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Loïc Niederhauser

EPFL Master student


September 2017now

Master degree in Microengineering (in progress)

École Polytechnique Fédérale de Lausanne (EPFL)

Master of science in microengineering with a specialization in robotics covering mainly mobile robotics, machine learning and control system. 

September 2014June 2017

BSc in Microengineering

École Polytechnique Fédérale de Lausanne (EPFL)

The microengineering EPFL program covers mathematics, physics, electricity and electronics, mechanics and computer science with emphasis on miniaturization.

August 2011July 2014

Maturité Gymnasial (High School diploma)

Gymnase Provence

Maturité Gymnasial with Physics and applied mathematics as option. Graduation with award for excellent results in applied mathematics. 

Work experience

July 2017Septembre 2017

Aid in a mountain farm

Swiss Civil Service

Help in livestock care taking, farm, fields and forest maintenance during mandatory Swiss civil service.  

Decembre 2014May 2016

Tutor for technical branches

Association "AppApp formation apprentis"

School tutoring for groups from four to six apprentices from various professions in different technical fields such as mathematics, physics, electronics and technical design.

Academical projects

Septembre 2018January 2019

Control a Robot by means of an adaptive body motion decoder [5.25/6]

Project realized at the laboratory for intelligent systems (LIS) at EPFL. The aim of the project was to implement a adaptive map between the user inputs and the drone attitude using an online machine learning algorithms implemented with python and Scikit learn, and compare the performances between different algorithms as well as an offline version using a custom made simulator in Unity3D.

Septembre 2018December 2018

Android App for Drone Navigation

Independent project. Development prototype app that can be used to have a Parrot drone take off, go to specific GPS coordinates and land. Source code available on

Decembre 2017June 2018

Machine learning for IEEG data [5.75/6]

Project realized at the microelectronics systems laboratory (EPFL). Multiple machine learning based compression algorithms for IEEG's assessment using MATLAB and Tensorflow. Followed by implementation of an SVM-based algorithm detecting epilepsy seizure from IEEG data in MATLAB

September 2017December 2017

IoT "PolyPot" [5.5/6]

Project done in an EPFL course in a team of five students where IoT based flower pot was developed. Details at: . PolyPot Android App available on the playstore.

February 2016July 2016

Guidance system for Watt balance [5/6]

3D CAD design of a linear, high precision, micro-scale guiding system for a Watt balance based on 150 microns wide flexible articulations using CATIA.