From a young age, I enjoyed learning about mathematics and foreign languages, which I explored in my high school coursework. As a mix of mathematics and languages, computer science naturally appealed to me. In pursuit of this interest, I began teaching myself C/C++ and PHP through online resources. My interest grew even more when I used Linux for the first time, and was able to enhance my interactions with computer systems. These were enriching experiences since it was my first time investing so much efforts in science on my own volition. Following my graduation from high school, I decided to work towards an engineering degree.
The first part of my studies involved acquiring a strong background in mathematics and physics. I chose to specialize in computer science, and was introduced to the CAML language, which provided me my first theoretical aspects in this field. Later, I was accepted at the Ecole Centrale Lyon Engineering School, where I learned to apply my knowledge to problem solving in engineering, and more particularly in signal processing, biological systems modeling, computer graphics, and bioinformatics.
In my third year of engineering school, I decided to take a year off to validate my career objectives by doing research internships in various laboratories. My first internship was in the Astrophysics Department of the French Alternative Energies and Atomic Energy Commission where I used wavelet decomposition algorithms to denoise telescope images. Working on this project was really impactful because it was my first experience doing research. I found that I really enjoyed the autonomy that I was given in my work and the everyday interactions with my peers that provided me insights about the latest trends in related fields. Then, I joined a collaborative effort between an acoustician and a computer scientist at two different institutions, l’Ecole Nationale Superieure de Techniques Avancées de Bretagne (Brest, France) and Scripps Institute of Oceanography (San Diego, California, USA). Our goal was to localize whales using a time-frequency analysis of their calls. I really enjoyed working on this project because of the interdisciplinary approaches and heterogenous background of my mentors. Finally, my end-of-study internship in Sanofi Pasteur (Marcy l’étoile, France) gave me the opportunity to work in the pharmaceutical industry, where I learned to use machine learning methods to predict a vaccine response.
Many aspects of computer science are appealing to me, and more particularly machine learning approaches. I enjoy combining probability theory and computer science to describe or predict patterns in data, and biology provides many opportunities to do so. Moreover, this field keeps evolving at a very fast pace and the flow of new ideas is very stimulating for creative research. My involvement in the data science institute in the University of Hawaiʻi at Mānoa with Dr. Mahdi Belcaid helps me strengthen my knowledge in this field, and my various collaboration with biological oceanography labs in the university provides me valuable experience analyzing and curating the data. Already, my current research tries to makes use of deep learning models to cluster genomic sequences in metagenomic samples.
In the future, I want my research to support other scientific fields through the development of data analysis tools and machine learning approaches.