Here are some project ideas I have for PhD, MPhil, MSc (team or individual and Final Year Under-grad projects (see list below).

If you are interested in these topics and would like to discuss then get in touch. But make sure that you have performed some detailed research on the proposed topics. This will allow you come to the discussion with ideas and questions, rather than saying that “I’m interested in this topic, can you tell me more about it”.

Funding: For MPhil and PhD student projects, there is currently no funding available for these projects. You will have to fund your project yourself or apply for funding before commencing the project. There are many sources for obtaining funding. Check with the DIT Post Graduate office for details.

MSc, MPhil and PhD projects

ASD Real-time Database Monitoring tool Build an application to monitor the database and all internal processes in real-time. To provide informative visualizations and data insights on what is happening, using various trend analysis and ML to identify anonomalies and alerts. Can this tool be build to work with more than one data vendor?
DA & ASD Augmented Data Analysis and Machine Learning Build an augmented data analysis and machine learning tool. Capable of loading any data set, analyse it, understand it, visualize the data, perform data enrichment, identify feature engineering, identify possible ML algorithms to use. All done automatically, with just a click of a button from the user. All they need to do is specify the data set.
DA & ASD Data Indexing using Machine Learning Check out the paper by the Google AI team on using neural networks as an alternative to B-tree indexes. Can you build something similar, can you improve on their design, can other ML algorithms be used, how does this scale, etc. There are lots and lots of possibilities with this project
DA Analysing people musical tastes This project will look at examining the musical characteristics of persons faviourate music. Taking in batches of various sizes to determine the optional number of compositions to determine a style. The music will be broken down into key components and compared across all music in the batch. A similar approach can be used to analyse how music styles have evolved over time for different musicians
ASD Evaluation of Low Code development environmrnt In recent years a number of Low Code software development environments have evolved. This project will look at evaluating 3-5 of these to examine their features, development effort, developer skills, adoption within enterprises and how these type of low code development enviroments are will impact in future
ASD Walk with me – for the visually impared This project will look at using a Raspberry Pi enabled camara to allow the visually imparted to walk down a street un-aided. The camera will constantly scan the environment, taking pictures in real time, scanning these images and then providing voice descriptions of the environment. This will allow the person to visualise their environment. When the person walks the image and data process will detect this and will feed motion related information to the user, such as certain objects are getting closer or moving away. The system will also identify potential hazards such as people, rubbish bins and other obsticals. All image and other process to be performed on a Raspberry Pi
DA & ASD Real-time Anomaly Detection of Server or Database Alert logs You need to have access to server or a database activity logs for this project. Using anomoly detection, along with variations in time-periods, identify unusual activity and provide appropriate level of nofication and information about the alert.
DA Syntetic data generation for imbalanced data sets An examination of various methods for the generation of syntetic data for imbalanced data sets. Similar to the processing used in SMOTH, additional techniques will be used and evaluated to determine their effectiveness for input to machine learning
ASD Twitter profile follower generator using GO Using Google Go language, build a library for the Twitter API. Then use this library to create an application to allow a user to increase their number of followers on twitter. Various approaches should be evaluated and implemented using the newly created library. The application should identify, based on an existing user profile, how to increase their number of followers.
DA & ASD Using Music and Machine Learning for Database Monitoring Combine your love of music and machine learning to monitor Database activity. This activity will involve monitoring the database engine logging and using a combination of anomaly detection, with moving windows of data selections to identify and capture the moving trends in the activity logs. Then take this activity and compose music (based on your favorite artist or genre) as a reporting mechanism. Then unusual activity is identified then this needs to be reflected in the music.
ASD Database storage 4.0- Multi storage management for next stage database In the next phase of database management will see an integrated approach to how and where the data is stored. The past decade has seen the push by the Hadoop eco-system to replace the traditional database. But given the install based of traditional databases and differing analytic requirements a complete migration will not happen. In the multi-storage enviroment data, within the database, can reside on one or more storage media and locations. These can include in-memory, flash, solid state, sindle and also on Hodoop. Based on the information lifecycle management approach for defining where data will reside, a new framework is needed to dynamically management to movement of the data based on the frequency of usage. The project will look at how the data can be dynamically and efficiently migrated between storage media with the minimum of downtime.
ASD Automation of VM builds and migrations using vagrant, ansible, docker and virtual machines, And how to autmate the migration of these to different Cloud vendors Automation of VM builds and migrations using vagrant, ansible, docker and virtual machines, And how to autmate the migration of these to different Cloud vendors
DA Evaluation of AutoML features across languages and tools The use of Automated Machine Learning (AutoML) is going to replace the data scientist! Or so they say. This project will evaluate the various AutoML solutions proposed by various vendors and languages to measure how good they really are, and how likely will companies and data scientists truct the use of them.
DA & ASD Building a repository for continuously evolving self monitoring predictive analytics models his project will focus at building the process to manage an automous building and rebuild of predictive models within an adaptive intelligence project. You will be working with many predictive and machine learning algorithms, building automated tools for the selection of the appropriate algorithms dependent on the underlying data sets. This project will integrate in with the other Adaptive Intelligence projects with the aim at developing an integrated solution that can easily be deployed in any environment.
ASD Is it really possible to build a Big Data cluster using Raspberry Pis In the era of big data and IoTs the cost associated with building a clustered environment can be huge. This project will look at building a Hadoop 5 node cluster using Raspberry Pi and evaluate how effective it is capturing data are different delivery rates. The data can be sent for storage on the cluster using Kafka. The second part will exaine the efficiency data analysis using this cluster. [The student will have to purchase the required equiment]
ASD Evaluation of Json and complex objects in Oracle, ProgreSQL, SQL Server and DB2 Most databases allow the creatation of Json objects within the database and the embed these into traditional database tables. This project will examine how the main database vendors have implemented these features and assess their capabilities and ability to scale. Additional most databases allow the creation of nested and other complex data structures. A similar evaluation will be performed on these
ASD Replacing the SQL query engine with JavaScript and Python This project will perform a detailed evaluation of the Oracle Multi-lingual Engine, benchmarking it’s performace against the traditional SQL query engine.
ASD & DA Expanding the analytical capabilities of the Database using the embedded JVM Most enterprise level databases come with an inbuilt JVM. This allows you to create new functions within the database using Java. This project will take a number of machine learning, and various analytical functions and write these in optimised Java code, store these in the database and then evaluate the performance of these features against the existing equivalent functions in the database
ASD Evaluation of live application upgrades with zero down time Evaluation of solutions by leading vedors of live application and database upgrades with zero downtime. For example Oracle for a tool called Edition Based Redefinition. Other vendors have similar products. This project will review these tools and will provide an evaluation and benchmark of their use.
ASD & DA Evaluation of Big Data Machine Learning Languages The Apache foundation have a number of machine learning projects. Some of these have a SQL interface. These include HiveMall, MADlib, Storm and others. THis project will evaluate the machine learning capabilities of these languages, providing numberof worked scenarios. These senarios will be benchmarked against each other
ASD Security issues of bi-directional cloud portability for applications Many frameworks exist to help developers build applications for cloud native architectures, both those in the cloud as well as those behind the firewall. Applications are becoming more complex with many components sitting in serverless and container environments hosted in the Cloud and behind a corporate firewall. This project will examine the implications of such frameworks and technical architectures and present a numberof alternative solutions
ASD Fn: The next phase of application architectures The Fn project is an open-source container-native serverless platform that you can run anywhere — any cloud or on-premise. It’s easy to use, supports every programming language, and is extensible and performant. With Fn, you deploy your functions to an Fn server which automatically executes and manages them. Each function is executed in a Docker container enabling the platform to provide broad support for development languages including Java, JavaScript (Node), Go, Python, Ruby, and others. Fn project has a strong enterprise focus with emphasis on security, scalability, and observability. In serverless, the small piece of code that does all the work is called a Function. And, a serverless cloud service typically provide functions-as-a-service (FAAS). Thus all the plumbing needed to provision, scale, patch and maintain the environment is provided by the service.

Adaptive Intelligence Projects
Many organization have been building predictive and machine learning models and applications over the past few years. The number these grows so does the complexity and human effort needed to manage these predictive and machine learning models. These tasks can become overwhelming and some organizations are just not able to keep up with the maintenance of these. There are a number of reasons for this. Firstly having or recruiting enough people with the right skills is major challenge. Secondly some of the tasks involved can be considered mundane and the data scientists are not really interested in doing this.

With adaptive intelligence, these tasks, at a basic level, can be automated. But there the really value comes with adaptive intelligence is the ability to learn and change how the predictive and machine learning models evolve over time, adapting to the changes in the data, with the customers, and how the transnational data will also evolve over time. The adaptive intelligence solution will automate all of this, informing the data scientists and business users of the changing patterns in the data. Additionally with adaptive intelligence, it will constantly monitor newly defined data sources and will determine how this can be used with existing data and predictive models, as well as making new recommendations.

Research Area
Project
Description
Adaptive Intelligence Building a repository for continuously evolving self monitoring predictive analytics models Many organization have been building predictive and machine learning models and applications over the past few years. The number these grows so does the complexity and human effort needed to manage these predictive and machine learning models. These tasks can become overwhelming and some organizations are just not able to keep up with the maintenance of these. There are a number of reasons for this. Firstly having or recruiting enough people with the right skills is major challenge. Secondly some of the tasks involved can be considered mundane and the data scientists are not really interested in doing this.
Identifying the when predictive models should be regenerated and recommending outcomes This project will focus at building the process to manage an automous building and rebuild of predictive models within an adaptive intelligence project. You will be working with many predictive and machine learning algorithms, building automated tools for the selection of the appropriate algorithms dependent on the underlying data sets. This project will integrate in with the other Adaptive Intelligence projects with the aim at developing an integrated solution that can easily be deployed in any environment.
Interpreting the impact of new data for predictive model success With this project you will be responsible for researching the appropriate evaluation metics to use for dynamic rebuild of 10s or 100s of predictive models using a variety of machine learning algorithms and to design and develop a recommendation engine to process this data in a near real time manner. As part of this process the solution will need to monitor when model rebuilds should occur and to assess what newly identified data can be included to asses it’s impact. The impacts can include to include or exclude certain part of the available dataset, as well as assessing the impact of using various machine learning models based on requirements from the business.
Developing visualisations that present meaningful results from the adaptive intelligence process With this project you will be responsible for designing a visualisation solution for the Adaptive Intelligence project. You will be responsible for researching, designing and building visualization solutions that automatically adjust and adapt to the changing nature of the predictive models produced by the adaptive intelligence solution. The visualisations will need to clearly show what data changes occurred, why those changes are significant, what data is no long significant, how the performance of the predictive models have been influences by the changes in the data, and to clearly present recommendations and conclusions drawn from the process. The end user of this application will be a data analyst who has limited knowledge of all the data and machine learning algorithms used, or the vast number of models produced. They will want to quickly inspect the results from the adaptive intelligence solution to identify key changes in the data so that they can act on these within their organisation.

Data, Database Management & Blockchain Projects
Project : Database storage 4.0- Multi storage management for next stage database
In the next phase of database management will see an integrated approach to how and where the data is stored. The past decade has seen the push by the Hadoop eco-system to replace the traditional database. But given the install based of traditional databases and differing analytic requirements a complete migration will not happen. In the multi-storage enviroment data, within the database, can reside on one or more storage media and locations. These can include in-memory, flash, solid state, sindle and also on Hodoop. Based on the information lifecycle management approach for defining where data will reside, a new framework is needed to dynamically management to movement of the data based on the frequency of usage. The project will look at how the data can be dynamically and efficiently migrated between storage media with the minimum of downtime.

Project : Querying all your data using SQL
Many of the database vendors allow you to store different types of structured and unstructured data in their Databases. Additionally they have some additional tools that allow you to query your data that is stored outside of the data. All done using the SQL. For example in Oracle you can query relational tables, XML, JSON, external files and even data stored on Hadoop using SQL. You can write queries that will select, merge, aggregate and format data from all of these data sources using one SELECT statement. This project will explore the features available in the Oracle Database and other databases that allow you to query all your data

Project : Polyglot Data Management and Storage. Is this something new or do all modern databases support this
Research the issues relating to Polyglot data managment and the various use cases around the creation and usage of data in a polyglot world. There are lots of scenarios relating to polyglot and most of these seem to be related to various programming paradigms.  But what about the storage of the data. At first it might appear multiple different database storage methods are required. If this is the case then that adds lots of complexity. This project will examine the capabilities of modern enterprise databases (current/modern versions of the traditional relational database) to evaluate how they support the polyglot data environment. Some of the databases to be evaluated include Oracle, DB2, SQL Server, Progress (EnterpriseDB), etc.

Project : Blockchain is just a fancy name for a distributed database! Discuss
Blockchain technology can be considered as an implementation of a distributed database. But it is a lot more than that. This project will look at examining the data storage, security and protection of a blockchain and how the new EU GDPRs can be addressed using blockchain technology. The student can use their current employer as a use case or base in on a company that they have close ties with. Students will need to build a demonstration of how the blockchain technology can be used in their use case.

Using Music and Machine Learning for Database Monitoring
Combine your love of music and machine learning to monitor Database activity. This activity will involve monitoring the database engine logging and using a combination of anomaly detection, with moving windows of data selections to identify and capture the moving trends in the activity logs. Then take this activity and compose music (based on your favorite artist or genre) as a reporting mechanism. Then unusual activity is identified then this needs to be reflected in the music.

Final Year Under-Grad project
The following projects are suitable for final year under-grad projects for full-time and part-time students.

(The following project should could Oracle APEX as the application development framework.)

Conference Organizer
Develop an application to allow the management of a conference from paper/presentation submissions right through to recording attendance and getting attendee feedback. Some of the main components can include:

  • Conference setup and call for papers/presentation
  • Speaker registration
  • Uploading of presentations
  • Conference committee evaluation of submissions and final section
  • Notifications of acceptances and rejects
  • Conference agenda creation applying for multiple tracks
  • Allow attendees to register for the event
  • Management conference communications
  • Manage attendee attendance and by session
  • Gather sessions and conference feedback

Building searchable applications using Oracle Text and APEX
Oracle Text is a feature in the Oracle Database that allows you search, structure, index and data mining text in your database. This project will explore these features and will build demonstrations using APEX that show what is capable with these tools.

An examination of options available to include/run other languages in a Database
for example you can run C, Java, etc code include your Oracle Database. This project will look at what other languages can be used within an Oracle Database, using the Oracle Call Interface (OCI), Oracle Java Connection, etc  The ability to include other languages can greatly expand the computing capabilities of a Database

Querying all your data using SQL
Many of the database vendors allow you to store different types of structured and unstructured data in their Databases. Additionally they have some additional tools that allow you to query your data that is stored outside of the data. All done using the SQL. For example in Oracle you can query relational tables, XML, JSON, external files and even data stored on Hadoop using SQL. You can write queries that will select, merge, aggregate and format data from all of these data sources using one SELECT statement. This project will explore the features available in the Oracle Database and other databases that allow you to query all your data

Multi-platform application development using Oracle APEX
Oracle APEX is an in-database application development framework that is based on the SQL and PL/SQL applications.You can build small to complex applications using APEX. This project will examine the feature available within APEX that allows an application to be deployed on multiple platforms including, desktop, browser, tablet, and other mobile devices.