25 Open Source professionals & enthusiasts representing local (and national) excellence in Artificial Intelligence, IoT, Cloud, DevOps and Open Source technologies.


Entrepreneur, IT Consultant, Speaker, Microsoft MVP Azure

Entrepreneur with experience of IT Manager in the industry. Consultant specialized in Cloud with a focus on IoT and IT security. MS MVP Azure, mentor and speaker.

Workshops day - Thursday July 5th



Senior software Engineer

Dealing with distributed systems at Amadeus for 10 years, I am in charge of building the next generation platform for Amadeus application. This platform is based on Openshift/Kubernetes and I had the chance to study ServiceMesh in 2017 to see how it could fit in such platform. Even if we are not yet running any production workload on top of servicemesh, I can share my experience on that topic.

Devops & cloud conference - Wednesday July 4th, 6:00pm

Introduction to service mesh
Recently CNCF opensource community was hit by a new buzzword: ServiceMesh. This talk will help you to understand the real values behind this buzz. Let’s see how a ServiceMesh like Istio adds control points to your architecture to enhance observability, ease traffic routing and mitigate failures.

The goal of the talk is to present what a ServiceMesh is, what kind of value does it brings to a distributed system.

To illustrate each value, examples will be provided on top of the leading project in that area: Istio.


Workshops day - Thursday July 5th

Kubernetes allows you to deploy, run and configure your applications. This lab will guide you through the core concepts of the platform: from a demo application, learn how to setup workload, rollout new version, route traffic and investigate issues.

The goal of the lab is to have people hands on kubernetes, manipulate core concepts such as pod, deployment, configmap, services (labels and selector mechanism), endpoints, job. From a pre installed application we will guide people th rough various use case, from application setup and rollout to investigation. This lab could be considered a learning by practice session. Attendees’ laptops will be used to connect to a prepared kubernetes instance.

The following core concepts will be described and manipulated: Deployment Pod Container configuration Volumes Probes ConfigMap Services Labels and Selector Endpoints Job.

Attendees will have to join with their own laptop and will have to connect to wifi. The lab will happen online on a preprovisioned kubernetes cluster.

The lab will be animated by David Benque and Cedric Lamoriniere.

Maxime beugnet

Developer Advocate EMEA

Maxime has been working with MongoDB for the past 4 years and in the IT industry for 7 years. He is a MongoDB and Java trainer, with DEV and DBA MongoDB certifications. Maxime recently joined MongoDB as a Developer Advocate EMEA to share his experience with the community. He loves clean code, scuba diving, code challenges and vikings!

Workshops day - Thursday July 5th

MongoDB Workshop
MongoDB is the first NoSQL and open-source database in the market and the new release MongoDB 4.0 going live this summer will support multi-document ACID transactions through Replica Set. It’s a real game changer for the database business so join us to discover the basics of MongoDB.

In this workshop, you will discover many things about MongoDB : – JSON modelisation, – CRUD – Import / export – Indexes – Aggregation framework – MongoDB Driver – Replica Set – Sharded Cluster – MongoDB Atlas – MongoDB Compass – Change Stream – Security basics No existing knowledge is required.

Notes :

This is a hands-on session. People are expected to bring their laptop without any special requirements except an Internet access.

christian couder

Software Engineer

Christian Couder is a software engineer with more than 20 years of professional experience. He is a Git developer since June 2006. He works as a freelance consultant and developer for GitLab and Booking.com on Git, and for Protocol Labs on IPFS. He has given presentations about Git at many conferences since 2009.

Workshops day - Thursday July 5th

Git workshop: learn how to use Git from the command line
Since it was created in 2005, Git has become the leading version control system.

This workshop will show you how Git can be learned and understood step by step. It will train you to become familiar with the most useful Git commands and the Git terminology.

This workshop will explain you how Git works along with training you to use it on the command line. You will learn how the Git commands work and practice using them on many small exercises.

This will start with a set of simple common commands, and some simple concepts. Then over the course of the workshop, it will cover some more and more important sets of commands, and some more and more advanced concepts.

Notes :

It is best to come to this workshop with a laptop where Git is already installed.

Fabien Ferrero

Associate Professor

Associate professor at University Nice Sophia, Fabien Ferrero is the Sophia Antipolis TTN community manager and developing Open IoT network all over the world for education.



Internet of things conference - Tuesday July 3rd, 6 pm

The Thing Network : Building a global internet of things network together

This presentation will be the official kick-off of Sophia Antipolis The Thing Network Community. 


Professeur des universités


Lionel Fillatre has been a Full Professor with the I3S Laboratory at Université Côte d’Azur since 2012. His current research interests include statistical decision theory, machine learning, deep learning, bio-inspired coding, signal and image processing, and biological data processing.

Workshops day - Thursday July 5th

Workshop : Why Deep Learning Needs Mathematical Theories ?
If you know Deep Neural Networks (DNN) and have some experimental skills but you face some issues with the reliability of DNN, this talk is for you. It will describe the most significant mathematical aspects of DNN.

Deep learning recently led to phenomenal breakthroughs in a myriad of practical machine learning tasks, such as ImageNet classification challenge and playing the game Go. Yet many engineers and researchers are in quest of mathematical and theoretical understanding which aims to penetrate through the mysteries that explain clearly how it works so well in empirical success, especially to exploit open-source software and tune the deep neural network architecture. This tutorial will review recent work that aims to provide a mathematical justification for properties of special classes of deep networks, such as global optimality, invariance, and stability of the learned representations. The penultimate goal is to be able to understand the strength and drawbacks of existing open-source tools.

This talk is composed of a general introduction about DNN and three technical parts. Each part includes a formal discussion on a mathematical concept and some practical works with Python to be familiar with this concept. A 10-minute break will take place between part 1 and part 2.

1- Introduction (20 minutes) – This introductory talk will briefly review the recent success of deep architectures and the main open-source frameworks to run deep learning neural networks. It uses recent results to motivate the following theoretical questions: – How to deal with the challenge that the learning problem is non-convex? – What is the importance of “deep” and “convolutional” in CNN architectures? – What statistical properties of inputs are being captured/exploited by deep networks? – How can we add robustness to the learning of the network?

2- Part 1 – Global Optimality in Deep Learning (presentation 20 minutes + practical works 30 minutes): One of the challenges in training deep networks is that the associated optimization problem is non-convex and hence finding a good initialization would appear to be essential. Researchers have tackled this issue by using different ad-hoc or brute force initialization strategies, which often lead to very different local solutions for the network weights. Nonetheless, these local solutions give roughly the same results. This lecture will present a mathematical analysis that discusses the difficulty to find the global optimum in training deep networks.

3- Part 2 – Data Structure Based Theory for Deep Learning (presentation 20 minutes + practical works 30 minutes): One of the arguments given for the success of deep networks is that deeper architectures can better capture invariant properties of input objects. While a mathematical analysis of why this is the case remains elusive, recent progress has started to shed some light on this issue for certain sub-classes of deep networks. Scattering networks are a class of convolutional networks whose success lies on the ability to preserve discriminative information while generating stability with respect to high-dimensional deformations.

4- Part 3 – Generalization Error (presentation 20 minutes + practical works 30 minutes): This part will focus on data structure based theory for deep learning and discuss two recent developments. We first study the generalization error of deep neural network, including a discussion on fooling a deep neural network. Fooling a DDN consists in producing images totally unrecognizable to human eyes that DNNs classify as familiar objects. Next, we will discuss how deep learning can avoid the curse of dimensionality for certain class of functions. The curse of dimensionality means that the number of parameters in the neural networks can be exponentially large in certain cases.

Laurent Grangeau

Cloud Solution Architect

Laurent Grangeau is a Cloud Solution Architect at Sogeti with more than 10+ years of experience. Former Java developer, he has since developed in .NET, with Agile and DevOps mindsets. He has been experimenting with cloud providers for more than 5+ years. Docker enthusiast from the beginning, he has experienced with building microservices and distributed systems. He loves to automate things and run distributed applications at scale.

devops & cloud conference - wednesday July 4th, 6:00pm

NET Core functions sur Kubernetes gérés par Azure en quelques minutes
A website in .NET Core, Serverless, on a Kubernetes cluster and secure in less than 20 minutes, impossible? Discover how to code a website in minutes, respecting the state of the art and good practices of micro-services distributed in Serverless.

The serverless is the new computer trend of recent years. With Microsoft Azure, which publishes a managed Kubernetes, known as Azure Kubernetes Service, and through open-source projects like OpenFaaaS or .NET Core, it’s now possible to start a resilient website with native https in minutes . During this conference, we will live code a real web site in .NET Core, exposed on the Internet with https natively, and supported by some functions, thanks to OpenFaaS, an open-source framework above Kubernetes.


Workshops day - Thursday July 5th

Workshop : OpenFAAS - Thursday July 5th

Mathieu LACAGE


Mathieu Lacage is co-founder and technical director of Alcméon where his mission is to facilitate the customer relationship on social networks of major brands by developing and integrating artificial intelligence components, within the customer relationship management platform. Alcmaeon.

artificial intelligence conference - Monday July 2nd, 6:00pm

Visualizing unsupervised clusters of short texts
Summary: Data mining is (relatively) simple when you know what you are looking for but most often, it’s really difficult to guess what is in your dataset without painful and lengthy manual inspection. We will focus on a real example to demonstrate how to use sklearn to explore a corpus based of public Tweets.

Cédric Lamorinière

Senior software Engineer

More than 6 years working as software developer in a C++ open back-end architecture. Golang developer since 1 years. One year working as project manager on IT research project and Master Research Student. Telecommunication and Network ENSEIRB Engineer equivalent to European Master’s Degree. Highly experienced in application development.

Tech Workshops Day - Thursday July 5th

Kubernetes allows you to deploy, run and configure your applications. This lab will guide you through the core concepts of the platform: from a demo application, learn how to setup workload, rollout new version, route traffic and investigate issues.

The goal of the lab is to have people hands on kubernetes, manipulate core concepts such as pod, deployment, configmap, services (labels and selector mechanism), endpoints, job. From a pre installed application we will guide people th rough various use case, from application setup and rollout to investigation. This lab could be considered a learning by practice session. Attendees’ laptops will be used to connect to a prepared kubernetes instance.

The following core concepts will be described and manipulated: Deployment Pod Container configuration Volumes Probes ConfigMap Services Labels and Selector Endpoints Job.

Attendees will have to join with their own laptop and will have to connect to wifi. The lab will happen online on a preprovisioned kubernetes cluster.

The lab will be animated by David Benque and Cedric Lamoriniere.

Sébastien Lefeuvre

Network & System Engineer

Sebastien is Network & System Engineer. He has 8 years experience. He installs and maintains any technical components required from TAS to operate the Com4Innov Fiware platform. His mission scope covers any of following components : Servers (Windows, Linux, HAProxy, Bind, Apache, Nginx, PHP, Varnish, Squid, Memcache) Storage/Filesystems (Ceph, Gluster, OCFS) Database (MongoDB, CouchDB, SQL Server, MySQL, MariaDB, PostgreSQL) Virtualisation (VMWare, Virtuoso, OpenStack, OpenNebula, Proxmox, KVM) Security (Firewalling, Intrusion Protection System, Incapsula, SecludIT) Collaborative (Colabtive, Office, PHPList, MediaWik) Frameworks (CMS, CRM) Exploitation (ISPConfig, Cpanel, Webmin, Usermin) Backups (BackupPC, RSYNC, Evault, Asigra) Monitoring (Nagios, Centreon, Cacti)

Devops & cloud conference - Wednesday July 4th, 6:00pm

Hyper Converged Infrastructures with Open Source technologies : feedback from a cloud/hosting services provider

Hyper Converged Infrastructures : Open Source technologies and tools

  • Orchestration : OpenNebula & OpenStack
  • Virtualisation : KVM
  • Network : Open vSwitch
  • Storage : Ceph, GlusterFS, QEMU

Lidwine martinot

CTO & Associate

After years spent serving large companies in the world of Telecom, in several corners of the world, I decided to join the great adventure of a Sophia Antipolis startup. I had two main goals: to bring my embedded systems architecture skills, and to create jobs. In the end I certainly brought my knowledge but it took me beyond and learn a lot for the industrialization phase. I now hope to share this new expertise with new and future entrepreneurs.

internet of things conference - tuesday july 3rd, 6:00pm

IoT, from prototype to product.
Developing a prototype in IoT has become – almost – a game of children: Affordable electronics, open source. Do not hesitate to get started, test even the craziest ideas. This simplicity can however hide the complexity to transform a prototype into a product. We will discuss the points to pay attention to, the steps not to be neglected and some of the pitfalls to avoid.


Research engineer

Research engineer in applied mathematics. Expertise in Revenue Management, Dynamic Pricing,simulation studies.

In the newly created Exploratory Research team, I conduct a study on building a new system based on Reinforcement Learning in lieu of the traditional Revenue Management System. Our presentation (The end of RMS as we know it? – Deep reinforcement learning for airline revenue management) at Agifors Symposium 2017 has received the Best Innovation Award.


artificial intelligence conference - Monday July 2nd, 6:00pm

The end of Airline Revenue Management as we know it?
Revenue Management (RM) is a key element for airlines to maximize revenue. RM systems performance heavily relies on the quality of the forecast and modelling. To overcome this, we use Reinforcement Learning (RL) which doesn’t need any forecast or modelling, showing that RL is much more than AlphaGo.

Reinforcement learning (RL) is an area of machine learning concerned with how machines take actions in order to optimize a given reward by interacting with its dynamic environment. Some well-known recent applications include self-driven cars, and machines playing games better than humans (e.g., chess and go). One of the main advantages of this approach is that there is no need to explicitly model the nature of the interactions with the environment.  In this study, we present a new airline revenue management optimizer based on RL. The model does not need neither demand forecasting nor customer modelling to work. It is theoretically proven that RL will converge to the optimal solution. However, in practice, the system may require a lot of data (e.g., thousands of years of historical bookings) to learn the optimal policies. To overcome these issues, we present a novel model that integrates domain knowledge powered by a deep neural network trained in specialized hardware. The results show very encouraging results with different numerical /simulated scenarios. We believe this opens the door to a new generation of revenue management systems that could automatically learn by interacting with competitors and customers, so it can react much faster to market changes.


Notes :

In this study, we demonstrate the utility of RL in a real application such as RM optimization. For this purpose, we use an air travel market simulator in which an RL system and different RM systems are implemented. To the best of our knowledge, we are the first to propose a domain knowledge integration process to solve the warm up problem, allowing the deep neural network to initialize with the current policies of RM. This process is particularly important: it does not only provide a good starting point for RL, but also makes the training more stable and allows RL to adapt faster to market changes.

No particular technical requirements.

David Pilato

Developer Evangelist

Since 2013, David Pilato has been a developer and evangelist at elastic.co, having spent the previous two years promoting the open-source Elasticsearch project. He animates the French community and organizes [BBLs] (http://brownbaglunch.fr) within companies.

workshops day - Thursday July 5th

The Elastic suite is without a doubt the most trendy and most used tool for log monitoring today, with:

Elasticsearch that does the main job of analyzing and searching in large volumes of data.
Logstash as ETL to extract and enrich.
Beats as light collection agent.
Kibana as a visualization tool.
This workshop will give you an overview of the possibilities offered by these 4 tools, how they interact together and especially how they can help you solve your problems!


The prerequisites are described on this page: https://xeraa.github.io/vagrant-elastic-stack/

It is absolutely necessary that the students have successfully completed the instructions on this page before they can join the workshop.



Johnny RAHAJARISON, developer at MyLittleAdventure in charge of Machine Learning, Dev Ops and Back-End architecture. Scrum & Angular enthusiast

artificial intelligence conference - Monday July 2nd, 6:00pm

Natural language processing and Machine Learning: How to automatically categorize tours and activities ?
To recommend the best products for each traveler context, MyLittleAdventure had to reclassify and fine-tune products from its providers according to its own criterias: in couple, with friends, nightlife, adrenaline, indoor, food, etc. Demonstration of a case including NLP and Supervised Machine Learning.

Nicolas Tribie

Signal processing engineer

System On Chip Architect specialized in high performance and low power applications. I have a broad knowledge of ARM processors architecture, and also of wireless LAN / Bluetooth baseband development. I am familiar with the newest multi antennas receivers techniques, from low level software, to mixed signal chip development. I am also an advanced user of architecture modeling technologies, like SystemC TLM.

Specialties: Systems on Chip, ARM architecture, baseband, WLAN, Bluetooth, MiMo, system modeling, Signal processing, SystemC, Verilog.


internet of things conference - Tuesday july 3rd, 6:00pm

Deux principaux réseaux sont utilisés pour les objets connectés : LoRa, et SigFox. Un troisième émerge , poussé par les opérateurs 4G: NB-IoT. Il s’insère astucieusement dans l’infrastructure existante, et permet à des modules low-cost , low-power de communiquer. Nous vous expliquons comment.

Cette présentation s’articulera autour des points suivants: – Introduction rapide des principes de la 4G – LTE , – Les canaux de communications, comment les objets “parlent” au réseau ? – Comment on optimise la portée et la consommation ? – quelques examples d’objets utilisant NB-IoT – Conclusion – ouverture vers la 5G


Pascal URSO

Research Investigator

As the leader of different tasks of the STAMP project and responsible of the validation process of the STAMP tools for all the partners, I got a extensive knowledge of all the aspects of the STAMP project, even the part I’m not directly contributing to.

I also taught software testing at Master level, and published international scientific articles about collaborative software


Devops & cloud - Wednesday July 4th 6:00pm

Test Amplification for DevOps
Do you want your tests to be automatically created ? Without any formal semantic model or whatever ? The STAMP project creates and improves your tests all along the DevOps cycle from existing unit tests, from release configuration, and operation logs with tools integrated to your DevOps process.

STAMP: Software Testing AMPlification for DevOps teams https://stamp.ow2.org/ =====

Overall Concept

The founding concept behind the STAMP project is that applying automatic transformation, a.k.a test amplification, to testing assets that are usually written by hand can greatly improve testing effectiveness. The STAMP project was launched to develop test amplification tools that increase levels of automation in software testing. STAMP focuses on test amplification in the context of DevOps and targets the early detection of regression bugs. The testing amplification tools developed by the STAMP project aim at helping DevOps to: – detect more regression bugs on continuous integration servers, before functional testing. – detect more scalability bugs, before going to production and experiencing bad behaviour (trashing, freezing) with high user load. – reproduce more production bugs in edge cases thanks to semantic logging.

STAMP Project

STAMP is an European project (Horizon 2020 program). The project gathers ten members including four academic partners with strong software testing expertise, an open source consortium (OW2) and five software companies in e-Health, Content Management, Smart Cities and Public Administration.

STAMP Open-Source Tools

The results of the STAMP project are open-source tools that are available on GitHub.
https://stamp.ow2.org/ For instance, – the DSPOT tool automatically generates new JUnit tests by modifying existing ones, – the Descartes tool verify your test suites to see if they really can detect possible bugs – the EvoCrash tool automatically crates non-regression test from exception appearing in your production log.

These tools are notably integrated in maven and jenkins pipelines to integrate easily your DevOps processus

STAMP Use Cases

Use cases provide strong experimental foundations to the STAMP project. They come from five different application domains (e-Health, Content Management, Smart Cities and Public Administration). The development of amplification technologies is carried out tight collaboration with the use cases so as to ensure the delivery of industry-relevant solutions.

In Activeeon, we leverage the STAMP tools to increase the quality of the open-source code of our products https://github.com/ow2-proactive. Notably, we improve our code coverage and we transform the events occurring in our production SaaS platform into new tests.

« Trophée Objets Connectés & Services 2018 » Teams

The contest’s finalists

For 3 years, SoFAB by Telecom Valley, the Sophia Antipolis FabLab, has been organizing « Trophée Objets Connecté & Services », an IoT Contest.

This year 13 project teams started the contest, which lasts 12 weeks creating and developping a connected object with a service. Teams are coached by professionals volunteers all contest long.

Tuesday July 3rd, teams will present the results of their projects in front of a comittee and SophiaConf attendees.


Internet of things conference - Tuesday July 3rd, 6:00pm

Trophée Objets connectés & services teams pitches
Each team will have 180 seconds to present her project, to convince the comittee and SophiaConf attendees.