Take part in the 7th edition of the Junior Conference on DataScience and Engineering (JDSE)
Date : September 15 and 16
Place : Amphithéâtre Sophie Germain, Bâtiment Alan Turing
Campus de l’École Polytechnique
1 rue Honoré d’Estienne d’Orves
Best student presentation award
Best student poster award
This conference is mainly aimed at M2 students and third-year students from engineering schools, as well as first-year doctoral students from Paris-Saclay The objective is to give these students the opportunity to present their work scientists and their research topics at a conference with prestigious speakers from academia and industry and to develop their critical thinking.
- Gabriel Peyré Gabriel Peyre ENS ULM, Directeur de recherches au CNRS
- Nataliya Sokolovska
Title: Interpretable models in machine learning and their application in medicine
Abstract: An important aspect of practical classifiers is interpretability. Learning compact but highly accurate models that help in human decision-making is challenging. Most such simple scoring systems were constructed by human experts using some heuristics and are not optimal. In many prediction tasks such as medical diagnostics, there are many more challenges: finding optimal individual treatment; taking budget into consideration, and the budget (any finite resource such as time, money, or side effects of medications) in real-life applications is always limited. I will consider principled methods to learn interpretable simple rules purely from data. I will also show possible solutions to take the limited budget into account, and discuss some perspectives for development of methods of personalised medicine.
- Pierre Monnin
Title: Knowledge graphs: construction, matching, and mining
Abstract: In the Web of data, an increasing number of knowledge graphs (KGs) are concurrently published, edited, and accessed by human and software agents. Their wide adoption makes the three tasks of construction, matching, and mining key. The construction of KGs can rely on knowledge extraction from various types of data (e.g., text, tables). Matching consists in identifying equivalent, more specific, or somewhat similar units within and across KGs. This task is crucial since concurrent publication and edition may result in coexisting and complementary KGs. However, this task is challenging because of the inherent heterogeneity of KGs, e.g., in terms of granularities, vocabularies, and completeness. Mining aims at discovering new and useful knowledge units from KGs. Such a process faces scalability issues due to the increasing size and the combinatorial nature of KGs. In the first part of this talk, I will present my Ph.D. work on knowledge graph construction, matching, and mining with applications in pharmacogenomics. In the second part of this talk, I will focus on knowledge extraction from tabular data, namely Semantic Table Interpretation, with the DAGOBAH project. Throughout all my presentation, I will highlight the advantages of domain knowledge in the form of ontologies associated with knowledge graphs. Indeed, when considered, such domain knowledge supports the construction, matching, and mining of KGs. Finally, I will discuss the perspectives of my work and future projects.
Pierre Monnin is a researcher with the Orange Innovation/Data-AI entity of Orange. He holds a Ph.D. from the University of Lorraine, where he worked on extracting, comparing, and mining knowledge in the biomedical domain of pharmacogenomics in the context of the ANR PractiKPharma project. His Ph.D. work was awarded the “2022 best thesis award” from the French association EGC (Extraction et Gestion des Connaissances – Knowledge Extraction and Management). Pierre’s research broadly focuses on knowledge extraction, matching, and mining to build and refine knowledge graphs. He is particularly interested in uncertain knowledge management, graph embedding techniques for knowledge graphs, and hybrid approaches that combine symbolic and numeric methods. He is Proceedings & Metadata co-chair of ISWC 2022.
We will award a prize for the best oral presentation and the best poster.
The Junior Conference on DataScience and Engeneering (JDSE) is organized by students for students.
- Armita Khajeh Nassiri Ph.D. candidate at LISN & Teaching Assistant at CentraleSupélec
- Loic Omnes PhD candidate in machine learning
- Melan Vijayaratnam PhD in Machine Learning at Telecom Paris
- Cedric Adjih chercheur à l’INRIA Paris-Saclay
- Michel Kieffer responsable scientifique du LabEx DigiCosme
- Zacharie Naulet maître de conférences à l’Université Paris-Saclay
- Erwan Scornet maître de conférences à l’Institut Polytechnique de Paris
- Fariza Tahi chercheur et maître de conférences à l’Université d’Évry Val d’Essonne