Dr Matthias Nickles is a Lecturer Above the Bar (≈ Assistant Professor with tenure) in the School of Computer Science at National University of Ireland, Galway. He commenced his current position after studying Computer Science with Psychology at Ludwig Maximilians University Munich (LMU), obtaining a PhD in 2006 in Computer Science/Artificial Intelligence from Technical University of Munich (TUM), Germany, and working in research and teaching positions at TUM and University of Bath (UK). His main research interests are in Artificial Intelligence, in particular Machine Learning (Statistical Relational Learning and Reinforcement Learning), Probabilistic Logics, Satisfiability Solving, Answer Set Programming, Semantic Technologies, and Multiagent Systems. He has authored or co-authored more than 80 publications in his research areas and has been a member of more than 40 program committees and 12 organization committees of international workshops or conferences. He was appointed a W3C Invited Expert on Web Uncertainty Reasoning and has been active in several collaborative research projects in his research areas.

Takfarinas is a Lecturer in the School of Computer Science at the National University of Ireland, Galway (NUIG) and a Funded-Investigator in Lero, the Science Foundation Ireland Research Centre for Software. 

His area of expertise is in the optimisation of Complex Software Engineering Systems such as Cloud Computing, Software Engineering and Testing, and Communication Network Systems. He designs and applies novel Artificial Intelligence techniques from Machine Learning, Operations Research, and Evolutionary Computation/Learning to improve the Performance and Trustworthiness of such systems.

Previously, he has held a lecturer position both in the School of Computing at Dublin City University (DCU) and in the School of Computer Science at Dublin City University (UCD). He has also held a Post-doctoral Researcher position at the Natural Computing Research & Applications Group at Michael Smurfit Graduate Business School, UCD.

He obtained his PhD in Computer Science in 2017 from UCD, Ireland. His PhD topic is Multi-objective Optimisation of Large-Scale Data Centres. He received his BSc in Computer Science and his MSc in Computer Science, track: Optimisation In Operations Research from the University of Nantes, France.

Dr. Ihsan Ullah did his Ph.D. in the University of Milan, specializing in designing lightweight deep neural network architectures with the pyramidal approach. He has more than nine years of research and development experience in applying Deep Learning to a variety of images, video, text, and time-series recognition problems while working with renowned labs in the US (Computational Vision and Geometry Lab at Stanford University), Europe (at CVPR Lab at the University of Naples Parthenope, Italy), and the Middle East (Visual Computing Lab in King Saud University, Saudi Arabia). Before joining the School of Computer Science in NUI Galway, he was a Senior Research Data Scientist in CeADAR Ireland’s Centre for Applied AI in University College Dublin where he was the head of the Special Projects group and was actively involved in applying for various national and international fundings e.g., Horizon Europe, SFI, EI. Prior to that, he worked in Data Mining and Machine Learning Group of School of Computer Science in NUI Galway as a Senior Postdoc, Adjunct Lecturer, and Project Manager of the H2020 project ‘ROCSAFE’. He also worked as a Postdoc at INSIGHT Research Centre in NUI Galway and Research Engineer in Prosa Srl Italy. His research interests are mainly in computer vision and designing lightweight deep neural network architectures with the pyramidal approach. More specifically, he worked on recognition & segmentation problems in health, autonomous vehicles, & other application areas as well as understanding the deep AI models with explainable AI techniques. I am also interested to work on differential privacy and synthetic data generation. Specific research interests in semantic segmentation of aerial images, Aortic segmentation, medical report generation, object/pedestrian detection, multi-object tracking, fish species (Salmon) recognition/tracking/detection, explainable AI, federated learning, synthetic data generation, and signal processing (EEG, ECG, etc.).

I am a tenured Lecturer (Assistant Professor) in the School of Computer Science at NUI Galway. Previously, I held appointments as:

• Postdoctoral Researcher in the CIREGS lab at Cardiff University, UK, working with Dr. Meysam Qadrdan. This work was funded by the EPSRC.
• Postdoctoral Fellow at the Georgia Institute of Technology, USA within the ACES Research Group, directed by Prof. Santiago Grijalva, in collaboration with Sandia National Laboratories. My work was funded by Sandia National Laboratories and the National Science Foundation.

Before this, I completed my PhD in Computer Science at the National University of Ireland, Galway. My PhD research primarily consisted of developing methods to evolve neural networks and to apply these algorithms within the energy sector for tasks such as: wind generation forecasting, electricity generation dispatch, etc. This PhD dissertation was nominated for the 2018 European AI PhD Dissertation award.

My research broadly falls under the heading of machine learning, but explores multiple topics including: neural networks, evolutionary computing, reinforcement learning, multi-agent systems and swarm intelligence. I’m also interested in applications of machine learning methods to problems including: renewable energy, smart homes, infrastructure planning, smart grid, robotics and cloud computing.

I am currently a Lecturer in the National University of Ireland Galway and am responsible for the delivery of five modules each year which are attended by 400+ students, with subjects ranging from Software Engineering, to Web Programming and Reinforcement Learning. I have extensive experience in Machine Learning extending from my Masters right through to my PhD. Upon graduation in 2006, from a BSc in Computer Science, I was invited to join a research team as a research assistant for one year, researching business process analytics solutions. In 2009, I completed a MSc (research) where my thesis contribution was the research and development of machine learning techniques to accurately classify cardiac arrhythmias from 3 lead ECG communicated over a Zigbee wireless sensor network. In 2013, I received my Ph.D. in Computer Science from NUI Galway. My PhD research investigated the application of a subset of machine learning techniques known as reinforcement learning to automate resource allocations and scale applications in infrastructure as a service cloud computing environments. Upon completion of my PhD, I joined Schneider Electric as a research engineer on a globally distributed innovation team. In industry, I worked on projects which included data analytics, linked data (designing enterprise level data integration solutions, ontology design and mapping) and training machine learning classifiers for acoustic event classification (specifically detecting household alarm sounds in the presence of noise). Since returning to academia in 2015, I have authored or co-authored over 50 research articles, I hold 4 patents and have won a number of competitive funding awards. I am actively pursuing research in machine learning, cloud and distributed computing problems, cybersecurity and computer vision.

Dr Patrick Mannion is a permanent member of academic staff at National University of Ireland Galway (NUIG), where he lectures in Computer Science. He is also Programme Director of the PgCert in Artificial Intelligence for Managers which was developed in collaboration with itag Skillnet. Since 2020 he has served as Deputy Editor of The Knowledge Engineering Review journal (Cambridge University Press, Scimago rank Q2). He previously served as a permanent Lecturer in Computing at Galway-Mayo Institute of Technology (GMIT). 

He received a BEng in Civil Engineering, a HDip in Software Development and a PhD in Machine Learning from NUIG, a PgCert in Teaching & Learning from GMIT and a PgCert in Sensors for Autonomous Vehicles from IT Sligo. Dr Mannion was awarded an Irish Research Council Government of Ireland Postgraduate Scholarship and an NUI Galway College of Engineering and Informatics Postgraduate Scholarship for his PhD studies. He was a silver medalist in the 2006 Irish Junior Science Olympiad, and represented Ireland in the 2006 International Junior Science Olympiad in Sao Paulo. In 2018, he visited Prof Kagan Tumer at the Collaborative Robotics and Intelligent Systems Institute, Oregon State University as a Fulbright-TechImpact Scholar. 

Dr Mannion served as Co-Chair and Co-Organiser for the 1st Multi-Objective Decision Making Workshop (http://modem2021.cs.nuigalway.ie/), which was held online during July 2021. He also served as Co-Chair and Co-Organiser for the Adaptive and Learning Agents workshops which were held in May 2017 at AAMAS in Sao Paulo (http://ala2017.it.nuigalway.ie), in July 2018 at the Federated AI Meeting in Stockholm (http://ala2018.it.nuigalway.ie) and in May 2019 at AAMAS in Montreal (http://ala2019.vub.ac.be). Dr Mannion has served as a member of the Senior Steering Committee of the Adaptive and Learning Agents Workshop series since May 2019. He has also served on the Senior Program Committee for the European Conference on Artificial Intelligence (ECAI).

colm.oriordan@nuigalway.ie

Prof. Michael Madden is the Established Professor and Head of School of Computer Science in NUI Galway. He leads the Machine Learning Research Group that he set up in 2001 in NUI Galway. His research focuses on new theoretical advances in machine learning, motivated by addressing important data-driven applications in medicine, engineering, and the physical sciences. This has led to over 100 publications, 9 publication awards, 4 patents and a spin-out company. He has spent time as a Visiting Research Scientist in University of Helsinki, University of California Irvine, and UC Berkeley.

His research includes: deep learning with data augmentation from virtual environments; learning agents and autonomous robotics; model-based probabilistic analytics for time series data analysis and decision-making; reasoning under uncertainty; Dynamic Bayesian Networks (DBNs) for representing medical knowledge and combining it with patient data for improved ICU monitoring; health monitoring using gene expression data.

Prof. Jim Duggan is a Personal Professor at the School of Computer Science, National University of Ireland Galway. Prof. Duggan has held a range of senior roles with NUIG, including Head of Department (two terms), Vice-Dean of Research and Graduate Studies, and has served on the Standing Committee and Academic Council. Prof. Duggan is a member of the Ryan Institute, the Data Science Institute, and is a Funded Investigator at the Insight Centre for Data Analytics. Prof. Duggan is a Managing Editor of the System Dynamics Review, and his research interests span simulation, mathematical modelling and data science, with applications in public health. Prof. Duggan is a member of the Irish Epidemiological Modelling Advisory Group (IEMAG), and also a member of the World Health Organisation’s Global Outbreak and Response Network.