Upcoming talks

Ioana Manolescu

Teasing journalistic findings out of heterogeneous sources: a data/AI journey
June 2nd, 2022

A series of monthly lectures, The Jacques Morgenstern Colloquium exhibits the most active, most promising research in the field of Information and Communication Science and Technology (ICST).

The lectures cover current research, new applications, as well as industrial and social challenges. The invited speakers are established senior experts of international stature in computer science, mathematics, and other fields where ICST plays a crucial role.

The colloquium is addressed to all researchers, engineers and students who want to better understand the future of IST. It is intended to create awareness and interest and to promote interdisciplinary discussions and collaborations.

The colloquium is named after Jacques Morgenstern, a professor of mathematics at the University of Nice Sophia-Antipolis and one of the pioneers in algebraic complexity and computer algebra. He headed a joint team of CNRS, Inria and the University of Nice until he died tragically in 1994.

The colloquium is part of the training at Ecole Doctorale STIC. Free entrance.

Our recent speakers

Sabine Süsstrunk – Opponency revisited
 
Sabine Süsstrunk – Opponency revisited
March 10th, 2022 – 11:00 am According to the efficient coding hypothesis, the goal of the visual system should be to encode the information presented to the retina with as little redundancy as possible. From a signal processing point of view, the first step in  removing redundancy is de-correlation, which removes the second order dependencies…
Andreas Flache – Opinion polarization and network segregation. Modelling a complex  Relationship
 
Andreas Flache – Opinion polarization and network segregation. Modelling a complex Relationship
June 24th, 2021 Recently, many societies seem to shift towards more polarization and volatility in opinions, for example in attitudes about immigration, climate policy, or the best policy response to Covid-19. A key obstacle for a scientific understanding of this development is that opinion dynamics in society involve a complex micro-macro interaction between processes of…
Damien Woods – 21 Molecular Algorithms Using Reprogrammable DNA Self-Assembly
 
Damien Woods – 21 Molecular Algorithms Using Reprogrammable DNA Self-Assembly
May 20th, 2021 The history of computing tells us that computers can be made of almost anything: silicon, gears and levers, neurons, flowing water, interacting particles or even light. Although lithographically patterned silicon surfaces have been by far the most successful of these, they give us a limited view of what computation is capable of.…
Kathryn Hess – Topological insights in neuroscience
 
Kathryn Hess – Topological insights in neuroscience
April 20th, 2021 Over the past decade, and particularly over the past five years, research at the interface of topology and neuroscience has grown remarkably fast. Topology has, for example, been successfully applied to objective classification of neuron morphologies and to automatic detection of network dynamics. In this talk I will focus on the algebraic…
Mazyar Mirrahimi – The quest for long-lived quantum bit
 
Mazyar Mirrahimi – The quest for long-lived quantum bit
January 30th, 2020 The field of quantum information processing (quantum computation and quantum communication) has grown considerably in recent decades. Numerous proof-of-principle experiments on small-scale quantum systems (few physical degrees of freedom) have been carried out in various physical frameworks such as NMR (nuclear magnetic resonance), trapped ions, linear optics and superconducting circuits. In spite…
Bertrand Meyer –  How to build quality software: the Eiffel experience
 
Bertrand Meyer – How to build quality software: the Eiffel experience
Wednesday, December 18th, 2019 With society’s growing reliance on IT systems, the ability to write high-quality software is ever more critical. While a posteriori verification techniques have their role, there is no substitute for methods and tools that provide built-in quality (“correctness by construction”) and scale up to very large systems. For several decades my…
Alexei A. Efros – Self-Supervised Visual Learning and Synthesis
 
Alexei A. Efros – Self-Supervised Visual Learning and Synthesis
Thursday, November 28th, 2019 Computer vision has made impressive gains through the use of deep learning models, trained with large-scale labeled data. However, labels require expertise and curation and are expensive to collect. Can one discover useful visual representations without the use of explicitly curated labels? In this talk, I will present several case studies…