Personal profile

Research Interests

His current research interests are in the areas of Computer Vision and Artificial Intelligence, with applications in automotive, consumer and environmental spaces

Teaching Interests

Dr. Scanlan currently teaches several modules on the University of Limerick Artificial Intelligence programmes. This includes CE6021 Machine Vision and; Image processing on the full time MSc in Artificial Intelligence, CE6003 Machine Vision on the online MSc in Artificial Intelligence and CE5021 Deep Learning for Computer Vision on the Professional Diploma in Artificial Intelligence for Computer Vision.

Biography

Dr. Scanlan is a Senior Research Fellow in the Department of Electronic and; Computer Engineering and member of the Data Driven Computer Engineering (D2iCE)andnbsp;research group. His current research interests are in the areas of Computer Vision and Artificial Intelligence, with applications in automotive, consumer and environmental spaces.andnbsp;He graduated with a BSc in Experimental Physics from N.U.I. Galway in 1998.andnbsp;From 1998 to 2002 he worked as a Design Engineer in the video product Group at Analog Devices Limerick. From 2002 to 2005 he completed his PhD at the Circuits and Systems Research Centre (CSRC) at the University of Limerick. The focus of this research was design automation techniques for pipelined Analog to Digital Converters. His previous research has included data converter design, signal processing and electronic circuit modelling.

Expertise related to UN Sustainable Development Goals

In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This person’s work contributes towards the following SDG(s):

  • SDG 3 - Good Health and Well-being
  • SDG 9 - Industry, Innovation, and Infrastructure
  • SDG 11 - Sustainable Cities and Communities
  • SDG 12 - Responsible Consumption and Production

Fingerprint

Dive into the research topics where Tony Scanlan is active. These topic labels come from the works of this person. Together they form a unique fingerprint.
  • 1 Similar Profiles

Collaborations and top research areas from the last five years

Recent external collaboration on country/territory level. Dive into details by clicking on the dots or