Richi Nayak is leader of the Applied Data Mining Research group, the HDR coordinator of Computer Science Discipline, Course-coordinator of IT81 (Doctor of IT) and an Associate Professor in the Faculty of Science and Technology at Queensland University of Technology, Brisbane, Australia.
She has made significant contributions to three areas of Data and Web Mining: (1) Semi-structured Document Mining; (2) Web Personalisation and Social Network Mining; and (3) Applied Data Mining. She has been successful in attaining over $1 million in competitive external research funding over the past five years including four CRC grants and one ARC linkage grant. She has successfully completed large-scale research projects and led research teams in those projects. She has achieved many established research outcomes that have been published and highly cited in high quality Journals and Conferences. She has published over 120 refereed papers (including 2 edited books, 10 book chapters, 15 journal articles and over 75 conference articles). Her research findings have also been cited in news media and magazine such as The Australian: IT section, The Australian: Higher Education Section, The Courier Mail and the Construction Contractor magazine. Some of her research findings have impacted the decision making process and resulted in substantial savings to industry partners (Road maintenance in the Qld Dept. of Transport and Main Roads (QDTMR) and building maintenance in the Qld Dept. of Public Works (QDPW)).
She has supervised four PhD and five Masters Research students to completion. She is currently Principal Supervisor of eight PhD, two Doctor of IT, and one Masters Research student, and Associate Supervisor of two PhD and three Masters Students. She is also supervising an academic staff member of MNIT Jaipur India enrolled in PhD program. She is unit coordinator and lecturer of the subject, “Enterprise Data Mining” that utilises a collaborative relationship with SAS (a world leader in business analytics software and services). Her teaching performance has been evaluated between ‘good’ to ‘very good’ range by students in postgraduate and undergraduate classes.
She is Editorial Board Member of the International Journal of Knowledge and Web Intelligence (InderScience), Editorial Board Member of the Book on “XML Mining: Models, Algorithms and Applications” Ideas Publications, Editorial Advisory Reviewer Board Member of the International Journal of Knowledge-Based & Intelligent Engineering Systems (KES) and Editorial Board Member of the International Journal of Data Mining, Modelling and Management. She was General Co-Chair of The Australasian Conference on Data Mining held in Gold Coast, Dec 2007. She was Program Chair of the International Workshop on Ontology Mining and Knowledge Discovery from Semi-structured Documents held in conjunction with the ICDM December 2006, Hong Kong and International Workshop on Knowledge Discovery from XML Documents, held in conjunction with the PAKDD April 2006, Singapore. She has co-chaired the 2009 and 2010 “XML Mining” Track in INEX (Initiative for Evaluation of XML Retrieval). She has presented tutorials on the topics relevant to her research area to the research community of DASFAA’09 (the 14th International Conference on Database Systems for Advanced Applications) and EDBT 2011 (the 14th International Conference on Extended Database Technology).
Education
- Ph.D. in Information Technology(2000), Queensland University of Technology , Brisbane , Australia
- Thesis: Data Mining and Machine Learning: A Methodology for rule extraction from artificial neural networks
- Masters in Electrical Engineering (1995), Indian Institute of Technology, Roorkee , India Thesis: Solving the Unit-Commitment Problem by a Hybrid Approach combining Neural Network and Simulated Annealing methods
- Bachelors in Electrical Engineering (1993), Govt Engineering College, Bilaspur, India
Thesis: Microprocessor Controlled Single Phase AC to DC Conversion
For more information, please visit Richi Nayak’s staff page.