Current Opportunities

The following is a list of research projects funded under the President’s Fellowship Scholarship. To apply, fill in the application form. The closing date for application is May 20th.

Automated measurement of activity levels for children with autism

health

In conjunction with the department of Health & Science, we aim to design and prototype a system to monitor and record the activity levels of children with autism. The aim is to link in with existing research, led by Dr. Kinsella, which is working with a cohort of autistic children.

More details on this project are here, and if you have any questions about this project, you can contact the principal supervisor, Oisin.Cawley@itcarlow.ie.

Automated Drone Navigation via real-time image processing through Convolutional Neural Networks

AI machine learning

Automated, real-time video analysis is both a difficult and time consuming process. Our aim with this project is to investigate the feasibility of performing the necessary image processing of footage taken from a drone camera, and to convert the interpretation of that input into navigation commands for the drone. In other words, automatically steer the drone according to the footage it is recording.

More details on this project are here, and if you have any questions about this project, you can contact the principal supervisor, Oisin.Cawley@itcarlow.ie.

Interpreting brain wave activity through the use of a Deep Neural Network

AI machine learning

Electroencephalography (EEG) is widely used in brain–computer interfaces (BCIs)—communication channels that bypass the natural output pathways of the brain—to allow brain activity to be directly translated into directives that affect the user’s environment. It is a highly promising medium with potentially extraordinary applications such as the direct control of prosthetics and exoskeletons. One of the most recent approaches to interpreting the EEGs is through the use of Artificial Neural Networks and Machine Learning. However, there are a number of challenges with non-invasive EEG interpretation, such as inter-subject variability, which will need to be addressed.

The objective is to review the field and develop a BCI interface which would initially allow the user to play a computer game. If successful this would demonstrate a novel interface for people with physical disabilities for game play, and indeed opens a path for further research in brain interfaces for other applications both digital and physical.

More details on this project are here, and if you have any questions about this project, you can contact the principal supervisor, Oisin.Cawley@itcarlow.ie.

Big Data Trustworthiness

data science machine learning

This researcher will investigate the use of those and other wide range of characteristics to help establish the trustworthiness of large volumes of data collected from a variety of sources and their lifecycle. The multifaceted evaluation of data trustworthiness will help organisations improve the utilization of human expert preferences and making proper interpretations of the data.

In recent years, there has been a significant amount of research in the area of trust and reputation in computer science areas such as security, Web services, e-commerce and game theory. The ability to analyse past actions and to monitor current environmental metadata allows us make predictions about the likely behaviour in the future. These predictions are based on trust models and algorithms that seek to replicate social concepts of trustworthiness and that are designed to compute trust ratings and share trust-related information with other actors. The researcher will analyse existing trust models from different application areas and their relevance to the big data lifecycle with the aim of building modified or brand-new models.

More details on this project are here, and if you have any questions about this project, you can contact the principal supervisor, Hisain.Elshaafi@itcarlow.ie.

Automated Regression Testing of C Programs

software engineering

Your mission is to develop a novel automated software tool that will help with the maintenance of C code by detecting differences between the new version of a program and the one it replaces leading to an MSc by research over 2 years with possible transfer to PhD programme if suitable progress.
Why focusing on maintenance? Because it is the biggest problem in the software industry: most coders are employed to modify existing code. Why focusing on C? Because it is extremely popular, relevant, simple language: there are billions of lines of code of C that needs maintaining.
Why regression testing? Regression testing is trying to ensure that a new version of a program behaves the same as the old one, the new code may add functionalities but should not break anything that was working before.

More details on this project are here, and if you have any questions about this project, you can contact the principal supervisor, Chris.Meudec@itcarlow.ie.

A Virtual Reality/Augmented Reality (VR/AR) game environment to aid in motivation and development of a user’s physical movement and skill acquisition

VR AR health

This project will examine if fun and engaging VR/AR interactions in recreational virtual game environments will increase the intrinsic motivation with a group of users to carry out physical movement and learn a physical skill. It will focus on providing skill-based games with hopefully physical movement being a by-product of the interaction techniques.
Building on research in VR/AR platforms with 3D 6 Degrees of Freedom accurate low latency controllers where users’ physical movement can be accurately tracked. The user’s movements and other biometric data are collated and assessed in the context of the user’s perception of exertion and motivation to continue to carry out the game interactions.
We hope to gain an understanding of the links between differing VR/AR experiences and motivation and enjoyment to carry out physical movement and real word skill acquisition.

More details on this project are here, and if you have any questions about this project, you can contact the principal supervisor, Noel.OHara@itcarlow.ie.

Trend Prediction in the Cryptocurrency Market

machine learning

The goal of this project is to learn models and design algorithmic trading strategies based on cryptocurrency trading and transaction data, as well as sentiment analysis, to predict market changes and make profit over time.

Algorithmic trading is a prevalent practice in major cryptocurrency exchanges of the world. Algorithmic trading strategies are designed to make trading decisions by identifying true signals among massive amounts of data that capture the underlying cryptocurrency market dynamics. Machine learning has therefore been central to the process of algorithmic trading because it provides powerful tools to extract patterns from the seemingly chaotic cryptocurrency market trends, which are greatly affected by the supply and market demand, mining cost, competing cryptocurrencies, monetary inflation rates, user sentiment, and legal regulations, as well as global macroeconomic environment.

More details on this project are here, and if you have any questions about this project, you can contact the principal supervisor, Lei.Shi@itcarlow.ie.