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Previous positions




Data Engineer

Feb 2022

As more batteries tend to take over fossil-powered engines, the need for a longer lifespan rises drastically. To answer this, one can come up with brand new battery cells with an extended lifespan. However, this turns to be relatively useless as long as typical client usage patterns keep aging batteries prematurely. This is why I currently work on the CIRCUBAT project in the Battery and Storage Systems laboratory of Prof. Vezzini to setup an ETL data pipeline processing deeply heterogeneous data from various industrial battery providers: on the long term, the goal consists to train an ML model able to automate the identification of usage patterns degrading the lifetime of a battery, allowing to alert the user before the battery gets worn out.


Master thesis in R&D

Jul 2021

Research on root cause analysis in telemetry data: Telemetry data can present various forms of inconsistencies with complex, possibly compound root causes. The set of root causes generating an observed error encompasses a great number of potential candidates (software versions, hardware devices, communication protocols etc) and can lie at any stage of the data processing pipeline. In order to avoid business decisions based on corrupted data, domain experts must go through a debugging process that is both time and money consuming. I introduced a multi-stage pipeline aiming at automating the error detection process and subsequent root cause analysis (RCA) using Contrast Set Learning (CSL) techniques on the error-related metadata. I additionally validated the approach on artificial data to make up for the unsupervised nature of the problem. Finally, I delivered an interface allowing to accelerate the exploration of novel hypothesis for a given type of error.

🔬Research Developer, Mathis Laboratory

Jan 2021

Development of a distributed data-pipeline aiming at providing a uniform interface for the multiple AI and neuroscience experiments carried in the laboratory: my main efforts were involved in extending the datajoint pipeline, refactoring the existing codebase and containerazing the whole application.


💼Machine Learning Consultant, Junior Entreprise

Dec 2020

Development of an object detection pipeline for industrial application: my client, an entrepreneur in the energy sector, needed a computer vision approach to automate some key aspect of his business requirements. After three months of work, I received excellent feedback from his side as he proposed me a permanent position.

🔬Research Developer, Topology and Neuroscience Laboratory

Dec 2020

Topological Data Analysis for Covid19 tracing data of Geneva canton. We perform a network analysis on time-series of graphs to observe if the increase in number of Covid cases might be explained by changes in the topological structure of these graphs.

💼Machine Learning Engineer,Visium

May 2020

In order to gain practical experience in industry, I decided to perform an internship in a Machine Learning consulting company. During this time, I improved software solutions for 3 major swiss companies in natural language processing and time series forecasting. Following excellent client feedbacks, I got offered to keep on working at Visium as a part-time machine learning engineer in parallel to my studies. The topics I worked on involve NLP, object detection and information retrieval.


🎓Master of Data Science, EPFL

Jul 2019

This master allowed me to develop skills principally in Software Development, Statistics, Machine learning and Data Engineering. More generally, I had the occasion to approach both theoretically and practically various state of the art usecases encountered in industry while adopting good devops practices and working as part of a team. Finally, multiple semester research projects gave me the occasion to keep up to date with the latest advances in multiple computer science fields and bringing my own contribution with the publication of my work.


🎓Exchange year, ETH

Jul 2018

Deeply motivated by the software development projects and courses taken in the previous years, I decided to change my field of study to Computer Science. In order to do so, I had to catch up with 50 ECTS credits. I took advantage of this opportunity to perform an exchange at ETH Zurich in order to benefit of the courses quality and meet new people.


🔬Software Development Intern, Deplancke's Lab

Jul 2017

Development of a multithreaded C++ real-time image analysis software facilitating a deterministic cell-bead coencapsulation allowing subsequent single cell sequencing. Following succesful results, I got hired as a research assistant in the same laboratory to pursue my research on the topic.




Jul 2015

As a student at EPFL in Life Science Engineering, I had a position of teaching assistant in Probability and Statistics and Object-Oriented C++ courses.