Dr Roland Dodd received his PhD in Information Systems Engineering from the Royal Melbourne Institute of Technology University in 2009. He has been a university academic at Central Queensland University (CQU) from 2001 to present. He is currently the Discipline Leader for Mathematics and Statistics and a Senior Lecturer in the School of Engineering and Technology at CQU.

His teaching over the past 17 years has covered Mathematics, Statistics, Data Communications, Networks, Database Use and Design, Database Application Development, Object Oriented Programming, Software Fundamentals, Dynamic Web Interfaces and Professional Issues in Computing. He has been the recipient of the multiple awards for excellence in learning and teaching, including recognition as the 2016 CQU Educator of the Year for his teaching in first year undergraduate mathematics.

His research interests include artificial intelligence, information systems engineering, industrial decision support systems, industrial process modelling and supervisory control systems in expert environments. He has more than 35 journal publications, conference papers, technical reports, thesis, government milestone reports, research presentations and prototyped intelligent systems, in his disciplinary areas.

As Chief Investigator leader he has secured grants, worth in excess of $700,000, in collaboration with industry partners. He is an editorial board member for the International Academy, Research and Industry Association International Journal on Advances in Intelligent Systems and the International Journal on Advances in Software. He was also a technical program committee member for 8 major international conferences and a special session track organiser for 37th Annual Conference of the IEEE Industrial Electronics Society.

Awards, Honours and Prestige

• CQUniversity, Educator of the Year (2017) - Commendation;
• CQUniversity, On-campus Educator of the Year (2017) - Commendation
• CQUniversity, Educator of the Year (2016) - Winner
• CQUniversity, Distance Educator of the Year (2015) - Commendation;
• CQUniversity, Vice-Chancellors Award for Emerging Researchers - Joint Nominee (2011);
• CQUniversity, Vice-Chancellors Award for Excellence in Learning and Teaching – Nominee (2010);
• CQUniversity, Faculty Award for Excellence in Learning and Teaching (2010);
• CQUniversity, Directors Award for Excellence in Learning and Teaching (2010);
• Australian Government, Young Tall Poppy Nominee (2010);
• CQUniversity, OPALS Engagement Award (Research and Innovation) - Joint Nominee (2010);
• Australia Government, Australian Postgraduate Award for Industry (APAI);
• CQUniversity, Faculty of Informatics and Communications Honours Degree Scholarship;
• CQUniversity, Faculty of Informatics and Communications Vacational Research Scholarship;
• Commonwealth Government, Merit Based Equity Scholarship;
• North Rockhampton State High School, Runner Up Dux; and
• The Caves State School, Dux.

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

Education

• PhD (Information Systems Engineering), RMIT University, July 2009. Doctoral Dissertation: "A Knowledge Based Supervisory Support System for Pan Stage Operations in a Sugar Mill", which was commended as "strongly competitive at international levels".
• Bachelor of Information Technology Honours (First Class), CQUniversity, November 2007. Honours Dissertation: "Improving the Learning Capacity of Fuzzy Neural Networks", which was commended as "excellent".
• Bachelor of Information Technology (Software Engineering), CQUniversity, June 2001.

Academic and Research Employment History

• Discipline Leader - Mathematics and Statistics, School of Engineering and Technology, CQUniversity. March 2016 - present.
• Senior Lecturer, School of Engineering and Technology, CQUniversity. October 2013 to present.
• Senior Lecturer, Academic Learning Services, CQUniversity. January 2013 - October 2013.
• Lecturer, Academic Learning Services, CQUniversity. January 2010 - December 2012.
• Associate Lecturer, Academic Learning Services, CQUniversity. February 2009 - December 2009.
• Casual Academic, CQUniversity. March 2001 - November 2007.

Professional Service

• Editorial Board Member, International Academy, Research and Industry Association (IARIA), International Journal on Advances in Intelligent Systems.
• Editorial Board Member, International Academy, Research and Industry Association (IARIA), International Journal on Advances in Software.
• Member, Technical Program Committee, UBICOMM 2012, The Sixth International Conference on Mobile Ubiquitous Computing, Systems, Services and Technologies Technology, 23^rd - 28^th September 2012, Barcelona, Spain.
• Member, Technical Program Committee, UBICOMM 2011, The Fifth International Conference on Mobile Ubiquitous Computing, Systems, Services and Technologies Technology, 20^th - 25^th November 2011, Lisbon, Portugal.
• Special Session Organiser, 37th Annual Conference of the IEEE Industrial Electronics Society 7^th - 10^th November 2011, Melbourne, Victoria, Australia.
• Invited Session Chair, 37th Annual Conference of the IEEE Industrial Electronics Society 7^th - 10^th November 2011, Melbourne, Victoria, Australia.
• Member, Technical Program Committee, 37th Annual Conference of the IEEE Industrial Electronics Society 7^th - 10^th November 2011, Melbourne, Victoria, Australia.
• Member, Technical Program Committee, Computation Tools 2011, The Second International Conference on Computational Logics, Algebras, Programming, Tools, and Benchmarking, 25^th - 30^th September 2011, Rome, Italy.
• Member, Technical Program Committee, 23rd Australasian Joint Conference on Artificial Intelligence: AI 2010, 7^th - 10^th December 2010, Adelaide, South Australia, Australia.
• Member, Technical Program Committee, 22nd Australasian Joint Conference on Artificial Intelligence, 1^st - 4^th December 2009, Melbourne, Victoria, Australia.
• Member, Technical Program Committee, 35th Annual Conference of the IEEE Industrial Electronics Society, 3rd - 5th November 2009, Porto, Portugal.
• Member, Technical Program Committee, International Workshop on Intelligent Decision Support Systems and Applications in Networked and Distributed Systems 2009, 19^th - 21^st October 2009, Gold Coast, Queensland, Australia.
• Invited Session Chair, International Workshop on Intelligent Decision Support Systems and Applications in Networked and Distributed Systems 2009, 19th - 21st October 2009, Gold Coast, Queensland, Australia. 

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.

PhD (Information Systems Engineering), RMIT University

PhD research led to the development of a prototype knowledge based supervisory support system (KBSSS) for pan stage operations in a sugar mill to demonstrate proof of concept. To demonstrate the viability of the proposed KBSSS framework a prototype system was developed in accordance with the proposed framework. As a result of research and development carried, the KBSSS's test results demonstrated the viability of the proposed KBSSS framework and highlight the forecasting capabilities of the system resulting in favourable outcomes compared to data from pan stage operations. As a result of the research undertaken a prototype KBSSS, for pan stage operations, based upon the three core supporting intelligent system technologies, supporting the overall industrial control system framework, was developed.

Sugar Research and Development Corporation, National Competitive Research Grant

This research project aims to implement a knowledge based supervisory support system (KBSSS) for pan and fugal station operations and to demonstrate and evaluate its effectiveness and acceptability by factory operators, supervisors and management.  The pan and fugal stations are considered to be an ideal location in the factory to initiate progress towards a factory wide supervisory/advisory system. This software development is based upon extension of PhD research prototyping.

The KBSSS will provide advice to supervisors and operators so that early decisions, such as changes to steam rates or allocation of pans to different duties, result in improved outcomes with respect to avoiding production rate difficulties, and maintaining good operational performance with respect to sugar quality, sugar recovery and minimisation and smoothing of steam consumption on the pan stage.

Industry implementation is being undertaken at Macknade sugar mill located in Ingham QLD with the support of Sucrogen industry partner.

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.