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Axel Hutt
Additive noise tunes the stability of high-dimensional systems
18 janvier 2024 - 09:00Salle de conférences IRMA
Experimental brain activity is known to show oscillations in specific frequency bands, which reflects neural information processing. For instance, strong oscillations at about 2Hz reflect tiredness and sleepiness, strong 40Hz oscillations indicate alertness. Changes of power in frequency bands indicate changes in information processing. For instance, it has been observed that strong activity about 10Hz and 2Hz emerge in electroencephalographic activity (EEG) when a subject loses consciousness in general anaesthesia. Numerical simulations of stochastic neural models have shown that such a change can be reproduced by changing the variance of external additive Gaussian uncorrelated noise. At a first glance, this is surprising since additive noise is not supposed to affect a system’s oscillatory activity or stability.
The presentation shows first how additive noise can affect a nonlinear system’s stability by applying stochastic center manifold analysis in non-delayed low-dimensional systems and delayed systems. Then, an extension to stochastic randomly connected network models shows that the observed effect also emerges. Applying random matrix theory together with mean-field theory demonstrates how additive noise tunes the stability and oscillatory activity in such systems. In sum, the mathematical studies provide an explanation why the brain’s oscillatory activity changes with changing experimental conditions.
The seminar will be also broadcasted via BBB: https://bbb.unistra.fr/b/hum-51d-suf-mzq
Axel Hutt has studied physics at the University of Stuttgart supervised by Prof. Hermann Haken and worked on his PhD at the Max Planck Institute for Cognitive Neuroscience, for which he has received a Schloessmann Fellowship Award of the Max Planck Society in the year 2000. After positions at the Weierstrass Institute for Applied Analysis and Stochastics in Berlin, the Humboldt University Berlin and the University of Ottawa/Canada, he started working at INRIA Nancy Grand Est in 2007 and became Directeur de Recherche at INRIA in 2015. In 2010, Axel received an ERC Starting Grant. After a sabbatical stay at the German Weather Service for 4 years, from 2019 on he is working in the INRIA-team MIMESIS / iCube-team MLMS in Strasbourg on stochastic nonlinear dynamics of brain models in the context mental disorders. -
Nalini Anantharaman
Gaps in the spectrum of large graphs
15 février 2024 - 09:00Salle de conférences IRMA
We discuss questions and results pertaining to the presence of gaps in the spectrum of the adjacency matrix of certain families of finite graphs (in the limit where the size of the graph goes to infinity). We mostly focus on the construction of expanders (i.e. families of graphs with a uniform gap at the bottom of the spectrum), but also describe recent results or Bordenave-Collins or Sarnak-Kollar related to the presence of gaps elsewhere in the spectrum. We will also allude to similar questions for hyperbolic surfaces instead of graphs.
The seminar will be also broadcasted via BBB: https://bbb.unistra.fr/b/hum-51d-suf-mzq
Nalini Anantharaman was a Professor at Université Paris-Sud from 2009 to 2014, at Université de Strasbourg from 2014 to 2022, and has been a professor at Collège de France since October 2022 on the "Spectral Geometry" chair. She directed the LabEx IRMIA and the ITI IRMIA++ from 2018 to early 2023. -
Jérôme Pétri
Neutron star magnetospheres: a challenge for plasma physicists and astrophysicists
21 mars 2024 - 09:00Observatoire Astronomique de Strasbourg
Neutron stars are fascinating astrophysical objects immersed in strong gravitational and electromagnetic fields of the order B~10^5-10^10T. These stars manifest themselves mostly as pulsars, emitting a timely very stable and regular electromagnetic signal with periods around P~ 1ms - 10s. Even though discovered 55 years ago, neutron stars still remain mysterious compact objects. Neutron star electrodynamics remains challenging for performing computer simulations because of the extraordinary large span in space and time scales involved in such stars. A typical ratio between the cyclotron frequency omegaB and the stellar rotation frequency Omega is omegaB/Omega ~ 10^16-10^19. Numerical schemes are far from being able to handle such huge ratio. However a global qualitative picture emerges slowly thanks to recent advances in numerical simulations. In this talk, I summarize the most fundamental theoretical aspects of pulsar magnetospheres and highlight the latest developments in simulations of pulsar magnetospheres, from the basic force-free approximation or from the ideal magnetohydrodynamics regime to more detailed particle-in-cell approaches including radiation reaction.
The seminar will be also broadcasted via BBB: https://bbb.unistra.fr/b/hum-51d-suf-mzq
Jérôme Petri is Maître de Conférences at the Université de Strasbourg, Observatoire astronomique, member of the GALHECOS team. His research focuses on the theory and simulation of neutron star electrodynamics and high-energy radiation processes, linking recent multi-wavelength observations of these stars to state-of-the-art numerical modelling. -
Ivan Tarassov, Joseph Schacherer, Nacho Molina
Special biology session with ITI IMCBio+
18 avril 2024 - 09:00Salle de conférences IRMA
This meeting of the ITI IRMIA++ Interdisciplinary Seminar will focus on interactions with biology. Our guests will be three colleagues from ITI IMCBio+ (Integrative Molecular & Cellular Biology). Ivan Tarassov, director, will give a a brief a presentation of the themes covered by the ITI IMCBio+, followed by two short research talks by Joseph Schacherer and Nacho Molina.
The seminar will be also broadcasted via BBB: https://bbb.unistra.fr/b/hum-51d-suf-mzq
TITLES OF THE TALKS
"What is the ITI IMCBio+" (Ivan Tarassov)
"Species-wide quantitative transcriptomes and proteomes reveal distinct genetic control of gene expression variation in yeast" (Joseph Schacherer)
"Modeling Gene Regulation Using Biophysics-Informed Deep Learning on Single-Cell Multi-Omics Data" (Nacho Molina)
ABSTRACTS OF THE TWO SHORT RESEARCH TALKS
Abstract (Joseph Schacherer): Gene expression varies between individuals and corresponds to a key step linking genotypes to phenotypes. However, our knowledge regarding the species-wide genetic control of protein abundance, including its dependency on transcript levels, is very limited. Here, we have determined quantitative proteomes of a large population of 942 diverse natural Saccharomyces cerevisiae yeast isolates. We found that mRNA and protein abundances are weakly correlated at the population gene level. While the protein co-expression network recapitulates major biological functions, differential expression patterns reveal proteomic signatures related to specific populations. Comprehensive genetic association analyses highlight that genetic variants associated with variation in protein (pQTL) and transcript (eQTL) levels poorly overlap (3%). Our results demonstrate that transcriptome and proteome are governed by distinct genetic bases, likely explained by protein turnover. It also highlights the importance of integrating these different levels of gene expression to better understand the genotype-phenotype relationship.
Abstract (Nacho Molina): Biology is currently undergoing an incredible revolution, enabled by the emergence of single-cell genomics. This advancement allows for the characterization of all cell types in the human body, leading to a systematic understanding of collective cell function in health and disease. However, computational biology faces the challenge of extracting valuable information and generating reliable predictions from this wealth of data. While deep learning methods have proven to be powerful tools for clustering and denoising data, their black-box nature limits interpretability and prediction power.
To address this limitation, we present an innovative approach that combines an interpretable variational autoencoder with biophysical modeling to characterize gene regulation using single-cell sequencing data. Our model, trained on large-scale datasets, identifies key regulators responsible for the gene program of each cell type. Additionally, our approach infers gene-specific non-linear response functions that capture complex combinatorial regulations. Moreover, we applied our model to single-cell multiomics data of mouse embryonic stem cells, enabling a deeper quantitative understanding of gene expression dynamics throughout the cell cycle. Specifically, we estimated chromatin accessibility dynamics during cell cycle progression, cell-cycle dependent transcription and degradation rates for each gene, and identified key transcription factors driving the observed transcriptional dynamics.
In conclusion, our approach provides a powerful tool for analyzing and interpreting single-cell sequencing data, enabling deeper insights into the mechanisms of gene regulation.
ABOUT THE SPEAKERS
About Ivan Tarassov: he obtained his Master degree in Biochemistry & Molecular Biology in 1986 and PhD in 1990, both in Moscow State University. In 1992, he moved as a Postdoc (FEBS & EMBO fellowships) in Strasbourg, in IBMC. In 1996, he was recruited in the CNRS as CR1 and founded his own team in the GMGM unit. Between 2013 and 2023 he was the Director of the GMGM unit. In 2011, he founded the MitoCross labex and in 2022-2024 he is the coordinator of the ITI IMCBio+. His main scientific interests are mitochondrial functions and dysfunctions and mitochondrial diseases.
About Joseph Schacherer: he obtained his PhD in 2005 in molecular and cellular biology from the Louis-Pasteur University in Strasbourg, France. Following the completion of his PhD, he joined the laboratory of Leonid Kruglyak at the Lewis Sigler institute of Integrative genomics at Princeton University (New Jersey, USA), where he began work on genomic approaches to study population genomics and intraspecies phenotypic variation. In 2007, he was appointed as assistant professor of genetics and genomics at the laboratory of Genetics, Genomics and Microbiology (UMR7156, University of Strasbourg - CNRS). In 2013, he became team-leader and brought together an experienced team of researchers with expertise in population genomics, genetics, bioinformatics and data analysis crucial to set up high-throughput sequencing and phenotyping experiments and analyse the data generated. The group’s long-term goal is to use population and functional genomics to have a better insight into the rules that govern the genotype-phenotype relationship within species. Moreover, he was laureate of the National Institutes of Health (NIH) R01 grant program (2012, 2017 and 2023) and was awarded an ERC Consolidator Grant in 2018. He also led the 1002 yeast genomes project (http://1002genomes.u-strasbg.fr/). He was nominated member of the Institut Universitaire de France in 2016. And since September 2017, he is professor of genetics and genomics at the University of Strasbourg.
About Nacho Molina: he is a CNRS researcher and the group leader of the Stochastic Systems Biology Lab at the IGBMC in Strasbourg. With a background in theoretical physics, he pursued a Ph.D. in computational biology at the University of Basel where he received outstanding training in Bayesian statistics, machine learning, and gene regulation. After his PhD, he underwent postdoctoral training at EPFL where he developed a novel method combining stochastic processes with hidden Markov models to analyze transcriptional bursting in individual mammalian cells. Currently at IGBMC, the main research focus of his team lies at the interface between deep learning and biophysics, combining tools from both fields to develop mechanistic and interpretable large-scale models of gene regulation. This approach allows to analyze and integrate single-cell sequencing and imaging data and generate testable predictions based on causal mechanisms. Recently, the team has started a new line of research leveraging the strength in modeling gene expression dynamics, to understand the interplay between cell cycle regulation, pluripotency maintenance, and cell differentiation. -
Jean Schmittbuhl
Deep geothermal energy in Alsace : the contribution of ITI GeoT
16 mai 2024 - 09:00Amphi Rothé
Since 12 November 2019, the campus of the University of Strasbourg has been shaken several times by local earthquakes that have been linked to a deep geothermal energy project located in Vendenheim, 10km north of Strasbourg. The fear linked to these earthquakes is strongly questioning the value of using a local renewable resource underground as part of the energy transition. ITI GeoT has been heavily involved in characterising these seismic events, understanding their origin, questioning the technology and proposing new perspectives for better management of such projects. The seminar will illustrate the main observations and lessons from this recent technological history, focusing on the challenges posed by deep geothermal technologies, the development of subsurface observation techniques, including citizen science approaches, and the numerical modelling of subsurface physical responses through the development of digital twins.
The seminar will be also broadcasted via BBB: https://bbb.unistra.fr/b/hum-51d-suf-mzq
About the speaker: Jean Schmittbuhl is CNRS researcher in geophysics at EOST/ITES – Ecole et Observatoire des Sciences de la Terre/Institut Terre et Environnement de Strasbourg). After multidisciplinary training in Earth Sciences at Ecole Normale Supérieure (ENS) Saint-Cloud/Lyon, he obtained an ‘agrégation’ in Natural Sciences in 1989 and a master's degree in Physics of Liquids at the Pierre-et-Marie-Curie University in 1991. He defended his PhD thesis in Physics in 1994 at ENS Paris. He became a junior CNRS researcher in 1995 at the Geology laboratory of ENS Paris, after a post-doctoral visit at the Physics department of the University of Oslo. In 2004, he joined the ‘Institut de Physique du Globe de Strasbourg’ as a CNRS research director and became head of the experimental geophysics team. In 2012, he initiated and coordinated the LabEx G-eau-thermie Profonde, as well as a deep geothermal energy consortium involving Electricité de Strasbourg. Since 2021, he has been the director of the Interdisciplinary Thematic Institute Geosciences for the Energy Transition (ITI GeoT) at the University of Strasbourg. He was a member of the expert committee for the industrial accident of the Vendenheim deep geothermal project. His interdisciplinary research combines seismology, geomechanics, physics of heterogeneous media, petrophysics, and geochemistry. He has developed innovative laboratory experiments, multiscale numerical modelling and geological and geophysical field observations. His research activity is focusing on geometry of fractures and faults, their frictional properties, fluid flow in fractured and porous massifs, thermo-hydro-chemo-mechanical couplings, and wave propagation in fractured media. His research applications include earthquake initiation processes, mechanisms of induced seismicity, imaging of deep reservoirs from microseismicity and ambient seismic noise, and deep geothermal projects. -
Bérenger Bramas
Vectorization: what it is, why it matters, and why the compiler often fails
20 juin 2024 - 09:00Salle de conférences IRMA
In this presentation, I will explain what vectorization is and how it is used by modern CPUs to increase peak performance. I will then discuss what it entails to vectorize code, focusing on the implementation of an efficient sorting algorithm, and why compilers often fail to do this automatically. Finally, I will present Autovesk, our tool for automatic vectorization. I will describe our solution for transforming a graph of scalar instructions into a graph of vectorized instructions.
The seminar will also be broadcasted on BBB: https://bbb.unistra.fr/b/hum-51d-suf-mzq
Bérenger Bramas is a researcher (Chargé de Recherches) at Inria Nancy since October 2018. He is also a member of the ICube laboratory. He defended his PhD thesis in 2016 on the parallelization and optimization of the time-domain boundary element method for the wave equation. Subsequently, he worked as an HPC Expert at the Max Planck Supercomputing Center (MPCDF). His research interests focus on scientific computing, runtime systems, scheduling, software engineering for HPC, and automatic optimization/parallelization. -
Guillaume Steimer, Yassin Rany Khalil
The Vlasov-Poisson equation: numerical aspects and applications to the dynamics of the Milky Way
19 septembre 2024 - 09:00Salle de conférences IRMA
Guillaume Steimer: Hamiltonian model order reduction of the Vlasov-Poisson equation
Numerous mathematical models of real-life processes pose major difficulties when it comes to their numerical simulation. Indeed, their dimensions are usually large, and their numerical resolution is often complex, requiring a great deal of computing power. The Vlasov-Poisson equation is one of such steep cost models.
Model order reduction (MOR) aims to build so-called reduced models which are valid approximations of their original counterparts with a reduced associated state space dimension. Doing so results in a reduced model that is much faster to solve, but at the cost of a certain accuracy.
Moreover, when the original model is Hamiltonian, it is critical to preserve this property at the reduced level. In this talk, I will show how to build Hamiltonian reduced models of the Vlasov-Poisson equation discretized with a Particle In Cell (PIC) method using classical tools from model order reduction. Then, I will introduce the benefits of adding neural networks to the process.
Guillaume Steimer is a Ph.D. student in applied mathematics and a member of the MACARON team at IRMA Strasbourg. He studies Hamiltonian systems and the construction of associated reduced models, specifically using machine learning techniques.
Yassin Rany Khalil: Deciphering the dynamics of the Milky Way bar and spiral arms with Gaia
Our galaxy, the Milky Way, can be modeled at zeroth order as an axisymmetric system at equilibrium, obeying the fundamental equations of galactic dynamics (the Vlasov-Poisson system of equations). Devising a precise non-axisymmetric model is, on the other hand, far from trivial. Using the conservation of the distribution function in infinitesimal phase- space patches following the Hamiltonian flow allows one to compute the current distribution function by integrating orbits backward in time to an axisymmetric equilibrium state. In this talk, I will show how we explored the vast parameter space of the bar and spiral arms with this method to establish the current most realistic dynamical non-axisymmetric model for the Milky Way disk.
Yassin Rany Khalil, after completing his studies at Ecole Polytechnique in 2021, has started an ITI-funded IRMIA++ PhD thesis at ObAS in 2022. His thesis deals with the detailed modelling of the stellar disk of our Milky Way galaxy.
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Pierre-Olivier Goffard
A gentle introduction to blockchain technology with applications
17 octobre 2024 - 09:00Observatoire Astronomique de Strasbourg
Since its inception in 2008 as the underlying technology behind Bitcoin, blockchain has evolved far beyond its cryptocurrency origins. Over the past decade, various blockchain systems have emerged, demonstrating diverse applications across industries. This talk provides a quick dive into blockchain analysis. I will cover the essentials of blockchain technology with a focus on consensus protocols like proof-of-work and proof-of-stake before discussing some applications in Finance and Insurance.
The seminar will take place in the Amphithéâtre du Bâtiment de la Grande Coupole, opposite the entrance at 11 rue de l'Université.
Pierre-Olivier Goffard is an Associate Professor at the University of Strasbourg, France. He conducts research at the intersection of applied probability, statistics, and their applications in finance and insurance. His areas of expertise encompass blockchain technology and Bayesian statistics. Pierre-Olivier actively participates in the actuarial science program at the University of Strasbourg, where he teaches courses on stochastic calculus and survival analysis. -
Étienne Le Quentrec
Locally Turn-Bounded Curves and their Applications to Digital Geometry
21 novembre 2024 - 09:00Salle de conférences IRMA
When an object is photographed, the resulting image is pixelated. The position of a point in such an image is described by integer coordinates, unlike that of a point on the original object, which is described by real coordinates. This transition from the usual Euclidean geometry describing the original object to the discrete geometry describing the obtained image, called digitization, causes significant information loss. If the resolution of the discrete image is too low compared to the level of detail of the original object, topological information and geometric quantities can be lost. It then becomes necessary to impose certain assumptions on this real object to allow the reconstruction of this information.
By modeling the digitization process, it is possible to ensure the reconstruction of the topology and geometric quantities of objects that meet certain assumptions. However, currently in digital geometry, the assumptions on real objects that guarantee the reconstruction of all this information are quite restrictive and do not allow the simultaneous inclusion of shapes whose boundary is a smooth curve and those whose boundary is a polygon.
To simultaneously address these two families of shapes, we propose a new assumption based on the concept of total curvature introduced by Milnor in 1950. This consists of locally limiting this total curvature on the boundary of the real object. This assumption, which includes shapes with smooth or polygonal boundaries, guarantees the reconstruction of topology and allows for bounding the errors of discrete estimators of geometric quantities.
About the speaker: Étienne Le Quentrec is assistant professor (maître de conférences) at ICube, member of IMAGeS team since September 2022. He defended his PhD thesis in 2021 on digital Geometry at ICube. He was also student at UFR in mathematics where he obtained his "agrégation" in 2016. His main research interests are digital topology and discrete estimation. -
Pierre-Alain Duc
Detecting low surface brightness structures on astronomical optical images: science impact and challenges
19 décembre 2024 - 09:00iCube Campus d’Illkirch
The exploration of the Low Surface Brightness (LSB) Universe currently motivates several surveys across the world, carried out with a number of instruments, and provides observational constrains for numerical simulations. It impacts multiple scientific fields, including the structure of the interstellar matter, galaxy archeology, galaxy evolution and cosmology, and has generated passionate debates, for instance regarding the very existence, nature and properties of the so called Ultra-Diffuse-Galaxies. Meanwhile the community prepares for the exploitation of next generation surveys, including Euclid and LSST. Detecting, identifying and characterising the faint, diffuse and extended optical light of the LSB structures on very wide areas on the sky raises a number of technical difficulties and challenges, that will be presented during the seminar. The first attempts to use artificial intelligence, and in particular deep learning techniques, to deal with these issues will be addressed. About the speaker: Pierre-Alain Duc is CNRS research director at the Observatoire Astronomique de Strasbourg and director of the observatory since 2017. He defended his PhD thesis in 1994 at CEA Saclay on the formation of dwarf galaxies in interacting systems before moving to ESO Garching and the university of Cambridge for postdoctoral studies. He joined the CNRS in 1999 at CEA Saclay before moving to Strasbourg to take charge of the observatory. Among his numerous research topics, he is particularly interested in the study of environmental effects on the formation and evolution of galaxies. Pierre-Alain is the PI of the MATLAS large program at CFHT and member of the Euclid and Rubin/LSST consortiums.