Question Answering (QA) system automatically answer questions raised by users in natural languages, and it is a crucial component of a human-machine conversation system. A typical QA system collects human written question-answer groups and structures them in a database system. However, in order to answer questions that are semantically similar to the questions stored in […]

The aim is to understand how fibroblasts, the most common connective tissue in animals, and cancer cells interact with each other through image analysis. These co-culture imaging screens, containing fibroblasts and cancer cells, will help identify novel signaling mechanism involved in cancer. The objective is to apply deep learning techniques to these image-based assays to […]

In this project, a VR-based testing station for impairment screening will be implemented. The station includes a Virtual Reality (VR) goggle (to be updated to Augmented Reality, AR, later), biophysiological measurement sensors, and an integration algorithm to integrate the result of measurement with scene construction of the VR system to implement dynamic scene rendering. The […]

This research proposal is about investigating and evaluating different technologies in order to ensure the security of a wireless device such as a tablet that is used to play games in retail and/or casino type of environments. In this context security not only includes legitimate users to use the devices and play the games but […]

Deep convolutional neural networks (CNNs) have been tremendously successful in many high-level computer vision tasks, e.g., image recognition and object detection. Although recent works have shown that it is also possible to learn an end-to-end CNN model for low-level vision tasks, e.g., image dehazing, the resulting performance is still not completely satisfactory. For high-level vision […]

Magnetic Resonance Imaging (MRI) is the non-invasive method of choice for diagnosing and studying neurodegenerative diseases such as multiple sclerosis (MS). However, conventional MRI that is currently used in clinics cannot provide a reliable measure of neuronal health. More specifically, it cannot distinguish healthy from diseased myelin, a key component of neuronal tissue that is […]

Technological improvements, competition in the survey services industry and the increased use of UAV’s (drone) has driven down the cost of LiDAR acquisition. As a result, LiDAR is rapidly gaining popularity in application in road planning and design. LiDAR data sets typically contain tens of millions of points. Efficiently processing this data efficiently presents challenges […]

Robots and other autonomous machines currently have limited sound awareness and speech recognition capabilities, which limits their ability to interact with humans. Applying insights from cognitive neuroscience provides novel ways to improve these interactions. The primary objective of this proposal is to implement an auditory AI for robotics that finds human talkers in the environment […]

In 2010, approximately 35.6 million people suffered from dementia around the world and the number is expected to double every 20 years. These alarming predictions call for a better understanding of the mechanisms underpinning cognitive decline in aging. One of the key cardiovascular risk factors for cognitive decline is arterial stiffening. My project involves the […]

Le projet consistera a développer des modèles prédictifs utilisant les données de tests médicaux de patients. Quatre algorithmes en utilisant les méthodes de régression logistique et de forêt aléatoire seront utilisés prédire le diabète, l’hémoglobinopathies, le beta thalassémie, le niveau élevé de LDL-C. Les algorithmes permettront de classer divers résultats et d’en déduire un recommandation […]

Natural language processing (NLP) is a branch of artificial intelligence that focuses on teaching computers how to analyze and understand human languages. The objective of this project is to develop advanced machine learning techniques to extract sentiment from text. We want to improve the current industry standards for sentiment analysis by leveraging the latest results […]

The project aims to facilitate the research and development of new drugs by exploring Machine Learning methodology useful for both the generation of new molecules and the prediction of molecule properties. Doing so will involve training deep learning models on a large number of small, heterogeneous datasets, with the objective of transferring learned representations quickly […]