Annual Meeting – 2020

The Annual DKM meeting takes place this year on February 13th and 14th in Rennes.
The first day is a meeting for the whole department, while the second day concerns only PhD students.

Below is the full program.

Organizers

  • Johanne Bakalara (Lacodam),
  • Francesco Bariatti (SemLIS),
  • Arnaud Belcour (Dyliss),
  • Kevin Da Silva (Genscale),
  • Ludivine Duroyon (Shaman),
  • Marie Le Roic (Assistants’ Service),
  • Anne Siegel (Dyliss),
  • Constance Thierry (Druid).

Day 1: Thursday, 13/02

Activity Description
Introduction DKM Presentation – Anne Siegel
Guest Lecture Mathieu Guillermin (Univ Catholique Lyon) – Ethical Challenges of AI and Big Data: The Need for Bridges

  • Abstract: Since last decades, the rapid progress of AI and big data processing techniques trigger deep worries as well as optimistic enthusiasm. Steering technological development in these fields becomes a more and more pressing challenge, reinforced by the high pace at which research breakthroughs in the domain of information technologies are transferred to societally implemented applications. In this presentation, I will discuss the form ethical investigation could take to ensure an enlightened development of AI and big data technologies. I’ll mobilize different case studies to highlight the importance of building bridges not only between different types of expertise, but also between experts and users or impacted persons.
  • Slides: PDF
Highlights
  • Structuring and analyzing data according to domain knowledge
    • Zoltan Miklos (Druid): Reconstruction automatique de l’histoire des sciences, façon Big Data
    • Olivier Dameron (Dyliss): Increasing life science resource re-usability with Semantic Web technologies
  • Improving performance and expressivity of data management and representation frameworks
    • Pierre Peterlongo (GenScale): A resource-frugal probabilistic dictionary and applications in bioinformatics
  • Guiding data exploration
    • Sébastien Ferré (SemLIS): Sparklis: an expressive query builder for SPARQL endpoints with guidance in natural language
  • Methods for extracting complex features and knowledge from data
    • Christine Largouët (Lacodam): Anomaly detection with extreme value theory
    • Grégory Smits (Shaman): Génération efficace d’estimations fiables de résumés linguistiques
Speed-dating Session Instructions:

  • Go to rooms Petri, Markov, or Turing.
  • Find the board matching the color of your badge.
  • Locate your partner’s name on the board and identify them.
  • You have 10 minutes to chat; suggested topics will be available on the tables.
  • After 10 minutes, find your next partner and repeat.
Guest Lecture Benoit Frenay (Namur) – Machine Learning: Getting Back Into the Loop

  • Abstract: Machine learning provides powerful predictive tools, but it often limits user control over decisions. This presentation covers methods to address these limitations, including interpretability in dimensionality reduction, embedding user feedback in Bayesian PCA, and enforcing constraints in decision trees.
  • Slides: PDF
Highlights
  • Structuring and analyzing data according to domain knowledge
    • David Gross-Amblard (Druid): Le crowdsourcing au delà d’Amazon Mechanical Turk
    • Claire Lemaitre (GenScale): Multiple comparative metagenomics using multiset k-mer counting
  • Improving performance and expressivity of data management and representation frameworks
    • François Goasdoué (Shaman): Gestion efficace de bases de données en présence de contraintes ontologiques
  • Guiding data exploration
    • Anne Siegel (Dyliss): Scalable analysis of families of metabolic-based biological systems
  • Methods for extracting complex features and knowledge from data
    • Elisa Fromont (Lacodam): Cost-sensitive imbalanced classification
    • Peggy Cellier (SemLIS): Graph mining for knowledge graphs
Round Table: Future of Health Data Moderators: Constance Thierry and Johanne Bakalara

  • T. Allard (Druid): Confidentiality
  • L. D’orazio (Shaman): Distributed computation
  • T. Guyet (Lacodam): Query classes and knowledge representation
  • D. Lavenier (Genscale): Future health genomics data
  • O. Ridoux (SemLIS): Energy impact
  • N. Théret (Dyliss): Ethical issues

Day 2: Friday, 14/02

Activity Description
Workshop How (Not) to Fail Your Poster – Emmanuelle Becker (Dyliss)Slides: PDF
PhD Student Presentations
  • Kévin Da Silva (Genscale): Strain identification in metagenomics using variation graphs
  • Hugo Talibart (Dyliss): Protein homology search via residue coevolution
  • Rituraj Singh (Druid): Reducing crowdsourcing aggregation costs
  • Thi To Quyen Tran (Shaman): Filter-based fuzzy big joins
  • Colin Leverger (Lacodam): Clustering-based seasonal time series forecasting
Flash Poster Presentations (1 minute per person, timer in effect)
PhD Student Presentations
  • Mael Conan (Dyliss): Predicting genotoxicity during liver fibrosis
  • Johanne Bakalara (Lacodam): Temporal model for medico-administrative data
  • Tompoariniaina Andriamilanto (Druid): Browser fingerprinting for web authentication
  • Van Hoang Tran (Shaman): Big data management in cybersecurity
  • Francesco Bariatti (SemLIS): Graph pattern selection via Minimum Description Length
Buffet with Posters
  • Marine Louarn (Dyliss): Reusability of life science resources with the Semantic Web
  • Ian Jeantet (Druid): Mapping scientific evolution
  • Ludivine Duroyon (Shaman): Linked Data for Facts, Statements, Beliefs
  • Méline Wery (Dyliss): Identifying causal signatures using omics data integration
  • Aurélien Lamercerie (SemLIS): Algebra for deterministic acceptance automata in cyber-physical systems
  • Erwan Bourrand (Lacodam): Discovering useful compact sequential rule sets
  • Lolita Lecompte (Genscale): SVJedi: Structural variation genotyping with long reads
  • Nicolas Guillaudeux (Dyliss): Insights into transcript isoforms across species
  • Grégoire Siekaniec (Genscale): Streptococcus thermophilus strain differentiation by Nanopore sequencing
  • Joris Dugueperoux (Druid): Ensuring confidentiality and efficiency in crowdsourcing platforms
  • Yichang Wang (Lacodam): Interpretable shapelet learning for time series classification
  • Constance Thierry (Druid): Future monitoring strategies
  • Heng Zhang (Lacodam): Multi-spectral object detection for day-long video surveillance

Comments are closed.