Electrical stimulation of nerves can be used to restore movements to individuals who are paralyzed following spinal cord injury. Our project is divided into two main parts. The first part aims to combine measurements of muscle and nerve activity evoked by electrical stimulation in order to improve our understanding of the mechanisms involved in nerve […]

This project will focus on the research areas of smart device monitoring and the analysis of complex medical data in public health. Through the use of artificial intelligence, researchers will develop solutions that exploit large-scale sensor data, address significant challenges caused by global threats by, for example, setting early heat alerts for extreme heat waves. […]

The ability to perceive the motion of approaching person and to make appropriate adjustments to avoid collisions is an essential component of safe locomotion through the environment. The proposed project will investigate young and older adults’ collision avoidance behaviours with an approaching young adult in order to understand the visual information used to accomplish the […]

Understanding pedestrian dynamics is crucial to the design of pedestrian facilities. Although pedestrian flows are part of everyday life, many basic characteristics of pedestrian dynamics cannot yet be described in detail. The aim of the PhD project is to study the upper body rotation of pedestrians when crossing a narrow passage (bottleneck). Since the movement […]

A consequence of aging is the increased risk of neurodegenerative disease. In the pathogenesis of neurodegenerative diseases is the production of misfolded proteins which can clump together and interfere with normal cellular function. Mitochondria are highly important as they produce energy necessary for cell survival as well as regulate the controlled cell death process of […]

High throughput multi-omic cancer studies have described the inter-tumor heterogeneity and led to well defined molecular classifications. Nevertheless, these classifications only reflect the most abundant tumor subtype in the examined sample, thus neglecting intra-tumor heterogeneity, a major source of therapeutic resistance. As advanced microdissection techniques to isolate a cell population of interest from heterogeneous clinical […]

A major challenge facing farmers is obtaining the nitrogen needed to support plant growth. Inoculation of legume crops with bacteria known as rhizobia, which supply plants with the required nitrogen, is a green alternative to environmentally hazardous nitrogen-fertilizers. The development of highly-efficient rhizobium inoculants is a pre-requisite for sustainable intensification of agriculture. In five clades […]

Music therapy is an evidence-based effective intervention to promote psychological, social and emotional health, and it is specifically favored by older adults. However, little is known on the efficacy of the AI-assisted empathic music therapy in which the music is continuously adapted to individuals’ mood. To fill this gap, the proposed project will assess the […]

Bacterial resistance to aminoglycoside antibiotics is a major public health problem. The WHO (World Health organization) has highlighted the urgent need to find new treatments to fight multidrug resistance MDR bacteria, as actual drugs are less effective or inactive. This research project aims to develop new chemical compounds to restore bacterial sensitivity to antibiotics currently […]

Sensitive gas sensors are urgently needed for the detection of biomarkers for disease prevention and greenhouse gas emissions for environmental monitoring. Dynamic cantilever gas sensors work by oscillating the cantilever to its natural resonance frequency by typical MEMS (micro electromechanical system)-based actuation methods. The adsorption of a target gas on the cantilever increases its mass […]

Serial electron diffraction (serial-ED) crystallography is an emerging structural biology method whereby data are collected from protein nanocrystals using a sub-micron-sized electron beam. The method is set to lead the future of nanocrystallography, given its cost-effectiveness and the small amount of sample required. Combining the expertise of the Colletier and Miller teams, the project will […]

Computer-based multimodal affect recognition methods fuse multiple informational channels, typically video, audio, and text, to resolve the emotional state of a monitored individual. The proposed research aims to develop multimodal deep learning models to recognize anomalous emotional responses, which correspond to a deviation from the expected affective reaction for a particular context. Since multimodal affect […]