Matthieu Simeoni, PhD

Experience

• 

  EPFL

  Sept 2012 - Jul 2014

  • Teaching Assistant « Mathematics I & II »

    Sept 2012 - Jul 2014

  • Welcome Desk EPFL, Rolex Learning Center

    Sept 2012 - Jul 2014
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  IBM

  Aug 2014 - Dec 2019

  Research Data Scientist

  In the Foundations of Cognitive Solutions research group at IBM Zurich, I collaborated with leading minds, including Pr. Paul Hurley, at the intersection of signal processing, data science, statistics, and applied mathematics. My research was geared towards crafting novel signal processing algorithms that optimize data acquisition and the processing chain within large-scale sensor networks. The impact of my work extended across various fields, such as medical imagery, radio-interferometry, sound localisation, and wireless networks, showcasing the versatility and innovation of my work. In this position, I authored 20 publications and secured 8 patents, affirming the academic and practical significance of my research. I was also given the opportunity to represent our group in two press conferences during the IBM Research press days, sharing insights and advancements with a broader audience. My time at IBM was marked by continuous exploration, collaboration, and tangible achievements, reinforcing my commitment to technological innovation. Show less

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  EPFL

  Sept 2018 - Feb 2019

  Principal Teaching Assistant « Statistics for Data Science »

  I was responsible of preparing and managing the exercise sessions (2h per week) as well as the exams for the class « Statistics for Data Science » taught by Prof. Victor Panaretos.

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  EPFL

  Jan 2020 - Dec 2021

  At the EPFL School of Information and Communication Sciences, I served as the lecturer for the Master-level class on "Mathematical Foundations of Signal Processing." I redesigned entirely this foundational course to explore both the theoretical foundations and real-world applications of modern signal processing and computer-aided sensing. Through the integration of hands-on projects and in-depth examination of algorithmic aspects, students were engaged in a stimulating learning environment that bridged academic theory with practical skills. The class featured notably a student project covering a broad scope of topics: hardware prototyping, Python development, dataset collection, camera technology, signal/image processing, and inverse problems. In this project the students were asked to perform imaging with a lensless camera built from a piece of tape and a Raspberry Pi HQ camera sensor.For a more comprehensive insight into the lecture content, slides are available at: https://infoscience.epfl.ch/record/283918?ln=en. Show less As a Postdoctoral Research Associate in the AudioVisual Communications Laboratory (LCAV) of Professor Martin Vetterli, I developed innovative data science methods for large-scale geo-environmental monitoring. This ambitious project aimed at constructing an Earth Digital Twin that could deepen our understanding of environmental processes and interactions. My responsibilities extended beyond research, encompassing the recruitment and supervision of both PhD and Master's students, ensuring their academic growth and alignment with the laboratory's goals. I also actively managed multiple research grants, crafting compelling proposals and overseeing their successful execution. This role allowed me to blend scientific innovation with leadership and administrative expertise. Show less

  • University Lecturer « Mathematical Foundations of Signal Processing »

    Jan 2020 - Dec 2021

  • Research Associate & Lab Manager

    Jan 2020 - Sept 2021
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  EPFL Center for Imaging

  Sept 2021 - Nov 2023

  Founding Principal Research Scientist, Head of the EPFL Hub for Advanced Image Reconstruction (AIR)

  Leading the R&D Image Reconstruction hub at EPFL, I oversee a dynamic team of 5 PhDs, 1 postdoc, and 2 engineers (and growing), all dedicated to advancing high-performance computational imaging methods across scales, modalities and communities. Our collaboration extends to the SKAO international consortium and the Swiss Plasma Center. In less than two years, I have built this hub from the ground up, securing a long-term budget of 1 Million Swiss Francs to fuel our innovative work.

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  Distran

  Nov 2023 - now

  In my role as Research and Scientific Computing Team Lead, I lead both the computational engineering and R&D teams. I drive the advancement of our technology, spearheading innovations in ultrasonic imaging and leak detection algorithms. Collaborating closely with software and application teams, I push the frontiers of wave signal processing and quantitative acoustic imaging to enhance our clients' experience with our cameras. My team's and I efforts focus on making gas leak detection easier, more accurate, and safer.In addition to my leadership responsibilities, I continue to contribute as an individual contributor to the development of our Python SDK for scientific computing, ensuring it remains a critical component of our technological advancements. Show less As a founding engineer of Distran's computational engineering team, I developed and architected the company's reference Python SDK for scientific computing, addressing the entire acoustic processing pipeline. This JAX-based toolkit enables fast, flexible experimentation and prototyping with a user-friendly front-end, a scalable back-end, and a robust ecosystem of validated, composable, and well-documented signal processing tools.My role involved creating high-performance, hardware-accelerated, and scalable software for numerical computing, implementing and validating algorithms, and driving innovation in our numerical pipeline. Collaboration was key, as I engaged in code reviews, testing, documentation, and team coordination.About Distran AG:Distran is an award-winning Swiss high-tech startup known for its pioneering ultrasound acoustic cameras that can see sounds. Our cameras are used globally in industries such as Oil & Gas and Space Exploration to detect gas leaks, protecting people and the environment. Show less

  • Research and Scientific Computing Team Lead

    Mar 2024 - now

  • Senior Computational Software Engineer

    Nov 2023 - Mar 2024