Research Days 2022

October 20 and 21, 2022

Each year, the Labex DigiCosme organizes Research Days whose objective is to present the work carried out within the teams supported by the Labex DigiCosme.

These days will also be an opportunity to discuss the future of the LabEx, beyond December 2022. From 2023, the Graduate Schools (for the University of Paris-Saclay) and the Departments (for the Institut Polytechnique de Paris) will take over from the LabEx Digicosme in scientific animation.

You are cordially invited to participate in these transition research days.


Thursday, October 20

9:00 a.m – 9:30 a.m breakfast at the Kfé 

9:30 a.m – 9:45 a.m Opening session – amphithéâtre Dorothy Hodgkin

9:45 a.m – 10:45 a.m Invited speaker Grégory Batt, Research Director – Inria and Institut Pasteur , amphithéâtre Dorothy Hodgkin

Title: Experimental and computational methods for synthetic biology and cybergenetics

10:45 a.m – 11:00 a.m Coffee break au Kfé

11:00 a.m – 12:00 p.m Presentations of doctoral students amphithéâtre Dorothy Hodgkin

  • Mehdi Zadem, LIX, Goal Space Abstraction in Hierarchical Reinforcement Learning via Set-Based Reachability Analysis
  • Gian Karlo Aguirre-Samboni, Inria Saclay, Ecosystem causal analysis using Petri nets unfoldings
  • Felipe Lisboa, LTCI, A Formal Approach to Designing Real-Time Memory Controllers

12:00 p.m – 2:00 p.m Lunch – ENS Paris-Saclay au Kfé by Health Inside (4, avenue des sciences)

2:00 p.m – 3:30 p.m Round table: Digicosme beyond 2022 amphithéâtre Dorothy Hodgkin

3:30 p.m – 4:00 p.m Pitch poster (M2 students and doctoral students)

4:00 p.m – 4:15 coffee break at Kfé

4:15 p.m – 5:00 p.m Poster session

  • Amélie Ledein, Inria Saclay, Interoperability and formal semantic proofs
  • Manon Blanc, LIX, A characterization of polynomial time computable functions from the integers to the reals using discrete ordinary differential equations
  • Li Jingyi, Computing the Rank Invariant for Persistence Bimodules
  • Paul Patault, LMF, Pattern matchning: Exhaustive tests for exhaustiveness check
  • Mouhamadou Tidiane Mangassouba, FaaSBoost: When serverless meets persistent memory
  • Vincent Bonczak, LIX, Creation and Exploration of Multiresolution 3D Sketches with Unlimited Zoom Scales
  • Mohamed Bassiouni, CEA LIST, Verifying quantum circuits equivalence in the path-sum formalism
  • Mohammed Abdullah, SAMOVAR, TBA
  • Hussein Awada, L2S, Resource Allocation in LoRaWAN Networks
  • Saloua Bouabba, DAVID , FL4Mobility: A federated learning approach for privacy of semantically enriched mobility data
  • Mehdi Benhelal , SAMOVAR, Techniques to reduce reinforcement learning time
  • Clément Bernard, IBISC, Resource Allocation in LoRaWAN Networks
  • Thibaut Soulard, LISN, Knowledge-based Entity Linking in Heterogeneous Knowledge Graphs at Web-Scale

4:45 p.m – 5:45 p.m Invited speaker Sébastien Destercke, researcher at CNRS – HEUDIASYC

Title: Uncertainty in learning: from prediction to data

Access to the presentation here 

Amphithéâtre Dorothy Hodgkin

Friday, October 21

9:00 a.m – 9:30 a.m Welcome coffee at the Kfé

9:30 a.m – 10:30 a.m Invited Speaker: Jakob Hoydis Principal Research Scientist – NVIDIA

Title : Machine Learning for Wireless Communications

Amphithéâtre Dorothy Hodgkin

10:30 a.m – 11:30 a.m Presentations of doctoral students

  • Goluck Konuko, LTCI, Ultra-Low Bitrate Video Conferencing With Deep Animation Coding
  • Ahmed Najjar, L2S, Design and Optimisation of a RIS based on an Electro-Magnetic approach
  • Carl de Souza Trias, SAMOVAR-LTCI, Neural Network Watermarking : between concept and practice

Amphithéâtre Dorothy Hodgkin

11:30 a.m – 11:45 a.m Coffee break at the Kfé

11:45 a.m – 12:45 p.m Presentations of doctoral students

  • Anfu Tang, MaIAGE, Injecting external information into BERT for biomedical relation extraction
  • Jialin Hao, SAMOVAR, Machine Learning for Road Active Safety in Vehicular Networks
  • Alice Lacan, IBISC, Data Augmentation with Generative Models for Transcriptomics

Amphithéâtre Dorothy Hodgkin

12:45 p.m – 1:55 p.m Lunch break 

Hall Emmy Noether

1:55 p.m – 2:45 p.m Presentation of Transverse Initiatives

  • Morgan Buisson, LTCI-L2S, Learning multi-level representations for hierarchical music structure analysis
  • NewEmma: Overview by Mihai Mitrea (Telecom SudParis)
  • Fakher Sagheer, SAMOVAR, Bayesian statistical methods for joint user activity detection, channel estimation and data decoding in dynamic wireless networks.

Amphithéâtre Dorothy Hodgkin

2:45 p.m – 3:00 p.m Conclusion

Guest speakers

  • Grégory Batt, InBio team, Inria and Institut Pasteur,  (talk 1)

Title Experimental and computational methods for synthetic biology and cybergenetics

In this talk, I will introduce synthetic biology and cybergenetics, and present recent results we obtained in these fields. Synthetic biology aims at genetically engineering cells to solve problems of biomedical or industrial interests, and cybergenetics aims at controlling natural or artificial biological processes using genetically-engineered cellular systems and automatic control. In both fields, quantitative modeling is expected to play a central role. Yet despite intense research in these fields, the gap between theory and practice remains large, and the predictive power of the models remains modest.
At InBio, we are trying to bridge this gap through the joint development of experimental and computational methods. In this talk, I will present in the first part some of our recent works on the construction of automated experimental platforms to generate high-quality data obtained in well-controlled conditions. In the second part, I will present two applications of modeling approaches that capture cellular heterogeneity to obtain quantitatively predictive models for natural and synthetic biological systems. I will conclude the presentation with perspectives on design, build, test, and learn approaches for the rational construction of synthetic biological systems.

  • Sébastien Destercke (talk 2)

Title : Uncertainty in learning: from prediction to data

“Uncertainty in learning problems can happen at different stages: in predictions, data, models. In this talk, we will start by discussing the nature of uncertainties and the mathematical tools we can use to model those. The talk will then focus on two distinct but linked issues: on the one hand quantifying uncertainties in the prediction problem, on the other hand dealing with possible uncertainties present in the learning data.”

Access to the presentation here

  • Jakob Hoydis (talk 3)

Jakob Hoydis is a Principal Research Scientist at NVIDIA working on the intersection of machine learning and wireless communications. Prior to this, he was Head of a research department at Nokia Bell Labs, France, and co-founder of the social network SPRAED. He obtained the diploma degree in electrical engineering from RWTH Aachen University, Germany, and the Ph.D. degree from Supéléc, France. From 2019-2021, he was chair of the IEEE COMSOC Emerging Technology Initiative on Machine Learning as well as Editor of the IEEE Transactions on Wireless Communications. Since 2019, he is Area Editor of the IEEE JSAC Series on Machine Learning in Communications and Networks.

He is recipient of the 2019 VTG IDE Johann-Philipp-Reis Prize, the 2019 IEEE SEE Glavieux Prize, the 2018 IEEE Marconi Prize Paper Award, the 2015 IEEE Leonard G. Abraham Prize, the IEEE WCNC 2014 Best Paper Award, the 2013 VDE ITG Förderpreis Award, and the 2012 Publication Prize of the Supéléc Foundation. He has received the 2018 Nokia AI Innovation Award, as well as the 2018 and 2019 Nokia France Top Inventor Awards. He is a co-author of the textbook “Massive MIMO Networks: Spectral, Energy, and Hardware Efficiency” (2017).

He is one of the maintainers and core developers of Sionna, a GPU-accelerated open-source link-level simulator for next-generation communication systems.