Dr. Sangeetha Kutty is a transdisciplinary academic at the School of Engineering and Technology in CQUniversity, specialising in data science. She is passionate about integrating industries, teaching, and research in data science to deliver impactful solutions benefiting both regional and metropolitan Australian communities. Her research interests encompass Data Science, AI/Machine Learning, Text mining, Social Media mining, Deep Learning, Generative AI, Recommendation Systems and Information Retrieval.
Dr. Kutty holds a PhD from Queensland University of Technology (QUT) and a Master's degree from Auckland University of Technology (AUT). Her expertise has made significant contributions to transdisciplinary research projects for various industry partners, including the Future Energy Export Cooperative Research Centre (FEnEx-CRC), Department of Resources (DoR), AgriFutures, Cotton Research and Development Corporation(CRDC) and the National Library of Australia (NLA). Previous positions include working as Software Engineer and Networking Engineer in Singapore and India.
Dr. Kutty is affiliated with professional organisations such as IEEE and ACS and has served as an IEEE Student Branch counselor at CQUniversity’s Brisbane campus. She is a certified professional of the Australian Computer Society and a Microsoft Certified Systems Engineer. Furthermore, she co-founded and serves as Vice-President of CQUni's WinTech (Women in Technology) STEM+C Club, organising industry seminars and meet-and-greet sessions for students. Recognised for her teaching, she was honoured with CQUniversity's Student Voice Award for 2021 and received several commendations. She has also received nominations for excellence awards in teaching, research, and service contributions.
Dr Sangeetha Kutty possesses a good track record in delivering top-tier education in ICT and research, consistently providing exceptional learning experiences for students and making significant contributions in research, resulting in several accolades. Her expertise extends to continuously enhancing curriculum quality, content development, and refining unit profiles and assessments. Notably, she uses innovative techniques in teaching and assessment. Alongside these responsibilities, she manages the delivery of lectures and tutorials to over 200 students across multiple campuses.
Furthermore, she actively engages in assessment marking and offers valuable mentoring for both undergraduate and postgraduate courses. Her dedication significantly contributes to fostering a positive academic environment, ensuring high levels of engagement and performance standards in learning and teaching.
Demonstrating effective communication skills, she shares research outcomes with audiences of varying expertise levels, catering to both experts and the general public. Notably, her publications predominantly feature in high-quality journals, conferences, and workshops.
PhD Queensland University of Technology (QUT)
MCIS Auckland University of Technology (AUT)
BE Madras University (MU)
Postdoctoral Research Fellow, Faculty of Science, Queensland University of Technology (QUT) - Mar 2016 - May 2023, Sept- Oct 2023
Research Associate, Faculty of Science, Queensland University of Technology (QUT) - Mar 2021- May 2021
Senior Research Assistant, Faculty of Science, Queensland University of Technology (QUT) - 2012- May 2013
Unit Co-ordinator, Lecturer and Tutor, Faculty of Science, Queensland University of Technology (QUT) - 2008-2010, Jun 2018 - Dec 2021
Research Assistant - Auckland University of Technology (AUT) - 2004
Women Empowering Women in Tech
Congratulations to our 2021 Student Voice Awards and Commendations recipients (cqu.edu.au)
Sessional Academic (Unit Coordinator, Lecturer and Tutor) - Mar 2009 - Oct 2023
School of Engineering & Technology, College of ICT, Central Queensland University
Unit Coordinator, Lecturer, Tutor (Casual) - June 2018 - Dec 2021
School of Engineering & Technology, Queensland University of Technology
Tableau, Power BI, MySQL, MongoDB, SAS, Weka
I am currently accredited for supervision in the following:
Education Systems - Education Systems not elsewhere classified
Education Technology and Computing
Artificial Intelligence and Image Processing - Natural Language Processing
Artificial Intelligence and Image Processing - Pattern Recognition and Data Mining
Computer Software - Programming Languages
Information Systems - Information systems organisation and management
Socio-technical aspects
Machine learning - Deep learning
Machine learning - Machine learning not elsewhere classified