Mathias ROESLER

Doctoral Student at Auckland Bioengineering Institute
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Contact Information
us****@****om
(386) 825-5501
Location
NZ
Languages
  • English Native or bilingual proficiency
  • French Native or bilingual proficiency

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Bio

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Experience

    • New Zealand
    • Research Services
    • 1 - 100 Employee
    • Doctoral Student
      • Oct 2021 - Present

      Smooth muscle electrophysiology in the uterus: from data to model. The goal of this research project is to better understand the electric activity that can be observed in the non-gravid uterus through experimental and modelling work. Smooth muscle electrophysiology in the uterus: from data to model. The goal of this research project is to better understand the electric activity that can be observed in the non-gravid uterus through experimental and modelling work.

  • LICIIS
    • Reims
    • Research Engineer
      • Nov 2020 - Sep 2021

      Working on the European project AI4DI at the LICIIS at the Université de Reims. The objective of this project is to develop tools to help the Champagne industry estimate the yield of its vines with better accuracy. Theses tools are based on AI and use the data from embarked sensors to function. My task is to convert the AI models so that they can run inference on a STMicroelectronics board. Working on the European project AI4DI at the LICIIS at the Université de Reims. The objective of this project is to develop tools to help the Champagne industry estimate the yield of its vines with better accuracy. Theses tools are based on AI and use the data from embarked sensors to function. My task is to convert the AI models so that they can run inference on a STMicroelectronics board.

    • France
    • Research Services
    • 1 - 100 Employee
    • Research Intern
      • Mar 2020 - Jul 2020

      Machine teaching for image classification. The objective of this internship is to extend the concepts of machine teaching from binary classification problems to multi-class problems. The machine teaching algorithm was tested using deep neural networks with the MNIST and CIFAR-10 databases. The performances were compared with model trained with other strategies such as self-paced learning and curriculum learning. Machine teaching for image classification. The objective of this internship is to extend the concepts of machine teaching from binary classification problems to multi-class problems. The machine teaching algorithm was tested using deep neural networks with the MNIST and CIFAR-10 databases. The performances were compared with model trained with other strategies such as self-paced learning and curriculum learning.

    • France
    • IT Services and IT Consulting
    • 1 - 100 Employee
    • Intern
      • Jun 2019 - Aug 2019

      Acquisition and processing of thermal images for photogrammetry. The objective of the internship was to develop an entire processing chain, from acquisition to processing, for thermal images for photogrammetry using Metashape to produce an exploitable thermal orthoimage. The thermal orthoimage also had to be able to match up with a color orthoimage produced with non thermal images. The developed method has been tested on real missions and proven to be successful. The images were acquired using a Zenmuse XT2 camera mounted on a Matrice 210 drone. Show less

    • France
    • Research Services
    • 1 - 100 Employee
    • Intern
      • Sep 2017 - Dec 2017

      Haptic interface communication for nano-robotic systems. The internship consisted in the writing of a program in C for the communication between the haptic interface and the nano-robotic system. The movements of the system where microscopic while the movements of the interface where macroscopic. The haptic interface used was a Falcon by Novint and the nano-robotic system used was a Piezoelectric Stick-Slip (PSS) actuator. Haptic interface communication for nano-robotic systems. The internship consisted in the writing of a program in C for the communication between the haptic interface and the nano-robotic system. The movements of the system where microscopic while the movements of the interface where macroscopic. The haptic interface used was a Falcon by Novint and the nano-robotic system used was a Piezoelectric Stick-Slip (PSS) actuator.

    • Intern
      • Jun 2015 - Jul 2015

      Analysis of the performances of facial recognition algorithms. The internship consisted in writing a Python algorithm to be able to see if centring the databases had an impact on the performances of the facial recognition algorithms. The centroids of various databases were used to see which one could boost performances. The performances were estimated using ROC curves. Analysis of the performances of facial recognition algorithms. The internship consisted in writing a Python algorithm to be able to see if centring the databases had an impact on the performances of the facial recognition algorithms. The centroids of various databases were used to see which one could boost performances. The performances were estimated using ROC curves.

Education

  • Master Sciences pour l’Ingénieur - Sorbonne Université
    Master of Science - MS, Artificial Intelligence
    2018 - 2020
  • Cockrell School of Engineering, The University of Texas at Austin
    Semester abroad, Aerospace, Aeronautical and Astronautical Engineering
    2018 - 2018
  • Sorbonne Université
    Bachelor of Engineering - BE, Mechanical Engineering
    2015 - 2018

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