Marija Bezbradica Dr. Marija Bezbradica is an Assistant Professor at the School of Computing, Dublin City University (Ireland). Marija obtained her B.Sc.E.E. and M.Sc. from the School of Electrical Engineering, University of Belgrade, Serbia in 2007 and 2008. She completing her PhD and subsequent postdoctoral research at DCU in the field of complex systems modelling and urban dynamics. Her current research projects in ADAPT are interdisciplinary and include inverse modelling methods, predictive and behavioural analytics in FinTech and InsurTech areas, as well in Educational and retail Analytics. Marija has received national and international grants from agencies such as European Union (H2020MSCA-ITN-2017), SFI/FInTech Fusion, IRC and Enterprise Ireland.
Vivek Nallur Dr. Vivek Nallur, Assistant Professor in Computer Science in the School of Computing, UCD, works on Machine Ethics and his research interests and expertise lie in computational ethics, how to implement and verify ethics in multiple autonomous machines. Questions such as what kinds of ethics would autonomous machines find consistent, how to ensure individually ethical machines don’t combine to produce un-ethical behaviour, are interesting to pose, and answer computationally. This is, by nature, an inter-disciplinary thread and Dr. Nallur is interested in collaborating with experts in the field of philosophy/law/politics etc. He is involved in the Organizing Committee for AAAI 2021 Spring Symposium Series on Implementing AI Ethics [22-24 March 2021]. He is a voting member, and serves on the IEEE P7008 Standards committee for Ethically Driven Nudging for Robotic, Intelligent and Autonomous Systems.
Matthew Nicholson Matthew is an architect working with the DLab. He was worked on a diverse range of projects from localisation/interoperability, personalisation/recommender systems, image processing, elearning. Matthew also organise MLDublin.
Goksu Yamac Goksu works under the supervision of Carol O’Sullivan and his research focuses on improving AR/VR experiences through the perceptual evaluation of human motion. He explores human motion and interactions with the virtual world to understand how more realistic and more efficient experiences can be developed for AR/VR platforms. This entails many sub-problems from developing task-specific action detection models to developing full-body motion synthesis models, and consequently evaluating these models perceptually through user studies.
Ali Karaali I have been working in Trinity College Dublin (TCD) as a research fellow for 3+ years, and conducting research on machine learning, mostly focusing on deep learning. I hold a PhD degree in computer science and have experience in various collaborative machine learning research projects as a researcher and/or co-advisor. I have had a deep enthusiasm for machine learning, whereby we train computer models using representative data to perform human-level evaluation instead of programming them explicitly for a given task. I have pursued this enthusiasm for over a decade, most often for the development of visual-related technologies, but also in other applications such as audio an/or multi model audio-visual technologies.
