Fakhri Dean Zouari
Team Lead at MADAR Consulting
About me
A skilled Software Engineering student at the National Institute of Applied sciences and Technology (INSAT) with extensive software design and development experience, as well as a solid theoretical foundation. Capable of working on multiple projects involving different technologies. Good analytical and problem solving skills. Keen to expand skills and knowledge and prepared to work in a variety of roles as required.
MADAR Consulting
Team Lead
2014 - Current
OVERVIEW LOCUST is a low cost intelligent transportation system that uses smartphones to create a virtual road orchestration network. DETAILS • Worked on the detection algorithms for potholes, traffic jams and driver behavior, using the Hadoop ecosystem • Designed the machine learning algorithm that runs on mobile devices to increase the accuracy of the data sent to the platform and help retain the user battery • Designed the routing engine based on genetic algorithms KEYWORDS Big Data, Machine Learning, Genetic Algorithms, Hadoop Ecosystem (HDFS, MapReduce, pig, Hive ,flume ,kafka ,Hbase, sqoop, storm)
Xavier University of LA
Software Engineering Intern
2015 - 2015
OVERVIEW: Create a toolbox to analyze grey matter, across two different populations (healthy subject and controls) and generate meaningful network patterns and brain structural insights. DETAILS • Joined a multidisciplinary team working on the brain analysis project, required adapting to a new field with different taxonomies and tools. • Analyzed the best implementation for a brain analysis toolbox, researching relevant APIs and different analysis techniques. • Used the information I collected, and developed toolbox that extracts viable insights from brain connectivity networks. KEYWORDS Computational Neuroscience, Machine Learning, Matlab, Python, R, Weka, Image Processing, Graph Theory, Brain Connectivity Toolbox.
Xavier University of LA
Research Trainee
2014 - 2015
OVERVIEW A natural language processing (NLP), and a machine learning with the purpose of extracting keywords from long narratives to be later used in text clustering as well as information retrieval systems. DETAILS • I implemented and analyzed RAKE to determine the reasons behind its drop in performance when applied to long narratives. • I examined other keywords extraction approaches, to get more insight into NLP best practices, since this was my first project in the field. • I finally, developed my own approach, that remedied the shortcomings of RAKE, and improved its performance as evident by the increase of F-Measure from 5.72 to 32.2 KEYWORDS NLP, Machine Learning, RAKE, Java, Python, R, Weka, Stanford NLP Toolbox
2013 - 2014
OVERVIEW The purpose of this project was to build an observation layer on top of the RoboCup Rescue Simulator, to observe the behavior of the various agents, detect flaws, and ultimately improve the performance of the system, which is used to simulate natural disasters and DETAILS • Configured the RoboCup Rescue Simulator • Created a an observation layer for each type of agent • Intercepted and logged actions and communications between the different agents • Analyzed the observation logs in tandem with the simulation logs to detects erroneous patterns and improve the default behavior of agents KEYWORDS RoboCup Rescue, Artificial Intelligence, Multi Agent Systems, Parallel Programming, Java, ant
National Institure of Apllied Sciences and Technology
Bachelors of Engineering,
2010 - Current
Xavier University of Lousiniana
Bachelors of Computer Science,
2014 - 2015
A Thomas Jefferson Exchange Student




Tunis, Tunisia


Product management
Project management


Big Data
Business Intelligence
Genetic Algorimths
Machine Learning
Data Visulisation
Elastic Search
Neural Networks
Deep Learning
Project Management
Agile Development
Object Oriented Programming
Service Oriented Architecture