Supervisor Database Search
Guidance for ICAT Supervisors
The ICAT Supervisor list is reviewed annually by the partner universities and updated online in March/April each year.
You can read about the ICAT supervisor selection process and eligibility criteria below:
Terms of reference/guide to supervising ICAT Fellows.
You can read the terms of reference for supervisors actively supervising ICAT Fellows below:
Supervisor Database
Search for supervisors below. You can filter your search using the options and select multiple fields by holding CTRL (Cmd on Mac) + clicking multiple options in a list.
Full NameDr Brian Mac Namee
- artificial intelligence/machine learning/data analytics
- Radiology
Dr. Brian Mac Namee received a BA (mod) and PhD in Computer Science from Trinity College Dublin in 2000 and 2004 respectively. In 2015 Brian joined the UCD School of Computer Science as a lecturer. At UCD Brian is the Centre Director for the SFI Centre for Research Training in Machine Learning (http://www.ml-labs.ie) and a Funded Investigator at the Insight (http://www.insight-centre.org) and VistaMilk (https://vistamilk.ie/) SFI research centres. Previously Brian was a founding Principal Investigator at the CeADAR centre (www.ceadar.ie) and a Funded Investigator at the Insight centre .
Brian's research focuses on machine learning, predictive analytics, data visualisation, and augmented reality. Brian has published extensively in machine learning, predictive analytics, and information visualisation - a recent highlight is the textbook "Fundamentals of Machine Learning for Predictive Data Analytics: Algorithms, Worked Examples and Case Studies" published with MIT Press in 2015 (www.machinelearningbook.com).
Prior to joining UCD Brian worked in industry as an R & D software engineer for Agilent Technologies, and at the School of Computing at Dublin Institute of Technology as a lecturer where he co-founded the Applied Intelligence Researcher Centre (http://www.ditairc.ie), and developed DIT's successful MSc in Computing (Data Analytics) programme.
I would be interested in collaborating with clinicians to bring machine learning techniques to bear on clinical challenges. In particular I am interested in interactive machine learning techniques.