Yassir Benkhedda

Yassir Benkhedda has a diverse work experience in the field of data science and machine learning. Yassir worked as a Data Scientist & Machine Learning Engineer at Unit8 SA from September 2019 to the present. Prior to that, they were a Machine Learning Engineer at Apple from January 2019 to July 2019. Yassir also worked as a Machine Learning Engineer at FASHWELL from December 2017 to December 2018.

Yassir has a background in research, as they served as a Research Assistant at the Idiap Research Institute from January 2017 to December 2017. During this time, they developed a predictive model using deep learning scene parser and face attributes, and published the results in ACM multimedia 2017. Yassir also analyzed place ambiance dataset machine predictions using Grad-Cam heat maps and contributed to the design of a crowdsourcing task to evaluate the heatmaps.

Additionally, Yassir gained practical experience as an Engineering Intern at nViso from August 2016 to November 2016. Yassir developed a deep learning algorithm to predict pain via facial expressions with an accuracy rate of over 90%. Yassir utilized Python, Caffe, and Theano for this project.

Lastly, Yassir worked on their Master Thesis Project as a part of their role at Axis Communications from November 2015 to May 2016. Yassir developed a deep learning framework for a distributed platform and created a theoretical model to predict performance. Yassir tested the framework on an experimental setup of 8 raspberry pi units and validated the model, using Python and Caffe as their primary IT tools.

Yassir Benkhedda's education history includes a Master of Science (MSc) in Technologies de l'information from EPFL (École polytechnique fédérale de Lausanne), which they obtained from 2014 to 2016. Prior to that, they completed a Bachelor of Science (BSc) in Ingénierie électrique, électronique et des communications from the same institution, from 2010 to 2014.