BUILTINCORK: The Future of Artificial Intelligence

In this month's BUILTINCORK we will hear from 3 panellists who are at the forefront of Artificial Intelligence in Ireland. The rise of Artificial Intelligence in every day life means we are never truly switched off.

BUILTINCORK and Getvisability bring you a panel of 3 AI specialists.

If you are intrigued by the future of Artificial Intelligence or how you can use Artificial Intelligence in your day to day work life join us on the 13th of November in REPUBLIC OF WORK where we will welcome audience participation to this conversation.

Our panel...

Keelin Murphy

Radboud University Medical Center, Nijmegen, The Netherlands

Keelin has worked for more than a decade in the field of machine-learning and artificial intelligence for medical image and signal analysis. She obtained her PhD in 2011 on the automated analysis of chest CT and worked for a number of years on analysis of neonatal brain MRI and EEG at University College Cork. She is currently working remotely for Radboud University in the Netherlands on deep learning for the analysis of chest x-ray images.

Derek Coetzee

Getvisibility

Derek is an experienced Chief Technology Officer with a demonstrated track record of delivering very complex and disruptive platforms across multiple industries. Skilled in Innovation Management, AI and Machine Learning-based solutions, Cloud Architecture and Distributed Systems, Pre-Sales, Cost Management and Start-ups. A strong, curious, business-savvy IT professional with a broad range of experience from Operations to Development to Research. Derek has managed distributed development teams and built enterprise software solutions for 18 years.

Alison O’Shea

PhD Candidate, INFANT (the Irish Centre for Maternal and Child Health Research)

Alison's research uses deep learning to detect neonatal seizures in EEG signals recorded at the cotside. INFANT has already achieved a major scientific breakthrough by developing an AI powered neonatal seizure detection algorithm. Alison’s work focuses on exploring application-specific deep learning algorithms to further improve the accuracy of neonatal seizure detection.