PhD students – past
- Bishnu Sarker, November 2017 – April 2021, co-advising (50 %) with Dave Ritchie (Until Sep., 19) and Marie-Dominique Devignes (From Sep. 19): « Developing distributed graph-based approaches for large-scale protein function annotation and knowledge discovery«
- Wissem Inoubli, September 2016 – January 2021, co-advising (30%) with Engelbert Mephu Nguifo, Haithem Mezni and Mondher Maddouri: « Mining and Analysis of Dynamic graphs: Case of graph clustering«
- Manel Zoghlami, September 2015 – December 2019, co-advising (40%) with Engelbert Mephu Nguifo (30), Mondher Maddouri (20%) and Amel Borgi (10): « Multiple instance learning approaches for ionizing-radiation-resistance prediction «
PhD students – current
- Kamrul Islam, since November 2019, co-advising (50%) with Malika Smail-Tabbone: « Distributed link prediction in large complex graphs: application to biomolecule interactions »
Master students
- Mohammed Khatbane, 2021/2022, , co-advising (50%) with Malika Smail-Tabbone: « link prediction in distributed knowledge graphs ».
- Yan Leprun, 2021/2022, , co-advising (30%) with Malika Smail-Tabbone and Pascal Moyal: « Apprentissage par renforcement pour des modèles de greffes d’organes ».
- Hadia Jalil, 2020/2021, co-advising (30%) with Yannick Toussaint and Frédéric Borges: « Predicting long-term diversity in bacteria populations by graph-based machine learning approaches ».
- Amal Stiti, 2019/2020, 100%: « Protein function annotation of large and distributed protein graphs ».
- Navya Khare, 2018/2019, 100%: « Graph Based Automatic Protein Function Annotation Improved By Semantic Similarity ».
- Zied Hermi, 2015/2016, co-advising (50%) with Haithem Mezni: « Frequent subgraph mining in large single graphs ».
- Chayma Sakouhi, 2014/2015, co-advising (30%) with Alberto Montresor and Salma Sassi: « Edge-based graph partitioning of large dynamic graphs« .
- Cyrine Arouri, 2013/2014, co-advising (30%) with Engelbert Mephu Nguifo, Cécile Roucelle and Gaelle Bonnet: « Towards a constructive multilayer perceptron for regression task using non-parametric clustering. A case study of Photo-Z redshift reconstruction ».
Other
- Alex Goarant, 2021/2022, Engineering school: 2nd year
- Guillaume Lassagne, 2019/2020, Engineering school: 2nd year
- Manar Amezrine, 2019/2020, Engineering school: 2nd year
- Tristan Durey, 2019/2020, Engineering school: 2nd year
- Damien Vantourout, Engineering school: 2nd year
- Cydric Mea, Engineering school: 2nd year
