This is a past event.

Institute of Computing and Cybersystems, Research Talk

in conjuction with the ECE Seminar Series, Fall 2016

Title: Capture, Analysis and Interpretation of Uncertain Data

Speaker: Christian Wagner, PhD, Visiting Professor, Institute of Computing & Cybersystems

Abstract: Most, if not all information sources, whether sensors through measurement, processes through inference, or humans through their opinions, are uncertain. While uncertainty is often either ignored or modelled retrospectively, this risks information loss, potentially resulting in poorly informed decision making, in particular when multiple data sources are combined. In this talk, I will discuss the capture, aggregation and modelling of interval‐valued data with a specific focus on human sources. The talk will include a number of techniques and recent applications from crowd‐sourcing, to consumer‐driven food manufacture and environmental conservation management decision support.

Biography:  Christian Wagner’s research focuses on modeling & handling of uncertain data arising both from qualitative (people) and quantitative sources (e.g., sensors, process), decision support systems and data-driven policy design. He has published more than 80 peer-reviewed articles, including prize-winning papers in international journals and conferences, most recently having co-authored runners-up for both the best regular and best student papers at the IEEE International Conference on Fuzzy Systems 2016 in Vancouver, Canada. He has attracted around £1 million as principal and £6 million as co-investigator in the last six years. He is an Associate Editor of the IEEE Transactions on Fuzzy Systems journal and is actively involved in the academic community through for example the organization of special sessions and tutorials at premiere IEEE conference. He has developed and been involved in the creation of multiple open source software frameworks, making cutting edge research accessible both to peer researchers as well as to different research communities beyond computer science, including an R toolkit for type-2 fuzzy systems and a new Java based framework for the object oriented implementation of general type-2 fuzzy sets and systems. His current research projects focus on the development, adaptation, deployment and evaluation of artificial intelligence techniques in inter-disciplinary projects bringing together heterogeneous data from stakeholders and quantitative measurements to support informed and transparent decision making.