Seminar Details
2024-10-01 (14h) : Newcomers seminars (PhDs)
At Euler building (room a.002)
Organized by Mathematical Engineering
Section 1: Tools for measuring and quantifying neurodegenerative diseases. Quantitative approach applied to essential tremor and Parkinson disease
Speaker :
François Lessage (PhD UCLouvain/INMA)
Abstract :
To develop quantitative measures and assess pathologies affecting movement control, we will study populations with essential tremor (ET) and Parkinson disease (PD) in tasks at the forefront of current knowledge on these pathologies. For essential tremor, we will study the mechanism of sensory attenuation in relation to recent laboratory results suggesting delay compensation errors. For Parkinson disease, we will study Long-Range Autocorrelation (LRA) and adaptation to better understand how this pathology affects gait control. In both cases, we hope to expand knowledge and identify complementary measures that could be useful to quantify these deficits.
Section 2: A computational framework to study the integration of mechanical and thermal inputs during tactile interactions
Speaker :
Louis Lovat (PhD UCLouvain/INMA)
Abstract :
A computational framework to study the integration of mechanical and thermal inputs during tactile interactions"
Abstract : "The study of somatosensation has made significant strides, with numerous models developed to simulate either mechanical or thermal responses of the skin. These models have provided valuable insights into the response of the skin under various conditions, such as stress, deformation, and temperature changes. However, most existing models tend to focus on either mechanical or thermal stimuli in isolation, bypassing proven interactions between the different somatosensory submodalities and often overlooking the fine-scale interactions that occur at the level of fingerprint ridges and small topographic features of objects. Here, we aim to develop a comprehensive computational framework capable of simulating the complex interactions between mechanical and thermal stimuli at the fingertip. The core of this work being to create a detailed model of the fingertip accurately predicting the mechanical and thermal responses of the skin at both macro and micro scales. This model will be integrated with artificial neurons representing somatosensory afferents which will allow precise simulation of the sensory system’s responses to various combined stimuli. Understanding how the human somatosensory system captures these intricate dynamics will provide a tool to design, predict and interpret future psychophysical and neurophisiological experiment, and contribute to practical applications in the development of haptic interfaces, neuroprosthetics and virtual reality technologies
Section 3: Tight analysis and design of online optimization algorithms
Speaker :
Erwan Meunier (PhD UCLouvain/INMA)
Abstract :
Online optimization algorithms aim at minimizing on average over time a function that can change every time it is sampled. Crucially, the value of the function often has to be “paid” each time it is sampled, e.g. in terms of energy, money, prediction error, etc. Preliminary results in my master‘s thesis show that (i) the currently available performance bounds are conservative, which can lead to a suboptimal use and tuning of online methods and higher costs, and (ii) tight performance bounds can be understood by analyzing highly structured low-dimensional functions. In my thesis, I will be to analyze and exploit this structure to develop general worst-case performance bounds, and to use these bounds and the insights gained to design novel more efficient online optimization algorithms.
Specifically, I will begin by analyzing online settings with unstructured (arbitrary) changes of functions. I will then move to several contexts where changes are structured, with applications in control and stochastic optimization. Finally, I will generalize my results to distributed online optimization, where a group of interconnected computers each own a part of the functions and collaborate towards the global minimization. Based on recent results in standards optimization, potential gains in the decentralized settings are suspected to be tremendous. A key enabler of my project and my preliminary works, is the recently developed performance estimation problem (PEP) methodology, which allows computing the exact worst-case behavior of a wide class of deterministic optimization algorithms, by formulating this analysis itself as a tractable optimization problem. I will exploit it both as a guide in my exploration, and as a method for theoretical developments
.