graphs that underlie interactive visual maps.

  2. Postdoctoral Researcher

    University of Oxford, IBME
    In collaboration with surgeons, I have developed a Python prototype of an interpretable clinical decision support system to support the decision of accepting or not a kidney transplant with interpretable ML.

  3. PhD Researcher

    Nokia Bell Labs
    During this industrial PhD (CIFRE), I developed pattern matching solutions for alarm prediction and root cause analysis in telecommunication networks. I have delivered a Python root-cause analysis module, which has been transferred to Nokia’s business units. Alternatively, I have produced a theoretical cartography of Hidden Markov Models and Recurrent Neural Networks’ expressivities.

  4. Lab Supervisor

    For two consecutive years, I supervised lab sessions for a course on Scientific Calculus (Master 1) and another one on Image Segmentation with Hidden Markov Models (Master 2) at Télécom SudParis. These courses were respectively coordinated by Yohan Petetin, and Wojciech Pieczynski and Emmanuel Monfrini.

Education

  1. PhD in Computational Mathematics

    Institut Polytechnique de Paris

  2. Diplôme d'ingénieur (Master)

    Télécom Paris

  3. Master's specialisation in Data Science and Engineering

    EURECOM

  4. Classe Préparatoire aux Grandes Écoles (MPSI/MP)

    Lycée du Parc
    French cram school focusing on Maths and Physics
Publications
Achille Salaün, Simon Knight, Laura Wingfield, Tingting Zhu (2024). Interpretable Machine Learning in Kidney Offering: Multiple Outcome Prediction for Accepted Offers. In Scientific Reports.
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Laura Wingfield, Achille Salaün, Aparajita Khan, Helena Webb, Tingting Zhu, Simon Knight (2024). Clinical Decision Support Systems Used in Transplantation: Are They Tools for Success or an Unnecessary Gadget? A Systematic Review. In Transplantation.
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François Desbouvries, Achille Salaün, Yohan Petetin (2023). Expressivity of Hidden Markov Chains vs. Recurrent Neural Networks from a system theoretic viewpoint. In IEEE Transactions on Signal Processing.
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Achille Salaün (2021). Alarm prediction in networks via space-time pattern matching and machine learning.
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Anne Bouillard, Marc-Olivier Buob, Achille Salaün, Maxime Raynal (2020). DIG-DAG: stockage et recherche de motifs dans un flux d'événements. In ALGOTEL.
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Achille Salaün, Anne Bouillard, Marc-Olivier Buob (2020). Demo abstract: end-to-end root cause analysis of a mobile network. In INFOCOM.
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Achille Salaün, Yohan Petetin, François Desbouvries (2019). Comparing the modeling powers of RNN and HMM. In ICMLA.
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Achille Salaün, Anne Bouillard, Marc-Olivier Buob (2019). Space-time pattern extraction in alarm logs for network diagnosis. In MLN.
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Anne Bouillard, Marc-Olivier Buob, Maxime Raynal, Achille Salaün (2018). Log analysis via space-time pattern matching. In CNSM.
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Talks
Interpretable machine learning for graft outcome prediction
Interpretable machine learning for graft outcome prediction

Presentation for Oxford Global

Jan 26, 2023
Prédiction d'alarmes dans les réseaux via la recherche de motifs spatio-temporels et l'apprentissage automatique
Prédiction d'alarmes dans les réseaux via la recherche de motifs spatio-temporels et l'apprentissage automatique

PhD defense

Jul 8, 2021
End-to-end root cause analysis of a mobile network
End-to-end root cause analysis of a mobile network

IEEE INFOCOM 2020

Jul 6, 2020
Coffee Break ☕️

Would you like us to meet around a cup of coffee or a glass of water? Here are some topics I am always happy to chat about!

Naturally, we can chat about research. I would be glad to know more about your current works and answer any of your questions about mine (but you can already start by asking them there 👉 ).
In my spare time, I love drawing on my pen tablet: you can have a look on my creations on Instagram 👉 ! One of my dreams would be to draw my own comic book. Who knows, maybe one day?
I used to do fencing at a competitive level. I also enjoy running from time to time!