LAFORGE: Log Analytics For Operational Intelligence

The goal of this project is to explore the use of log analytics and machine/deep learning techniques to improve Ubisoft operational intelligence. Logs contain a wealth of information, but often hindered by the lack of best practices, tools, and processes. Despite the importance of logging, the area has not evolved much over the years. At […]

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Research on Multi-Platform Supported Realtime Locator for Transport/ Fleet Management Applications

The project is to conduct research on multi-platform supported Locator device by investigating an easy-to-port and extendible design to migrate a Locator firmware offered by WebTech wireless Company on alternative operating systems with more advanced features. The Locator firmware is currently run on the FreeRTOS operating system, which is known to be small and simple, […]

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Kali: Optimizing Resource Utilization in Distributed Clusters

Decreasing operational costs is a key criterion for organizations that manage compute clusters, such as Amazon, Microsoft, Google, Alibaba, etc. One way to decrease costs it to improve resource utilization in the cluster [13, 14]. Yet, high resource utilization can negatively affect workload performance and thus user satisfaction. Performance degradation happens when workloads running on […]

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Exploring Deep Learning Architectures for Automatic Casting from Movies

Automatic casting applications aim is to accurately recognise facial regions that correspond to a same actor appearing in a movie to produce described video. This project will focus on the tasks of re-identify the face of each principal actors when they appear in different scenes of a movie. This is a challenging task because although […]

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Named Entities Recognition for Customer Service Automated System

This project aims at creating a robust, efficient and reliable tool for Named Entities Recognition (NER) from vast amounts of textual data related to the customer service. Named entities recognition, a subtask of information extraction, seeks to locate and classify elements in text into pre-defined categories such as the names of persons, organizations, locations, expressions […]

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Developing Optimally Discriminative Subnetwork Markers for Predicting Response to Chemotherapy

Molecular profiles of tumour samples have been widely and successfully used for classification problems. Many algorithms have been proposed to predict classes of tumor samples based on expression profiles. However, prediction of response to cancer treatment has proved to be more challenging and novel approaches with improved generalizability are still highly needed. Recent studies have […]

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Combining data science and wearable technology for early health risk detection

It has been well established that if human diseases can be diagnosed early, the prognosis and future quality of life is much improved. With advancements in computing technology in both the hardware (e.g. smaller, lighter, better batteries) and software (i.e. improved artificial intelligence), health systems are entering a renaissance when wearable technology and data science […]

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Towards Clinical Use of Whole Genome Sequencing based Tests in a Clinical Setting

Using genomics in clinical care has the potential to treat patients more efficiently. There have been a number of recent discoveries of genomic assays that can guide treatment. However, most genomic data is generated in a research setting and useful health data only in a clinical setting. Translating potential genomic research into a clinical setting […]

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Designing Soft+Stiff Haptic Interactions with Opensource Authoring Toolkits

Our sense of touch is vital to most daily activities we engage in, but is underused by most existing computing devices. Though haptics is an active research field, the main outcomes of three decades of research are limited to cost-effective vibrotactile feedback (as in mobile phones) or expensive force-feedback devices (mainly for surgical operation simulation). […]

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