As the Discipline Leader (Mathematics and Statistics) I am proud to be leading learning and teaching efforts for university mathematics because it allows me to make a meaningful impact on the education and success of our students. Mathematics is a critical subject that not only underpins many academic and professional fields, but also plays an important role in shaping the way we think and problem solve. As a leader in this area, I am committed to fostering a supportive and inclusive learning environment, where all students have the opportunity to succeed. I support student learning by providing clear and engaging instruction, developing innovative teaching strategies, and actively working to address the diverse needs and learning styles of our students. I also collaborate with other educators and academic leaders to ensure that our curriculum and resources align with the latest research and best practices in the field. Overall, I am proud to be leading the charge in providing high-quality and effective mathematics education for our students, and in fostering a culture of continuous improvement and innovation in our teaching and learning practices.
I received my PhD in Engineering (Information Systems) from the Royal Melbourne Institute of Technology University in 2009, and has been a university academic at Central Queensland University (CQU) since 2001. I am currently the Discipline Leader (Mathematics and Statistics) and have also been the STEM Leader in the School of Engineering and Technology at CQU.
In 2016 I was recognised as the CQU Educator of the Year and have also been the recipient of multiple CQU Student Voice Commendation Awards in Foundation Mathematics and Applied Calculus since 2015.
My teaching over the past 22 years has covered Bridging Mathematics, Foundation Mathematics, Applied Mathematics, Applied Calculus, Statistics, Object Oriented Programming, Software Fundamentals, Networks, Data Communications, Database Use and Design, Database Application Development, Dynamic Web Interfaces and Professional Issues in Computing.
My research interests include artificial intelligence, information systems engineering, industrial decision support systems, industrial process modelling and supervisory control systems in expert environments. I have more than 35 referred journal publications, referred conference papers, technical reports, government milestone reports, and prototyped intelligent systems, in his disciplinary areas.
As Chief Investigator leader I have secured grants, worth in excess of $700,000, in collaboration with industry partners. I am an editorial board member for the International Academy, Research and Industry Association, and reviewing for the International Journal on Advances in Intelligent Systems and the International Journal on Advances in Software. I have also been a technical program committee member for 8 major international conferences and a special session track organiser for the 37th Annual Conference of the IEEE Industrial Electronics Society.
Sugar mill process crystal clear thanks to artificial intelligence, 23 June, 2011, http://uninews.cqu.edu.au/UniNews/viewStory.do?story=8383
Recognising those who inspire our students, 08 March, 2011, http://uninews.cqu.edu.au/UniNews/viewStory.do?story=7893
Dr Roland Dodd and Dr Andrew Chiou of CQU, Professor Xinghuo Yu (RMIT) and Professor Ross Broadfoot (QUT), were granted a Sugar Research and Development Corporation research grant to be undertaken between July 2011 to December 2014. The grant supports implementation of a supervisory control system for pan and fugal stations operations in Australian sugar mills. This system is based on an intelligent industrial decision support platform and industrial process models, developed by Dr Roland Dodd during his PhD research, with the grant focusing on implementation and commercialisation aspects of this technology within the sugar mill environment.
This project aims to demonstrate the viability of the developed framework through improved sugar productivity and quality, reduction of production costs, increasing equipment utilisation and improving the decision making process undertaken by factory staff within the sugar mill crystallisation stage and fugal operational areas. Live factory trials are to demonstrate the merits of the proposed technology with expected benefits conservatively estimated at $10,000,000 per annum when implemented in Australian sugar mills.
Bachelor of Information Technology Honours (First Class), CQ University
Honours degree research led to the development of a fuzzy neural network for intelligent adaptive learning control of an inverted pendulum system. The research focused on examining outcomes for improving the learning capabilities of a fuzzy neural network system. The research proposed a modified adaptive rule importance learning algorithm based upon a fuzzy hierarchical error approach. A modified network structure that is more intuitive, powerful and melds directly into the fuzzy neural network system was developed. This system allows for fast online adaptive control while simultaneously performing system learning with the considerable feature of no offline training required. Furthermore, genetic algorithm optimisation of fuzzy rule neural network rule base and learning parameters was also undertaken.
Dodd, R. and Broadfoot, R., (2015). Milestone Report 7: Implement supervisory/advisory control of pan and fugal stations, Australian Government Sugar Research and Development Corporation, Project Number QUT038.
Dodd, R. and Broadfoot, R., (2014). Milestone Report 7: Implement supervisory/advisory control of pan and fugal stations, Australian Government Sugar Research and Development Corporation, Project Number QUT038.
Dodd, R. and Broadfoot, R., (2013). Milestone Report 6: Implement supervisory/advisory control of pan and fugal stations, Australian Government Sugar Research and Development Corporation, Project Number QUT038.
Dodd, R. and Broadfoot, R., (2012). Milestone Report 5: Implement supervisory/advisory control of pan and fugal stations, Australian Government Sugar Research and Development Corporation, Project Number QUT038.
Dodd, R. and Broadfoot, R., (2012). Milestone Report 4: Implement supervisory/advisory control of pan and fugal stations, Australian Government Sugar Research and Development Corporation, Project Number QUT038.
Dodd, R. (2011). Pan Stage Sucrose and Impurity Loadings: Macknade Sugar Mill 2006-2009 Seasons, internal report, CQUniversity.
Dodd, R. and Broadfoot, R., (2011). Milestone Report 3: Implement supervisory/advisory control of pan and fugal stations, Australian Government Sugar Research and Development Corporation, Project Number QUT038.
Dodd, R. and Broadfoot, R., (2010). Milestone Report 2: Implement supervisory/advisory control of pan and fugal stations, Australian Government Sugar Research and Development Corporation, Project Number QUT038.
I am currently accredited for supervision in the following:
At the level of Associate Supervisor
Curriculum and Pedagogy - Mathematics and Numeracy Curriculum and Pedagogy
Artificial Intelligence and Image Processing - Expert Systems
Artificial Intelligence and Image Processing - Neural, Evolutionary and Fuzzy Computation
Computer Software - Software Engineering
Information Systems - Decision Support and Group Support Systems