About me

In 2008, I graduated with a Master Of Science (MSc) degree in microengineering and robotics from the Ecole Polytechnique Fédérale de Lausanne (EPFL). Then, I joined the laboratory of Intelligent Systems directed by Prof. Dario Floreano and started a PhD thesis in biotechnology and bioengineering funded by SystemsX.ch, the Swiss initiative in systems biology. This project was conducted in collaboration with Prof. Markus Affolter from the University of Basel. At the end of my thesis, I had developed several methods and usable computational tools for quantifying multicellular organisms and reverse engineering gene regulatory networks.

My research interests lie in the development of new technologies for application-oriented projects in biomedical, biotechnology, and computer sciences. Topics of interest are but not limited to computational biology, artificial intelligence, optimization algorithms, consensus-based methods, graph theory, image processing, software development, and human-computer interaction.

Reverse engineering biological organisms

The goal of the reverse engineering algorithm is to generate a computer model that accurately describes a specific organism. Though the generation of whole models belongs presently in science fiction, such models hold the promise of powerful predictive capabilities. As an example, I believe it will be possible one day to simulate the effect of drugs using a customized computer model of a patient before effectively applying a treatment.

Significant efforts have been put into reverse engineering gene regulatory networks, the normal functioning of which plays a central role in the development and health of any organism. Numerous methods have been developed for reverse engineering gene regulatory networks from expression data. However, 1) both their absolute and comparative performance remain poorly understood and 2) there are usually not enough in vivo data available to generate accurate computer models.

The goal of my thesis was to address these two issues through the development of a comprehensive framework for reverse engineering computer models of biological organisms, in particular gene regulatory networks. The two principal contributions of my thesis are:

Yet another important contribution of my thesis is that I have implemented the methods developed as open-source, extensible, and user-friendly computational tools. Please click on one of the following images for more information about the applications.

Keywords: gene network inference, community detection, optimization algorithms, evolutionary algorithms, data integration, consensus methods, reverse engineering, unsupervised methods, image segmentation, computational tools

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