Current Research Group Members
Faculty
Prof. Michael Madden
Prof. Michael Madden's research is focused on new theoretical advances in machine learning and data mining, motivated by important practical applications, on the basis that challenging applications foster novel algorithms which in turn enable new applications. Specific research topics include: Artificial intelligence; Algorithms for classification and numeric prediction; New methods for combining domain knowledge with data mining; Time series data analysis; Reasoning under uncertainty; Bayesian networks; Reinforcement learning; Applications in science, engineering & medicine. Further details can be found on these links (Personal Webpage, GoogleScholar)
Dr Frank Glavin
I received an honours B.Sc. degree in Information Technology from NUI Galway in 2006. I received an M.Sc. degree in Applied Computing and Information Technology from NUI Galway in 2010 as part of a collaborative project between NUI Galway and UCD. This work resulted in a publication which won a best paper award at a national AI conference. I received a Ph.D. from NUI Galway in 2016. My Ph.D. research involved designing and implementing multiple reinforcement learning architectures in Java to automate the control and adaption of non-player characters in a commercial first-person shooter game. My Ph.D. work resulted in four peer-reviewed papers being published including an international student best paper award. Upon finishing my Ph.D., I began work as a software engineer for Analyze IQ™ Limited and this involved designing and developing software applications for performing data analytics and library search on spectral data. I took up the post of Below the Bar Lecturer in Information Technology on a fixed term basis in August 2016.Further details can be found on these links (Personal Webpage, GoogleScholar)
Postdoctoral Researchers and Engineers
Dr Brett Drury (Research Fellow): Remotely Operated CBRNE Scene Assessment and Forensic Examination (EU H2020 ROCSAFE)
Dr Ihsan Ullah (Senior Postdoctoral Researcher): Remotely Operated CBRNE Scene Assessment and Forensic Examination (EU H2020 ROCSAFE)
I received my BS in Information Technology from University of Peshawar, Pakistan in 2008. I was awarded fellowship from King Saud University and joined Visual Computing Lab as Researcher Assistant (Feb 2009 till Dec 2012). In addition to other projects, I completed my MS(CS) degree focusing on category based feature extraction/selection for face recognition. I was awarded full PhD scholarship by University of Milan, Italy in 2013. I joined CVPR lab University of Naples Parthenope under supervision of Prof. Alfredo Petrosino and started working on designing of deep neural network architectures. During PhD, I worked as a visiting researcher at CVGL Lab Stanford in 2015 under supervision of Prof. Silvio Saverese and Dr. Amir Zamir. My research interest/experience include supervised recognition problems as well as designing deep models. Prior to ROCSAFE, I was working on Open Social Data Crime Analytics, a project by DM&ML group in collaboration with Insight Centre for Data Analytics Galway and IBM Ireland. Further details can be found on these links (Personal Webpage, GoogleScholar)
James Fennell (Research Software Engineer): Remotely Operated CBRNE Scene Assessment and Forensic Examination (EU H2020 ROCSAFE)
PhD and Research MSc students
Mary Loftus (PhD Student)
Biography: My primary degree is in Communications Studies from DCU (formerly NIHE) and after an early career in youth work and local development, I freelanced as an IT Consultant for over 15 years. In 2006, I graduated with a Masters in Software & Information Systems from NUI Galway and did some research on student feedback in an online learning environment. I managed a team in a corporate IT environment from 2011 to 2015 where we completed €2m IT infrastructure upgrade. In 2015 I began my PhD research under the supervision of Professor Michael Madden, looking at the application of machine learning and learning analytics to support student self-reflection and metacognition in learning environments. I teach subjects like Internet of Things, Artificial Intelligence, Distributed Systems and Software Engineering on IT Sligo’s BSc in Computer Science and on NUI Galway’s MSc in Software Engineering & Database Technologies.
Personal Webpage
David Smyth
I completed my BS in Mathematics and Computer Science in NUIG, 2017. I was awarded the Blaney exhibition for receiving the highest mark in Mathematics for the undenominated science stream as well as an entrance scholarship in my first year and excellence scholarships in all four years of my undergraduate for high results. I was also awarded a scholarship to study in the Hong Kong University of Science and Technology in the first semester of my third year of my undergraduate degree. During my undergraduate summers I worked as a data scientist for Prudential and Orreco. My research interests include multi-agent systems, optimization and statistics. My github page (Link) contains software projects that I have worked on in my spare time.
Sai Abinesh Natarajan
I am currently doing research on an EU funded project called ROCSAFE, in the super exciting area of Deep learning, for image and sensor data analysis. I also have a Masters in Data Analytics from NUIG that gave me a good hands-on in state-of-the-art techniques and tools, in Machine learning, Natural Language Processing, Web mining, Big data, and Interactive Web visualization. Before my masters I worked as a data analyst, serving clients in various industries ranging from healthcare, finance and consulting, to engineering and education. I believe that analytical insights should lead to a tangible financial or social impact.
Hamda bint-e Ajmal
Nazli Bagherzadeh Karimi
Ghanshyam Verma (jointly with Prof. Dietrich Rebholz-Schumann)
Students on Taught Programmes
Mark McConn (BSc CS&IT): Creation of a Virtual Parking World
Sean Reilly (BSc CS&IT): Road Sign Identification for Autonomous Driving
Ashfaque Azad (MSc CS Data Analytics): Autonomous Driving: Identifying Pedestrians, Road Signs and other Key Items Reliably
Suchandra Mandal (MSc CS Data Analytics): The Semantic Annotation of Natural Images using Deep Learning and Synthetic Training Data
Maria Scanlon (MSc CS Data Analytics): Deep Learning using Natural and Synthetic Images
Ashwin Naidu (MSc CS Data Analytics): Optimizing 3D Pyramidal Neural Network for Action/Scene Recognition
Alumni
Past Postdoctoral Researchers and Research Software Engineers
Dr Catherine Enright, 2012-2015: Senior Postdoctoral Researcher, Handhold FP7 project.
Dr Frank Glavin (short term, 2015-16): Postdoctoral Researcher, Scientific Solutions for Secure Societies.
Dr Ricardo Santiago Mozos, Postdoctoral Researcher, 2009-11: Galway Lab for Biomedical Data Mining, then 1-year Spanish Government Grant.
Dr Abdenour Bounsair, Postdoctoral Researcher, 2007-2010: OSCAIL project, then Galway Lab for Biomedical Data Mining.
Dr Imtiaz Khan, Postdoctoral Researcher, 2009-10: Galway Lab for Biomedical Data Mining.
Dr Mei Chen, Postdoctoral Researcher, 2009-10: Galway Lab for Biomedical Data Mining.
Shehroz Khan, Software Engineer on [CS]2 project, 2008-2009.
Dr Yang Liu, Postdoctoral Researcher, 2006-2007: OSCAIL project.
Rúben Carvalho, Software Engineer, 2004-2006: Hazard-IQ (Intelligent Quantification of Hazardous and Illicit Materials).
Dr Ken Hennessy, Postdoctoral Researcher 2006-2007: Hazard-IQ (Intelligent Quantification of Hazardous and Illicit Materials).
Dr Tom Howley; Postdoctoral Researcher 2006-2007: QRS/ML (Quantitative Raman Spectroscopy using Machine Learning Techniques).
Dr Dayong Gao, Postdoctoral Researcher, 2004-2005: PRIMA project (Machine Learning Techniques for Portable Remote Intelligent Medical Agents).
Past PhD & Major MSc Research Theses
Garg, Ankita: “A Novel Library Search Approach: The ‘Contains’ Concept”, MSc Research Thesis, submitted August 2017.
Glavin, Frank: “Towards Inherently Adaptive First Person Shooter Agents using Reinforcement Learning”, PhD Thesis, awarded Nov 2015.
Enright, Catherine: “A Probabilistic Framework with Application to Medical Data Streams”, PhD Thesis, awarded September 2012.
Glavin, Frank G.: “A One-Sided Classification Toolkit with Applications in the Analysis of Spectroscopy Data”, MSc Research Thesis, awarded September 2010.
Khan, Shehroz S.: “Kernels for One-Class Nearest Neighbour Classification and Comparison of Chemical Spectral Data”, MSc Research Thesis,awarded July 2010.
Lyons, William: “Data Mining for Academic Institutions.” MSc Research Thesis, awarded November 2008.
Hennessy, Kenneth: “Machine Learning Techniques for the Analysis of Raman Spectra.” PhD Thesis, awarded June 2007.
Howley, Thomas: “Kernel Methods for Machine Learning with Application to the Analysis of Raman Spectra.” PhD Thesis, awarded June 2007.
Scully, Edward Andrew: “Coalition Formation and Calculation in Dynamic Multi-Agent Environments.” PhD Thesis, awarded May 2006.
Xing, Yan: “Context-Based Numeric Prediction for Distributed Data with Contextual Heterogeneity.” PhD Thesis, awarded December 2004.
Ridge, Enda: “The Evolution of Reciprocity in a Multi-Agent Environment with Neighbourhoods.” MSc Research Thesis, awarded September 2004.
Past Minor MSc Theses
Creaven, Ben: “The Impact Adaptive Cruise Control Systems Have on a Small City’s Road Network”, MSc Software Design & Development Thesis, awarded Sept 2017.
Natarajan, Sai Abinesh: “Prediction of Future News Trends”, (co-supervised with Dr Brett Drury), MSc CS Data Analytics Thesis, awarded Sept 2017.
O’Neill, James: “Classification and Risk Scoring of Cardiovascular-Related Mortality Using Ambulatory Blood Pressure Monitoring Measurements in a Hypertensive Population”, MSc CS Data Analytics Thesis, awarded Sept 2016.
Reilly, Eoin: “Optimisation and Influential Factor Analysis for an Enterprise Sales Forecasting Model”, MSc SDD Thesis supported by HP Enterprise, awarded Sept 2016.
Bhreathnach, Gráinne: “Real Time Human Activity Recognition Using Multiple Sensor Streams”, MSc SDD Thesis supported by HP Enterprise, awarded Sept 2016.
Steven, Cory: “An Energy Efficient Predictive Heating System using Particle Filtering”, MSc SDD Thesis, awarded Sept 2016.
Gallagher, Claire: “A Bayesian Classification Approach to Improving Performance for a Real-World Sales Forecasting Application”, MSc SDD Thesis supported by HP Enterprise, awarded Sept 2015.
Taaffe, Robert: “Cluster Analysis of Smart Meter Data”, MSc SDD Thesis, awarded Sept 2015.
Tomkins, Joseph: “Analysing the Performance Differences between Distributed and Standalone Frameworks on Processing Small to Medium Sized Datasets”, MSc SDD Thesis, awarded Sept 2015.
Gaurav, Tejasvi: “Analyzing Salesforce Data and Open Government Data to Predict Matches Between Them”, MSc SDD Thesis supported by HP Enterprise, Sept 2015.
Bradshaw, Stephen: “The Application of Reinforcement Learning to Robotics”, MSc SDD Thesis, awarded Sept 2013.
Tighe, Darren: “Transfer of Experience Between Simulated and Situated Robotics”, MSc SDD Thesis, awarded Sept 2013.
Flood, Ciarán: “Hadoop Based Storage and Analysis of Events”, MSc SDD Thesis, awarded Sept 2013.
Fitzgerald, Sarah: “Mining of Data from Census of 1901/1911”, MSc(SIS) Thesis, awarded September 2012.
McDonagh, David: “A Practical Probabilistic Approach to Predicting Glycaemia Levels in Intensive Care Unit Patients”, MSc SDD Thesis, awarded September 2011.
O’Connor, Enda: “Improving the Performance of Dynamic Bayesian Network Inference by Varying Uncertainty over Time”, MSc SDD Thesis, awarded September 2011.
O’Rourke, Conor: “Activity Recognition Based on Accelerometer Data Using Dynamic Time Warping with Ensembles”, MSc SDD Thesis, awarded September 2011.
O’Malley, John: “Image Recognition of Tuberculosis in Sputum”, MSc SDD Thesis, awarded September 2011.
Byrne, Matthew: “Visualisation and Cross Census Family-Tree Building using 1901 and 1911 Census Data”, MSc SDD Thesis, awarded September 2011.
O’Mahony, Sunghwa: “A Machine Learning Approach to Batch Chemical Process Data Modelling.” MSc SIS Thesis, awarded October 2008.
Munroe, Daniel: “Machine Learning Methods for Automatic Vehicle Model Recognition from Images.” MSc SDD Thesis, awarded October 2005.
Nagle, Keith: “Machine Learning Techniques Applied to Raman Spectral Data For Cancer Detection.” MSc SDD Thesis, awarded October 2004.
Torpey, Colin: “The Implication of Using Regression and Neural Network Models for Forecasting Financial Time Series Data.” MSc SDD Thesis, awarded October 2002.
Raftery, Gillian: “A Machine Learning Approach to Diagnosis of Gastrointestinal Ailments.” MSc SDD Thesis, awarded October 2002.
O’Farrell, Patrick: “Control of Software Development for Internet-Based Projects.” MIT Thesis, awarded October 2001.
