I believe that big-data can be tremendously useful in a variety of domains such as finance, smart cities, healthcare and personalized medicine, etc... With big-data and machine learning as my playground, I enjoy solving complex problems, visualizing new patterns in data and discovering insights that will ultimately be beneficial to users.
I am a researcher in data-science at the Computer Research Institute of Montreal (CRIM), a not-for-profit Applied Research Center focusing on innovation and collaborative development. My area of expertise is in large- scale distributed systems, data-mining, knowledge representation and predictive analytics of spatio-temporal big-data. I am performing research for the integration, analysis and visualization of big data using Spark, Hadoop, ElasticSearch, Impala, etc. with applications to finance, GIS, telecoms, etc. I am also supervising students, managing various data science projects, and advising our customers with their own data science projects.
In 2013-2014, I improved the social search engine of Wajam to bring users more relevant search results and social recommendations from their friends. More specifically, I was building a semantic knowledge graph (NoSQL) by processing and analyzing structured and unstructured big-data, as well as building statistical models to help interpret users' intent in real- time. In 2009-2013, I was a post-doctoral fellow with the Centre for Structural and Functional Genomics in Montreal, where I focused on some of the challenges of genomics big-data to optimize the production of cellulosic biofuels.
I have published and presented my work in several well-established peer-reviewed journals and international conferences. My work was rewarded by many awards and prizes.
I earned my Ph.D. in Computer Science after two years from the CSE Department of the University of Nebraska-Lincoln in 2009. I obtained a French Engineer Certificate and my Master's degree in Computer Science and Engineering in the French Grande Ecole ENSICAEN with distinctions.