Automated Impact Analyses to Support Code Review Practices

Large software systems are updated incrementally to add new features or fix bugs. It is a common practice in the software industry to have each incremental change reviewed by a peer to detect software quality issues and transfer knowledge among team members. While peer review boasts technical and non-technical benefits, it is still primarily based […]

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Anomaly Detection in Event Data

The proposed research project targets anomaly detection of event data. The project has a duration of six months and aims to achieve two objectives: (1) to evaluate the effectiveness of a novel approach for real-world data, and (2) compare it to alternative methods. The intern will use existing research resources, and will apply them to […]

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Applications of deep learning to large-scale data analysis in mass spectrometry-based proteomics

As a result of recent advances in high-throughput technologies, rapidly increasing amounts of mass spectrometry (MS) data pose new opportunities as well as challenges to existing analysis methods. Novel computational approaches are needed to take advantage of latest breakthroughs in high-performance computing for the large-scale analysis of big data from MS-based proteomics. In this project, […]

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A ubiquitous positioning solution for head-mounted sensors – Year two

Recent advancement in computer vision and sensing technology has shown great potential for autonomous vehicles. This work aims to studies using an Augmented Reality heads-up display to improve the reliability of Advanced Driver Assistance Systems (ADAS). The algorithms developed will help drivers detect obstacles e.g. pedestrians crossings, improve current lane departure warnings to allow a […]

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Smart Learning and Course Management System

This is a research and development (R&D) project. The primary objective is to develop a Smart Learning and Course Management System with a pilot demonstration of an entrepreneurship development course. The target audience for the course is students interested in learning the fundamentals of running a startup company. The secondary objective is to document and […]

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Towards a Universal Cloud-based IoT Platform for Smart Applications

With the Internet of Things technology, a multitude of small devices and sensors are connected to the cloud and social networks using the Internet. These devices generate a huge volume of data, which can be used to discover trends and profiles. This enables building diverse useful applications for our modern society. This project is a […]

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Using Machine Learning to Optimize a Workflow Management System.

Workflow management frameworks support the creation of task dependencies and make efficient use of resources while running those workloads. Typically, these tasks can be long running processes like machine learning algorithms or access data from databases. Workflow management consists of mapping tasks to suitable resources and the management of workflow execution in a cloud environment. […]

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Data Science Search Engine Optimization

Search is an important way people get the information they want. Whether we want to find more content about a specific topic, or get general information on a subject, search engines lie at the core of this process. At Flipp, search plays a crucial role in the overall user experience and drives relevant content to […]

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Exploring Inventory optimization Through Small Business

Upon completion of the project the interns work will allow the partner organization to better understand how inventory management is handled in small businesses. The project will also help understand what inventory levels should be for small businesses based on predictive analytics. With this knowledge the partner organization can better understand how it can help […]

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Linguistic Data Science for the Development of a Business Corpus

This project is dedicated to the development of a new business corpus as a novel data for the company’s business intelligence. It focuses on linguistic pre-processing for the business domain using two types of collected corpora: text and speech. An automatic annotation of the pre-processed business corpus will be completed using labels related to sentiment […]

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