About me

This summary wont be as efficient or sufficient to describe my education, experience and technical skills as the other sections of this page. So let's exploit this space here to talk about less measurable stuff.

During my studies, I have tried hard to build as much competences in the computer science domain as possible. I did not focus on a specific topic. However, I avoided gathering sparse and incoherent knowledge and I did not compromise the quality of my learning process (I was almost always the top of my class). Now, I do know how stuff connect and exchange data, how computers can see and how machines can learn. I would like to pursue my career in any of these domains, or better, to work on all of them in the same time.

In the past 6 years, I lived in 3 different countries: Italy, France and Germany. I learned from Italian how to meet new people and socialise, from French how to be efficient when working alone and from German how to be precise and punctual when dealing with collaborative work.

One More thing, I like bouldering, CGI and street photography.


Chief Blockchain Architect

Ki Foundation

Blockchain, IoT, Cryptocurrency, Proof of Reputation

Nov 2018 - Now

ATER - University Lecturer and Researcher

IUT - University of Lyon 1 - France

software engineering, teaching, UML, JAVA

Process modeling UML : Lectures and seminars

Usecase, Class, Activity, Sequence and State diagrams

JAVA Programming : Lectures and seminars

Basics, databases, multithreading, graphical UI and other stuff

2017- 2018

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PhD candidate - Computer Science

IRIXYS - Without walls - International

DRIM - INSA Lyon - France

DIMIS - University of Passau - Germany

Crowdsourcing, machine learning, data mining, quality control, clustering, Python, Java, CrowdFlower

Title : Quality Control in Crowdsourcing Systems

Abstract : In the last decade, crowdsourcing (CS) has emerged as a very promising approach for obtaining services, feedback or data from a large number of people connected through the Internet, in a short time and at a reasonable cost. CS has been used in a large range of contexts, thus proving its versatility. However, the quality of the services or data provided by the workers (the ”crowd”) is not guaranteed, and therefore must be verified. This verification usually results in additional time and cost. We propose a novel approach of quality control in crowdsourcing that reduces, and in some cases eliminates, this overhead. Our approach uses a learning technique to characterize and cluster tasks, and selects, within the available crowd, the most reliable group of workers for a given type of tasks.


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Engineering intern - Computer vision

Atomic and Alternative Energy Agency CEA/LIST/LVIC - Saclay - France

SLAM, augmented reality, camera calibration, projective geometry, C++, Ogre3D

Duration : 6 months

Reference letter :

Title : Augmented Reality on Transparent Screens - the driving assistance usecase

Abstract : The first part of this internship consisted in implementing an Over-Transparent-Display Augmented Reality system for driving assistance. Three component were implemented; a user tracking module, a SLAM based environment real-time scanner and a calibration system with bundle adjustment. The second part of he internship consisted in improving the theoretical part of the calibration algorithm to fulfil the client requirements. A 2D calibration process was proposed instead of the 3D calibration.

Developer intern - Collaborative systems

SESAR Lab - University of Milan - Italy

Liferay, Java, SQL

Duration : 4 months

Reference letter :

Abstract : The internship work consisted in designing and implementing a log capturing and storing system for a collaborative work platform base don Liferay.

Developer intern - Creating web-based virtual visits

Antonin University, TICKET lab - Baabda - Lebanon

MM databases, Virtual visits, Web developpement, CBIR

Duration : 3 months

Reference letter :


Engineering diploma - Computer science and electronics

ESIREM - Dijon - France

Network administration, security and quality, software engineering, project management

Graduated with high distinction - Top of my class

Reference letter :


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Master of research - Image processing

University of Burgundy - Dijon - France

Geometrical modeling, image processing, information systems

Graduated with high distinction - Top of my class

Reference letter :


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Engineering diploma - Telecommunications and networks

Antonin University - Baabda - Lebanon

Telecommunications, electonics, software engineering

Graduated with high distinction - Top of my class



Efficient Worker Selection Through History Based Learning

CompSac 2017, Turin - Italy

Tarek Awwad, Nadia Bennani, Konstantin Ziegler, Veronika Rehn-Sonigo, Lionel Brunie and Harald Kosch


Task Characterization For An Effective Worker Targeting In Crowdsourcing

HASE 2016, Orlando - USA

Tarek Awwad, Nadia Bennani, Lionel Brunie, David Coquil, Harald Kosch and Veronika Rehn-Sonigo


Software and resources

CrowdED - Crowdsourcing Evaluation Dataset

Source code (Github)

CrowdED is a crowdsourcing evaluation dataset. It consists of 300K+ contributions collected from 400 workers for 1000+ questions distributed over 500+ tasks. It also contains a declarative profiles for each worker, a self evaluation (1-5 rating) in different knowledge domains and a crowdsource consistency relevance of this profile. Tasks belong to various domains such as sport, fashion, economy, politics etc., and have different types, relevance judgment, data annotation, image labelling etc.

CREX - Create Enrich EXtend

Python, Javascript, PHP

Source code (Github)

UI Demo - BETA

CREX (CReate, Enrich, eXtend) is a framework allowing the creation the extension and the enrichment of crowdsourcing datasets such as CrowdED. CREX allows a clustering based tasks selection and the generation of crowdsourcing campaign sites. Code is in Python for the computational parts and in Javascript for the campaign generation tool.


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WSP - Worker Selection Platform


Source code will be added ASAP

CAWS is a framework that learns during an offline stage the relation between the various types of tasks and the declarative profiles of reliable workers. The task types are determined through a content-based clustering process. The learned models are then used in an online stage to select reliable workers within the available crowd.


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Talks and presentations


IRIXYS workshops

November'14 - Besançon - France
Enabling Resilience in Crowd Computing systems
June'15 - Passau - Germany
Quality Control in Crowdsourcing Systems
December'15 - Lyon - France
Task Characterization For Efficient Worker Selection in Crowdsourcing
June'16 - Gargnano - Italy
Crowdsourcing Quality Control: A Recommender System Approach
November'16 - Lyon - France
Crowdsourcing Quality Control: A Recommender System Approach
July'17 - Chiemsee - Germany
History-based Learning for Worker Selection in Crowdsourcing Systems
Juin'18 - Gargnano - Italy
CrowdED and CREX: Enabling Crowdsourcing Quality Control Evaluation


HASE 2016

January'16 - Orlando - USA

CompSac 2017

July'17 - Torino - Italy


English : Full proficiency

French : Full proficiency

Arabic : Mother Tongue

German : B1 Level - Goethe Institut

Technical skills


3rd Generation Languages

C++, Python and JAVA (advanced), C#

Databases, Web and Process modeling


Python libraries (ML)

Scikit-learn, Gensim, NLTK, Seaborn, Pandas


Network Administration

SNMP, HP OpenView

Network Quality

IntServ, DiffServ, RSVP

Network Security

IPSec, OpenPGP, OpenVPN, OpenSSL, RADIUS, PyCrypto

Netowrk Configuration

Cisco Router and switches configuration

Computer vision

Augmented Reality

SLAM, 3D reconstruction, OpenCV, Projective geometry



Ogre 3D, 3D modelling, texturing and rendering Cinema4D, 3Dmax, Photoshop, Illustrator, Flash

Office and OS

Latex, Microsoft Office, Libre Office, Windows, Linux and Mac OS X


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