Professor Bernard Pailthorpe
CM3 - Machine Learning, Machine Vision and Computational Machines
Abstract
About CM3
CM3 is a Research Unit in Machine Learning, Machine Vision and Computational Machines. It is a research initiative of Charles Sturt University, which builds on the research strengths within CSU's School of Computing and Mathematics.
CM3 focuses on machine learning and machine vision as well as the application of these fields to real-world problems.
Research and Development Areas
The research focus of CM3 is on the core techniques of:
* Pattern analysis and data mining
* Data compression
* Image processing and computer vision
* Agent-based modelling
with application in the following areas:
* Agriculture & Environment
* Health
* Industry and Mining
* Security, including Information and Communications Technology (ICT) security.
Presentation
CM3 - Machine Learning, Machine Vision and Computational Machines (pdf - 830 kB)
Biography
Bernard Pailthorpe is Head, CM3: Machine Learning Research Unit and is a Professor in the School of Computing and Mathematics at CSU, described above.
He was Professor of Computational Science at UQ, Director of UQ Vislab and CEO of Queensland. Cyberinfrastructure (QCIF Ltd). He built up advanced computing research infrastructure over nearly two decades. In 1992 he established Sydney VisLab as a component of the national advanced computing infrastructure, with one of the first labs at the ATP in 1995. He was a member of the team that presented to PMSEC in Dec'94, leading to the establishment of APAC.
During 1999-2000 he was a Director of the San Diego Supercomputer Center at UCSD. There he directed the Interaction Environments research program for the 50-member NSF-funded NPACI consortium. He also was involved in the early planning of CalIT2 with which he has continued collaborations, in particular with its OptIPortal development program.
He has been CEO of the Queensland's advanced computing partnership during which time funding was provided for construction of OptIPortals and associated infrastructure at UQ and the QUT.