To build a transversal scientific and technical network specifically oriented towards the academic and business communities, the MSI relies on a team of expert engineers working on research projects with Université Côte d’Azur researchers and faculty.

Some of these experts bring their support to various thematic centers of expertise requiring strong skills in modeling, simulation and data science.

Dr. Maeva Antoine
+33 (0)4 89 15 15 76
Petit Valrose, Avenue Joseph Vallot, 06100 Nice

Maeva Antoine obtained a Ph.D. in computer science from the University of Nice Sophia Antipolis in 2015. Her thesis focused on load balancing in distributed systems. In September 2019, Maeva was recruited by the MSI as HPC Systems Administrator of Azzurra, the Université Côte d'Azur Computing Center.

Dr. Silvia Bottini

+33 (0)6 30 56 69 99
Hôpital Archet 3, 151 Route de Saint-Antoine, 06200 Nice

Holder of a master's degree in physics, Silvia obtained her Ph.D. in bioinformatics from the University of Siena (Italy) in 2014. During her Ph.D., she developed computational pipelines dedicated to the study of the bacterial transcriptome from high density chip experiments. From October 2014 to December 2018, she was a postdoctoral fellow at the Mediterranean Center for Molecular Medicine (Inserm U1065) in Nice to study the regulation of gene expression mediated by miRNAs. Her main areas of expertise concern high throughput sequencing data analysis including OMICS technologies such as RNA-seq, CLIP-seq, ChIP-seq and the development of bioinformatic pipelines.

Since January 2019, Silvia Bottini is the Operational Manager of the Medical Data Laboratory (MDLab), the center of expertise in medical data processing based at the CHU in Nice.

Dr. Djampa Kozlowski

Djampa Kozlowski
Djampa Kozlowski
Hôpital Archet 3, 151 Route de Saint-Antoine, 06200 Nice.
Institut Sophia Agrobiotech, 400 Route des Chappes, 06903 Sophia Antipolis, bureau C204.

Djampa Kozlowski holds a master's and a doctorate in bioinformatics from Université Côte d'Azur. His thesis work, carried out at INRAe, focuses on the study of crop pests and their adaptability through the analysis of multi-omic data. Djampa then completed a post-doctorate course on similar themes before training in Artificial Intelligence. Djampa specializes in multi-omic data processing and molecular evolution.

In November 2021, Djampa joined the MSI as an "Operational Engineer in Multi-omic Data Integration and Artificial Intelligence" as part of a bilateral project between Université Côte d'Azur and INRAe. Through the use of Artificial Intelligence, this project aims to study interactions between organisms in the context of plant health.

The list of Djampa's scientific productions is available here:


Dr. Marco Milanesio

Inria Sophia Antipolis Méditerranée
bât. Fermat, Bureau F215
2004 Route des Lucioles, 06902 Valbonne

Marco Milanesio earned his PhD in Computer Science at the University of Turin (Italy) in 2010, with a thesis on "Layering Multi-Purpose Applications over Structured and Dependable P2P Systems". During his PhD, he worked on the security aspects of distributed systems, their architectures and features.

From 2011 to 2017, he was research engineer at Eurecom in the "Network and Security" (until 2016) and "Data Science" departments, where he worked on several topics: network performance measurements, QoE / QoS, distributed storage, virtualization, time series analysis and forecasting.

He joined the MSI in September 2017. His first research project is carried out within the Inria Epione team, where he works on distributed optimization and ETL (Extract/Transform/Load) pipelines for distributed analysis of medical images.

He has worked for the Medical Data Lab since its creation, by contributing to the design of the architecture and the deployment of the servers' infrastructure. Within the same lab, he currently manages the servers and works on the development of software for the processing of genetic data.


 At Inria Epione Team: Distributed Analysis of Medical Data

 At the Medical Data Lab

  • NGS sequencers data backup;
  • Fetal fraction determination;
  • Data management;
  • Virtualisation.