SwEng Industry Projects is a unique offering from the School of Computer Science & Statistics (SCSS) at Trinity College Dublin connecting future engineers with companies to work together on real-life industry projects proposed and mentored by our industry partners.

A student gathering at the Software Engineering (SwEng) Industry Projects

Proposed by participating companies, the Software Engineering (SwEng) projects are a response to real-life industry needs and all have a significant software development aspect to them and are focused on building an end-to-end product employing software development and design principles common in industry such as DevSecOps, GitOps and automated tested.

The projects are undertaken by Year 2 and Year 3 undergraduates students at SCSS who gain hands-on experience working in collaboration with industry experts from the School’s industry partners panel who mentor the students during the project’s intensive 12-week lifespan. Project teams are a mix of second-year and third-year students from different degree courses creating a unique blend of knowledge and experience; mimicking real-life industry teams.

For the partner companies, who include Microsoft, IBM, Dell and Arista, the benefits are incalculable as it gives them unprecedented access to some of the country’s best young talent before they reach the recruitment market. It allows them to identify and mentor potential future employees and introduce them to the company’s culture and practices before they graduate into the workplace.

Because of the deep bonds created during the projects, many of the students who work on projects with industry partners go on to apply for internships and full-time employment at the company.

During the lifespan of the project, the companies act as the client and mentor the team, with structured and consistent support from the SCSS team. Industry mentors – at least two per project –meet their teams weekly for the duration of the project, guiding and advising the teams on technical, project management and team management aspects of the project. The best projects are showcased at the SwEng Industry Projects Awards; an annual prize-giving event.

SwEng Industry Projects are a key component of the overall SwEng Industry Programme and the connections created between student and company can lead directly to internships which are put in place in Year 4 of the programme. The SwEng Industry programme was created by SCSS as a strategic solution designed to bridge the gap between academic and industry practice. Integrated into all Computer Science courses at SCSS, the programme’s aim is to produce industry-ready engineers who can seamlessly transition from university to the workplace and to forge links with industry partners who very often become their future employers.

The result of this unique programme — only available at the School of Computer Science & Statistics — is a win-win for both students and industry. Students get real and practical exposure to industry practice and are ‘industry ready’ by the time they graduate while companies get to build a recruitment pipeline of graduates who are already embedded into their corporate culture and practices.

*The development of SwEng has been partly funded by the HEA Human Capital Initiative, Pillar 3.

SwEng Industry Project Examples 2022

Project name: Lecture Dictation & Natural Language Querying of Knowledge Corpus

Project description: There is currently a unique opportunity to digitize all the ZOOM/TEAMS recordings from last Academic Year to avoid losing all the work done and turn audio recordings into written, classified and usable persistent knowledge. Students need to do this by: 1. Transcription - Can be done using IBM Watson STT. This should be customized using domains-specific language models which can be done by the students. 2. Ingestion into an NLP-based searchable repository - Using IBM Watson Discovery with trainable queries - the whole set of transcription can be tagged, classified and searchable 3. Creation of a User Interface that would allow searching of answer passages and links to videos covering particular material - Using the Discovery API a query front-end could be built that would allow - entry of natural language queries, filtering by entities and keywords, links to source video clips.

Lecture Dictation & Natural Language Querying of Knowledge Corpus

Project name: NLP based Sentiment analysis

Project description: Sentiment analysis - We input a paragraph or sentence(s) and create a sentiment score between -1(most negative) and 1(most positive). Also, each sentence is classified as positive/negative besides the overall sentiment score. Text similarity & text summariser- We take two text bodies of any size as input and find a similarity score. We need to ensure that some words are synonyms and so this aspect needs to be taken into consideration. Text summariser will help in reducing large text body into a smaller one so that text comparison scores are more optimum. Note: In all the models, based on the use case chosen a dashboard needs to be created.

NLP based Sentiment analysis

Project name: Multiple users Kanban board

Project description: Develop a Kanban board that supports multiple users in a language of your choice, then deploy it with modern CI/CD pipeline with container technology based on Red Hat.

Multiple users Kanban board

Project name: A TODO App

Project description: Develop an A TODO app, that stores TODOs in a persistent database in a language of your choice, then deploy it with modern CI/CD pipeline with container technology based on Red Hat.


Project name: HoloLens Mixed Reality Video Game

Project description: The HoloLens is a mixed-reality device which enables untethered and immersive mixed-reality experiences. A crucial benefit of mixed-reality experiences is the ability to provide multi-user collaborative experiences, which is becoming ever-more important during the current requirements regarding social distancing. We will plan to build smartphone-based AR client for this project, if restrictions allow us to access HoloLens headsets, we will use those instead. Objective The challenge for this project is to develop a multiplayer game that utilizes augmented reality technology that allows users to share the experience of playing a game together, regardless of whether they stand in the same room or across the globe. There are multiple challenges involved in this project, from designing an interactive and easy to use game client using Unity to designing a service which can handle large volumes of game sessions, process individual user commands to modify game state, and seamlessly sync the game state to multiple users.

HoloLens Mixed Reality Video Game

Project name: Pneumothorax Detection Using Computer Vision

Project description: The objective of this project is to use open-source data to build a machine learning model that can detect pneumothorax from a presented x-ray.

Pneumothorax Detection Using Computer Vision

Project name: Mobile Music app: Music discovery experience

Project description: Students were given the task of creating a music discovery platform using Dart, Flutter and Firebase.

Mobile Music app: Music discovery experience

Project name: A Blockchain publishing system

Project description: Legislative documents undergo many changes between their initial creation and their final passage into law. Bills and resolutions can be amended, sponsored, heard in committee, replaced, reverted, and more. This project involves creating a web-based tool for visualizing how individual pieces of legislation evolve over time, along with some larger visualizations about how the broader legislative landscape is changing. The project is a mix of data processing, analysis, and web-based visualization.

A Blockchain publishing system

Project name: Web-based Dashboard App for monitoring & alerting of automation jobs anomalies

Project description: Project Description: Develop a web-based application using the framework/language of choice with the following characteristics: 1. Historical metrics of the execution times of each job - a type of job can be uniquely identified by "topic" and "group" (team responsible for the job) 2. Graphical representations of those metrics with different ways to slice and dice the data - by day, year, month, groups, topics, etc. 3. Alert sinks supported should be : 1. REST - With out of the box integration for Slack, OpsGenie and ServiceNow's incident module 2. Email 4. The alerts to each sink should be configurable based on the group and topic of each job - in other words, depending on the owner (group) and the topic of the job, the alerts should be sent to the respective teams

Web-based Dashboard App

Project name: Import function for 3rd party Bots to native Genesys Bots

Project description: Develop an import function that will allow an admin user to target an existing 3rd party Bot – e.g. DialogFlow or Lex and then import that definition converting it to the Dialog Engine definition. Part of the import process will be to identify custom extensions on the 3rd party Bot side that would require to be reimplemented on the Dialog Engine side – e.g. the use of a Webhook.

Import function for 3rd party Bots to native Genesys Bots


I’d just like to acknowledge the fantastic work done by the students over the last few months. Starting with almost a blank sheet with regard to Bots, the team demonstrated a real thirst for learning and hard work over the course of the engagement. The communication from the students was excellent. We met on a weekly basis, agreed on goals and deliverables for the upcoming week, and the team always delivered on those commitments. The quality of the work was top class, and they have proved out some concepts that I’m sure will be useful to Genesys in the future. In my view the team went above and beyond to deliver a fully functional Bot conversion tool. Personally I’m very impressed with the calibre of undergraduates on the SWENG course, and would certainly be open to participating in this program in future.

Patrick Buckley

Senior Manager, Development - Genesys

As the projects are done and handed over, we wanted to express that we’re especially pleased with the group we had this year...The group put together such a complete effort in such a short amount of time, and with relatively little intervention on our part – they grasped and executed the requirements mostly independently, and the result is something that is actually useful to us.

Jonathan Epperlein

Research Scientist - IBM Research Europe

Wonderful opportunity to be involved in the development of the next generation of software talent through the Sweng project! What a pleasure for Mersus Technologies. The students that worked with us demonstrated responsiveness, technical competence, and openness to learning throughout the project assigned to them. Very gratifying to observe the growth in their interpersonal skills and increased technical proficiencies over the weeks. They brought a renewed vigour to the team in Mersus. Congratulations to Trinity on the exceptional students they are cultivating and look forward to taking part next year.

Brenda Mannion

Chief Operating Officer - Mersus Technologies