Data Science Entry and Exit program


Since september 2015, UCA runs an entry point in DSC. The exit point running since 2016 offers a specialization entitled Multimedia and Web Science for Big Data.

Be aware of the great opportunity by studying as an ENTRY student at UCA => you will be registered to two UCA degrees, mainly the UCA Polytech Nice Sophia engineering degree in Sciences Informatiques (Computer science), and the Master in computer science of UCA. The engineering degree is well-recognized through two labels: by the French CTI and the European EUR@ACE, still it requires you to commit to extra requirements, especially a French proficiency level at least A2 at the end of (or at worst 2 years after) your studies as an UCA engineering student (you may only graduate with the Master degree at the end, if some requirements get not fulfilled).
Sorry, but this opportunity cannot apply to EXIT students, as the number of studying semesters in the premises of UCA Polytech engineering school is too low (only 1..., should be at least equal to 2 to get opportunity to graduate with a CTI labelled engineering degree) => you can only graduate with the Master degree of UCA.


Check here for more information about studying at Sophia Tech campus of UniCA as international student.

Syllabus of some of the DSC entry or exit courses are collected in this zip file.

First Year (4th year SI MUNDUS) EIT Digital track in Data Science 

In the sequel, MAM4 means 4th year of Maths Appliquées (MAM) department of Polytech Nice Sophia. SI5 means 5th year of Sciences Informatiques (SI) of this same engineering school. MAM5 SD corresponds to the 5th year' option track entitled "Sciences des Données" (SD). All courses listed are taught in English except if not specifically mentioned (FR).

Semester 1

For courses from the 5th year offer, time schedule is split in two periods (quarters of consecutive 8 weeks including last one for the written exam). 

Technical courses

Name of the Module Total
number of ECTS
Data science fundemental courses Semester 1 6
Subject Coeff. Shared with
Modelisation & optimisation in machine learning 3 MAM4; Till Christmas break
Advanced tools in Maths, Probas & Stats 3 Specific to EIT Digital Blocked full half days from early september
Data science complementary courses Semester 1 , that could be selected if no time schedule conflicts, for a total of at least: 15
Subject Coeff. Shared with
Personal or in group project in Data science * 3 N/A, starting ASAP, early October till end of February
Technologies for massive data 3 MAM5 SD; Period 1
Processus stochastiques (FR) 3 MAM4; Till Christmas break;
Equations aux dérivées partielles (FR) 3 MAM4; Till Christmas break;
Data science include seminars from industrial local partners 3 MAM5 SD;  Period 1
Machine learning for networks 3 SI5;  Period 2
AI Engineering 3 MAM5 SD; Period 2
Introduction to Security 3 SI5; Period 2 
Blockchain and privacy 3 SI5;  Period 2
Virtualized infrastructures for cloud computing 3 SI5; Period 1
Large scale distributed systems 3 SI5; Period 2
Peer to peer 3 SI5; Period 1
Deep learning 3 MAM5 SD; Period 1
Applied A.I. 3 MAM5 SD; Period 1
Text mining and NLP 3 MAM5 SD; Period 2
Web of data  3 SI5; Period 1
Semantic Web (prerequisite Web of data) (in FR) 3 SI5;  Period 2
Ingénierie des connaissances (in FR) 3 SI5; Period 1
Traitement automatique du texte en IA (shared with M1 Info.) 3 Starts early Nov
Advanced programming (shared with M1 Info.) 3 Starts early Nov
Computer networks (shared with M1 Info.) 3 Starts early Nov
Parallelism (shared with M1 Info.) 3 Starts early Nov
AI Game programing (shared with M1 Info.) 3 Starts early Sept
BD vers Big Data (partly FR) (shared with M1 Info.) 3 Starts early Nov

Innovation & Entrepreneurship courses

I & E Semester 1 (9 ECTS) Coefficient
Basics in I&E (spread in the empty slots, till end of january) 0,3
Business Intelligence 1 0,3
Business Dev. Lab part 1(spread in the empty slots, till end of january) 0,3
Foreign language 0,1

Semester 2

Technical courses

Name of the Module Total number of ECTS
Data science fundamental courses Semester 2 6
Subject Coeff. Shared with
Data valorization 3 MAM4 from early Jan till end of April
Computer vision and machine learning 3 Specific EIT, spread in empty slots till end of May
Data science complementary courses Semester 2 , that could be selected if no time schedule conflicts, for a total of at least: 9
Subject Coeff. Shared with
Personal or in group project in Data science (can be continuation of sem. 1)* 3 N/A
Embedded A.I., Sensors&Actuators 3 SI4 from early Jan till end of April
Parallelism 3 SI4 from early Jan till end of April
From low level to high level protocol networks 3 SI4 from early Jan till end of April
Algorithmics 3 SI4 from early Jan till end of April
Functional and data description languages 3 SI4 from early Jan till end of April
Optimisation(FR) 3 MAM4 from Jan till end of April
Séries temporelles 3 MAM4 from Jan till end of April
Combinatorial optimization 3 M1 Info
Operational research 3 M1 Info
Software engineering 3 M1 Info
Internet of the future 3 M1 Info
Graphs 3 M1 Info
Web 3 M1 Info

Innovation & Entrepreneurship courses

I&E Semester 2 (15  ECTS) Coefficient
Business Intelligence 2: Marketing & Consumer Experience 0,2
I&E complementary course 0,2
Foreign language 0,1
Business Dev. Lab  (spread in the empty slots, from early march till mid of June) 0,3
Summer school : globally organized by EIT Digital, July-August  0,2

Second Year EIT Digital track in Data Science

Semester 3

Mandatory as elective courses are most of the times spread on either of the two periods (quarters of consecutive 8 weeks including last one for the written exam). The semester lasts from early september up to early march.  

Compulsory courses (6 ECTS)

Period 1 Mandatory courses  Schedule
Panorama of Big Data technologies Monday morning Coefficient 2
Data Science: include seminars from industrial local partners Monday afternoon Coefficient 2

Period 2 Mandatory courses Schedule
AI engineering Tuesday morning Coefficient 2

Elective courses (12 ECTS)

Elective courses list 2023-24 Topic Schedule Coeff
Statistical machine learning (Period1 and 2) Data modeling and analysis From mid Oct. till  mid Jan.., Sciences faculty campus NICE, Valrose, 2+2
Statistical computational methods, CART and random forests for high-dimensional data (Period 1 and 2) Data modeling and analysis Friday afternoon 1:30 pm,to 4:30 a priori from mid Sept. till Dec. Sciences faculty campus NICE, Valrose 2+2
Deep learning (Period 1)  Data modeling and analysis Period 1, Tuesday afternoon 2
Advanced Data mining (Period 2) Data modeling and analysis Period 2, Tuesday afternoon 2
Advanced topics in deep learning (Period 2) (more Maths oriented) Data modeling and analysis Period 2, Monday afternoon 2
Advanced deep learning (Period 2) (more CS oriented) Data modeling and analysis Period 2, Monday afternoon 2
Graph algorithms and combinatorial optimization (Period 1) Data modeling and analysis Period 1, Tuesday afternoon 2
Machine learning for image analysis (Period 1) Application of data science, in particular on multimedia content and data on the web Period 1, Friday afternoon 2
Machine learning for networks (Period 2) Application of data science, in particular on multimedia content and data on the web Period 2, Tuesday morning 2
Text mining and NLP (Period 2) Application of data science, in particular on multimedia content and data on the web Period 2, Monday morning 2
Web of linked Data (Period 1) Application of data science, in particular on multimedia content and data on the web Period 1, Tuesday morning 2
Semantic Web (Period 2) Application of data science, in particular on multimedia content and data on the web Period 2, Tuesday afternoon (prerequisite: web of data) 2
Knowledge Engineering (Period 1) Application of data science, in particular on multimedia content and data on the web Period 2, Monday morning (prerequisite: web of data) 2
Réalité virtuelle (Period 2, in French? TBC) Application of data science, in particular on multimedia content and data on the web Period 2, Friday morning 2
Security and privacy 3.0 (Period 2) Data processing supporting technologies Period 2, Tuesday afternoon 2
Sécurité des applications web (Period 2, in French) Application of data science, in particular on multimedia content and data on the web Period 2, Tuesday morning 2
Blockhain and privacy (Period 2) Data processing supporting technologies Period 2, Monday morning 2
Peer to Peer (Period 1) Data processing supporting technologies Period 1, Tuesday morning 2
Virtualized infrastructures in cloud computing (Period 1) Data processing supporting technologies Period 1, Tuesday morning 2
Large Scale Distributed Systems (Period 2) Data processing supporting technologies Period 2, Tuesday afternoon 2
Multimedia networking (Period 2) Data processing supporting technologies Period 2, Friday morning 2
Evolving internet (Period 1) Data processing supporting technologies Period 1, Friday morning 2
Techniques modernes de programmation concurrente (Period 1, in French) Data processing supporting technologies Period 1, Monday afternoon 2
Full stack software engineering for the Internet of Things (Period 1) Data processing supporting technologies Period 1, Monday morning 2
French as a Foreign Language. On top of program. (Period 1) Period 1

Project Fin d'Etudes in Data science (6 ECTS)

Project Fin d'Etudes Schedule
Personal research and/or development project in Data Science, individual or in small teams (up to 4 people) Starts september till  early march, 4 weeks, almost full time in feb 6 ECTS

Innovation and Entrepreunership module (6 ECTS)

Besides, the student must develop a mandatory Innovation and Entrepreneurship (I&E) work of 6 ECTS, as mandated by EIT Digital I&E common specification of masters. This work is coached by the UCA coordinator in I&E and spans the whole October-Early March period once per two weeks approximatively starting early october. The goal is to reuse on-line I&E material from the Moodle, common to all EIT Digital masters, and apply this to selected business cases. These business cases are most of the time proposed by the various EIT Digital Action Lines partners and the local ecosystem.

Semester 4

Internship/Master thesis (30 ECTS, 4 to 6 months max)

This internship can be done either in our partner research institutions teams at I3S, LJAD, INRIA even if for EIT Digital students, industrial internship is the preferred choice. We provide support and guidance to this aim. Including for outside the Nice - Sophia-Antipolis Technology park. The evaluation of the internship work encompasses three aspects: work achieved as measured by the internship supervisor, written thesis submitted at the end of August and evaluated by the university supervisor, oral defense organized early September (can happen in visio conference mode) and evaluated by a jury of professors. Positions as employee in a company can also be turned as the mandatory period for preparing the master thesis, as soon as the content is approved by the track local coordinator.

Project subjects and internships of former students


This is one way to let known who are the students that have studied one year in Data Science at UCA. This includes the name of their exit point, or respectively entry point. And what are the topics that they have been able to be in touch with. For Master 2 students, is also indicated the title of their master thesis, where they prepared it, and if available, where they are now employed.

Master 1, Cohort 2015-16

Project Topic/Title Team Student(s)
Car Embedded Raspberry PI implementation of machine learning algorithms MinD/Sparks CNRS I3S Ivan Lopez Moreno (TUB), Fabi Eitel (UPM), Diego Burgos Sancho (UPM)
Computing continuous SPARQL queries using Bloom filters over RDF streams on Storm and Grid'5000 platforms Scale/Comred CNRS I3S Usman Younas (TUB), Sander Breukink (TU/e)
Optimized hyper-parameters for deep architectures MinD/Sparks CNRS I3S Joana Iljazi (TU/e)
Deep Neural Style Adaption in Music MinD/Sparks CNRS I3S Fabi Eitel (UPM)
Data analytics applied on tweets Alcmeon Start-up Ivan Lopez Moreno (TUB), Diego Burgos Sancho (UPM)
SecTracks: a cybersecurity company that uses Open Data to predict threats as exposed by a tool that predicts attacks BDL project (including POC) in collaboration with SAP labs, Sophia-Antipolis Henny Selig (KTH), Joana Iljazi (TU/e), Zhanjie Zhu (TU/e)
Air tickets price optimization using social networks data BDL project (including POC) in collaboration with Amadeus, Sophia-Antipolis Sander Breukink (TU/e), Bo Li (TUB), Diego Burgos Sancho (UPM)
Optimising the maintenance of city bikes BDL project (including POC) in collaboration with Antibes municipality Ivan Lopez Moreno (TUB), Fabi Eitel (UPM), Siqi Li (TU/e), Usman Younas (TUB)

Master 1, Cohort 2016-17

Project Topic/Title Team Student(s)
Observatoire du discours politique français MinD/Sparks CNRS I3S and BCL UNS laboratory Veeresh Elango (KTH), Nazly Santos Buitrago (TU/e), Luis Galdo (TU/e), Juan Gonzales Huesca (TU/e)
A pruning method to compress deep network MinD/Sparks CNRS I3S Tongtong Fang (KTH)
A middleware to support continuous RDF data querying Scale/Comred CNRS I3S Ma Xin (TU/e), Hamed Mohammadpour (KTH)
Security solutions for big data systems (research papers study) Sparks CNRS I3S Marcos Bernal (UPM)
Jathagam: a solution for finding cyber security for big data BDL project in collaboration with SAP research lab (Sophia-Antipolis) Veeresh Elango (KTH), Nazly Santos Buitrago (TU/e), Luis Galdo (TU/e), Juan Gonzales Huesca (TU/e)
Smart Grid Security (SGS) Solutions BDL project in collaboration with SAP research lab (Sophia-Antipolis) Ma Xin (TU/e), Hamed Mohammadpour (KTH), Tongtong Fang (KTH), Marcos Bernal (UPM)

Master 2, Cohort 2016-17

Project and Internship Topic/Title Team Student(s)
Principal Component Analysis: theoretical properties in high dimension LJAD CNRS Yang Song (TU/e)
Development of a JSON Library for satisfaction surveys on mobile devices Zenith INRIA Ignacio Uya Lasarte (UPM)
Play Outside own group, startup project Argan Veauvy (UPM), Loic Lavillat (UPM), Justin Vailhere (UPM)
RGB-D store navigation through immersive techniques and sensor Lagadic INRIA Yolanda De La Hoz (UPM)
In-depth understanding of deep learning MinD/Spark CNRS I3S Hausmane Issarane (UPM)
CREDIT SCORE PROJECT DEVELOPMENT BASED ON QUNAR’S USER FEATURES Qunar.com, Being China Yang Song (TU/e)
DESIGN AND IMPLEMENTATION OF PARALLEL OPERATORS FOR A DISTRIBUTED QUERY ENGINE Leanxcale, Mardid, Spain Ignacio Uya Lasarte (UPM)
Large Scale Video Description on
YouTube-8M dataset
Mind/Spaks I3S CNRS Yolanda De La Hoz (UPM)
Creation of Data Science tools for Natural Language Processing and data visualization internal displacement monitoring centre (idmc), Geneve, Switzerland Hausmane Issarane (UPM) [now as EIT Digital post doc]
Operational Customer exPerience Air France KLM, Sophia-Antipolis Argan Veauvy (UPM) [now in ADP, Roissy]

Master 1, Cohort 2017-18

Project Topic/Title Team Student(s)
Deep Learning Spell Check MinD/Sparks CNRS I3S and BCL UNS laboratory Eliane Birba (KTH), Upsana Biswas (TU/e), Ponathipan Jawahar (TU/e)
Deep MNREAD Biovision INRIA & MinD/Sparks CNRS I3S Adriana Janik (KTH)
Geo Detection SAP Labs (Mougins) Carlos Callejo (Aalto)
Multiple Instance Learning for segmenting video content based on audio information Widmoka (Sophia Antipolis) & MinD/Sparks CNRS I3S José Diaz Mendoza (TU/e)
Analysis of adverse drug events in the French primary care database PRIMEGE MinD/Sparks CNRS I3S & CHU Nice Jacqueline Neef (UPM) [now IBM Madrid]
Computing images similarity using deep learning MinD/Sparks CNRS I3S & Bentley Antoine Lain (Aalto) [now PhD candidate, Edimburgh]
Deep learning for counting in crowds MinD/Sparks CNRS I3S Ion Mosnoi (Aalto)
Labeled topic classification Meritis Lab Guo Lei (Aalto) [now BMW, Munich]

Master 2, Cohort 2017-18

Project or Internship Topic/Title Team Student(s)
Action elasticity compensation in video classification MinD/Spark CNRS I3S Emily Söhler (UPM), Dane Mitrev (UPM), Luca Coviello (UPM), Antonio Paladini (POLIMI)
Joconde Learn Wimics-MinD/Spark CNRS I3S/INRIA Dina Mohamed Mahmoud (UPM), Sara Zanzottera (POLIMI)
Labeled topic classifier Meritis Labs Jaime Boixados (UPM)
Tensor and matrix factorizations in Python: application to recommender systems SIS CNRS I3S Claus Jungblut (UPM), Miguel Zaballa Pardo (TU/e)
Assessment of the quality and relevance of automatic tests Amadeus Lorenzo Frigerio (POLIMI), Alessandro Polenghi (POLIMI), Ivan Vigorito (POLIMI)

Long term digital data storage on DNA

SIS CNRS I3S Jose Luis Contreras (UPM), Riccardo Lo Bianco (POLIMI)
Multi-language topic classifier Meritis Lab (Sophia-Antipolis) Jaime Boixados (UPM) [now at Meritis, Paris]
Semantic segmentation on satellite imagery with
Deep Learning
Amazon Web Service (Berlin) Jose Luis Contreras (UPM) [now at AWS, Berlin]
Deep Neural Networks and Precision Agriculture for Grape Yield Estimation Fondazione bruno kessler (Trento) Luca Coviello (UPM)
Data anonymization through Generative Adversarial Networks in the differential Privacy scenario SAP Labs (Mougins) Lorenzo Frigerio (POLIMI)
Business intelligence for e-commerce Otto (GmbH & Co KG) (Hamburg) Claus Jungblut (UPM) [Virtuagym, a Columbia/NL company]
Clustering techniques for DNA signal reconstruction I3S CNRS Riccardo Lo Bianco (POLIMI)
End-to-end Multiple Object Tracking with
Convolutional Recurrent Neural Networks
Renault Software Labs (Sophia-Antipolis) Dane Mitrev (UPM)
Machine Learning in Transportation Data Analytics SWVL company (Cairo) Dina Mohamed Mahmoud (UPM) [CIB, Cairo)]
End-to-end Models for Lane Centering in Autonomous Driving I3S CNRS & Renault Soft. Labs Antonio Paladini (POLIMI)
Test quality analyses Amadeus (Sophia-Antipolis) Alessandro Polenghi (POLIMI)
Machine learning techniques for the detection and prediction of Multiple Sclerosis Berlin Center for Advanced Neuroimaging (Berlin) Emily Söhler (UPM)
Power Forecasting Models for Renewable Energy Sources Edison (EDF Group), Milano Ivan Vigorito (POLIMI) [Edison]
Live Data Sampling for Analytics Amadeus (Sophia-Antipolis) Miguel Zaballa Pardo (TU/e)
Evaluation of User Interface Technologies for Accelerator Controls CERN (Geneva) Sara Zanzottera (POLIMI)

Master 1, Cohort 2018-19

Project Topic/Title Team Student(s)
Detection of actions in Sports Videos using Multiple Instance Learning MinD/Sparks CNRS I3S Sherly Sherly (KTH)
Deconvoluted and distributed Deep CNNs for ECG classification MinD/Sparks CNRS I3S Ziqing DU (TU/e), Yaowei LI (Aalto)
Counting people in the tram MinD/Sparks CNRS I3S Jinrui LIU (KTH/Aalto/VCC)
Machine learning for healthcare Computing biomarker and pathway for cancer diagnostic using metabolic data Mediacoding/SIS CNRS I3S & Medecine faculty Chenchen HE (UPM)
Machine learning for biomedical: Localizing atrial flutter circuits using machine learning techniques on electrocardiograms (premilinary) CNRS LEAT laboratory Alessio MOLINARI (KTH)
Mobility for Seniors Invent@UCA Cristina RIOS IRIBARREN (UPM)
TrustSpace Invent@UCA Ignacio SANCHEZ (TU/e)
Deep learning for non linear regression problems (very preliminary) MinD/Sparks CNRS I3S Ignacio GARCIA MARTIN (Aalto)
DRL for communication networks (premilinary) Signet/SIS CNRS I3S Dana TOKMURZINA (Aalto)

Master 2, Cohort 2018-19

Project or Internship Topic/Title Team Student(s)
A Bio-Inspired Approach to Image Recognition LEAT CNRS Luca Comoretto (POLIMI)
Deep Reinforcement Learning for Solving Network Optimization Problems Signet/SIS CNRS I3S Mickaël Bernard (UPM)
Analytics of the Spain basket league results and performances Own project creation, ACB Analytics Ricardo Garcia Garcia (UPM), Rodrigo Rosado Gonzalez (UPM), Francisco Santos (UPM)
Nouvelles expériences clientes grâce à des modèles d'IA Accenture SAS France, Sophia-Antipolis Mickaël Bernard (UPM) [now PhD Candidate Univ Nebraska Lincoln, USA]
Machine learning demos/POC and action recognition learning Atos integration, Sophia-Antipolis Nasseredine Bajwa (UPM)
From payment transactions to a structured network: Key companies Identification, Risk Assessment and Graph Mining UniCredit, Wien (Austria) Comoretto Luca (POLIMI) [now ECB Frankfurt]
SAP Predictive maintenance IECISA (Spain) Alvaro Gallego (UPM)
Machine learning for analysis of multimedia content Pragsis Technologies, Madrid Ricardo Garcia Garcia (UPM)
DNA FOR COLD DATA ARCHIVING: USING MACHINE LEARNING FOR ROBUST DECODING Mediacoding/SIS CNRS I3S Eva Gil San Antonio (UPM) [now PhD candidate UCA]
Audit Logs and Metadata Pragsis Technologies, Madrid Francisco de Borja Gonzalez Conzalez (UPM)
Design of a toolbox allowing the recognition / detection and prediction of one or more behaviors on a client system in real time Alten, Sophia-Antipolis Rodrigo Rosado Gonzalez (UPM) [Alten]
Intelligent drone tracking system: design and development of IDTS cloud platform IDTS (Spain) Francisco Santos (UPM)
Deep Speech Recognition in noisy environment NXP semiconductors, Sophia-Antipolis Frederico Ungolo (UPM)
Hotel big data smart cache prototype Amadeus, Sophia-Antipolis Yirui Wang (UPM)

Master 1, Cohort 2019-20

Project Topic/Title Team Student(s)
NAMB Scale/Comred CNRS I3S Seyed Farzam Mirmoeini (UPM)
Deep learning networks as Process networks Keros/Comred CNRS I3S/INRIA Li Yang (ELTE)
Génération d’emplois du temps d’infirmières. MC3 CNRS I3S Zhaopeng Tao(KTH), Rui Zhang (TU/e)
Towards an evaluation of the carbon footprint of digital activities Sparks CNRS I3S Md Nurain Haider (TUB)
N/A UCA Yidan Cai (TU/e)
N/A UCA Juan Alvarez (KTH)
Thomas Van Dommelen (UPM)
Comparaison des performances de codes de calculs scientifiques : C++ versus Java Keros/Comred CNRS I3S/INRIA Lin Sinan(Aalto)

Master 2, Cohort 2019-20

Project or InternshipTopic/Title Team Student(s)
A DSL for safety validation of Autonomous Vehicles Keros/Comred CNRS I3S/INRIA Rafael Mosca (POLIMI)
What next? When next? Amadeus Sophia-Antipolis Jacek Wachowiak (KTH)
Bias Mitigation MinD/Sparks CNRS I3S Victoria Hedenmalm (KTH)
Prediction of hospital readmission MinD/Sparks CNRS I3S Lorenzo Foà (UPM)
Medical Text Analysis MinD/Sparks CNRS I3S Puneet Beri (TU/e)
NAMB- A High-Level Benchmark Generator for Stream Processing Platforms Scale/Comred CNRS I3S Ankita Pillay (KTH)
Spiking neural networks for event-based stereovision Sparks CNRS I3S Rafael Mosca (POLIMI)
Clustering of investment funds‘ business models and characteristics ECB Frankfurt Jacek Wachowiak (KTH)
Automatic Modeling of Critical Control Systems for IT Infrastructure
Merging Information with Trust Networks
KTH and FOI Victoria Hedenmalm (KTH)
Customer behaviour analytics JAKALA spa -Milano Lorenzo Foà (UPM)
Detection of Motion Artifacts in Thoracic CT Scans THIRONA Nijmegen, NL Puneet Beri (TU/e)
Energy Evaluation For Buildings Myrspoven, Stockholm Ankita Pillay (KTH)

Master 1, Cohort 2020-21

Project or InternshipTopic/Title Team Student(s)
Synaptic delays for temporal pattern recognition Sparks CNRS I3S Nicolas Arrieta Larazza (UT)
Nerea Ramon Gomez (UT)
Ivan Zabrodin (UCA)
Detecting Offensive Posts in Social Media Wimics-Sparks/CNRS I3S/INRIA Mariia  Solodiankina (next: ELTE)
Deep Learning as applied to medical diagnostics Masai-Sparks/CNRS I3S/INRIA DhivinJoshua Nelson (UT) Zhijie He (next: AALTO)
Classification of Spiking Neural Networks Prediction Sparks CNRS I3S Thuany Stuart(KTH)


Master 2, Cohort 2020-21

Project or InternshipTopic/Title Team Student(s)
Comprehensive Study of Neuromorphic Computing
and Spiking Neural Networks
Sparks CNRS I3S Gabriele Zambra (UPM)
Yazan Salti (UPM)
Development of Spark-Kafka Applications for Data Retrieval
concerning the Migration of the Cluster from IBM BigInsights to Cloudera 7.1
Reply S.p.A. Milano Gabriele Zambra (UPM)
Bug report classification: A comparison of machine learning approaches Ericsson Yazan Salti (UPM)

Master 1, Cohort 2021-22 

Project or InternshipTopic/Title Team Student(s)
Mixture of linear regressions for clustering of trajectories SIS CNRS I3S Mattia Arsendi (AALTO)
Online hate speech detection Wimics-Sparks/CNRS I3S/INRIA Lynda Attouche (Erasmus POLIMI)
Transformers Explainability Masai Sparks/CNRS I3S/INRIA Lynda Attouche (Erasmus POLIMI)
Descriptive and Inference Analysis of the ACQUA Dataset DIANA INRIA Lenny Klump (TU/e)
Crypto Bot and Alerting System UCA Ilaria Enache (UT)
Taylor Lucero (UTrento)
Analysis of a research paper about Numerical study of distortion
approximation of a compressed softmax layer
SIS CNRS I3S Zeyneb M'HAMEDI (UCA local student)
Stereo vision, Event camera Sparks CNRS I3S Yazaman Pazhoolideh (KTH)


Master 2, Cohort 2021-22 

Project or InternshipTopic/Title Team Student(s)
Semi-automated labeling of Time Series
for anomaly detection
EZAKO, Sophia Abetayeva Anar (AALTO) [now at Ezako]
Assessing and improving Data Quality using
Machine Learning and control charts
TIP Trailer Services Stefano D'Angelo (POLIMI) [now at TIP]
NLP for startup industry classification Novable, Brussels Giuseppe Dimonte (POLIMI) [now ATA Italy]
AI-Assisted for Modeling Multitasking Driver Aalto Univ. school of science Hossein Firooz (AALTO) [now Sony AI Zürich]
Web development Fortinet, Sophia Antipolis Otto Makinen (UCA) [now Fortinet Sophia]
Automated insights extraction from a text with
Amazon Web Services: Pastlab
AWS Madrid Arturo Pinar (UPM) [now Ibermatica, Spain]
Detecting Body Languages from interaction videos INRIA STARS Akos Tánczos (UPM) [now Bosch, Hungary]
Batch effect correction for Toxicogenomics data using
Machine Learning and Deep Learning approaches
Univ of Laval, Québec Ivan Zabrodin (UCA) [now zz]

Master 1, Cohort 2022-23 

Project or InternshipTopic/Title Team Student(s)
Human performance assessment of downscaled event data Sparks, CNRS UCA I3S Bueno Garcia Marina (UNITN)
Kupczyk Eva (UPM)
Trillo Carreras Lucia (UNITN)
yyy xxx Ciesielski Tymoteusz (UPM)
yyy xxx Malatinski Zsombor (UTurku)
Human body parsing Masai Sparks/CNRS UCA I3S/INRIA Raspanti Frederico (TU/e)
yyy xxx Van der Heijden Niels (UTwente)


Master 2, Cohort 2022-23 

Project or InternshipTopic/Title Team Student(s)
ve-NeRF: Velocity and Pose Parameterized Event Generating NeRF
for anomaly detection
CNRS UCA I3S, Sophia-Antipolis Abdikharim Aziz (UPM) [now at xxx]
Evaluation of Explainability Methods for Neural Natural Language Processing LAMSADE, Univ Paris Dauphine Attouche Lynda (Erasmus at POLIMI) [now at xxx]
Efficient 3D model retrieval for Industrial Metaverse applications Siemens AG Di Domenico Alessio (POLIMI) [now xxx]
Modeling, development and improvements on B2B banking Data Analysis Processes Management solutions Freyre Gomez Eduardo (UPM) [now xxx]
Deep active visio-tactile human pose estimation for intelligent interactive interior BMW research and technology house Fumelli Chiara (POLIMI) [now xxx]
Application of transformers in scientific literature mining Rays of space Oy Isavnina Kseniia (ELTE) [now xxx]
Data science and ML Nyris Gmbh Kubelka Laurin (UPM) [now xxx]
Aide à l’orientation dans le supérieur : visualisation d’une forêt aléatoire CNRS UCA I3S, Sophia-Antipolis M'hamedi Zeyneb (UCA) [now xxx]
Data analyst Airbus Operations Gmbh Martin Lesmes Rafael (UPM) [now xxx]
Privacy preserving machine learning DEIB, Politecnico de Milano Pazzi Riccardo (POLIMI) [now xxx]

Workflow aware Access Control for the Industrial Metaverse in a Multi party environment
 
Siemens Pizzamiglio Giacomo (POLIMI) [now xxx]
Digital transformation Loro Piana S.P.A. Ruaro Giovanni (POLIMI) [now xxx]
Operations Stragegy and Analytics Hellofresh SE Schweiker Marcel (UPM) [now xxx]