Farshid Hajati

Dr Farshid Hajati is a Lecturer in Data Science at the School of Science and Technology, University of New England. He has accumulated a wealth of teaching and research experience at multiple Australian universities and organisations.Before joining UNE, Dr Hajati was a Senior Lecturer and Course Coordinator at Victoria University, Sydney. During his tenure, Dr Hajati managed the Master of Applied Information Technology and the Bachelor of Cybersecurity courses. He also taught AI and Machine Learning subjects at Victoria University, earning three teaching excellence awards due to the high quality of teaching and outstanding student feedback.Also, Dr Hajati was a researcher at the Institute for Integrated and Intelligent Systems (IIIS), Griffith University, where he researched computer vision and image processing methods for biometric systems such as 2D and 3D face recognition. He published in A* journals and conference proceedings, including the journal of Pattern Recognition (Elsevier), while collaborating with Griffith University.Dr Hajati has also been an honorary research fellow at the Graduate School of Health, University of Technology Sydney, developing innovative deep-learning models for the early detection of ocular diseases. The results of this collaboration have been published in leading journals and conferences, including NeurIPS 2023.In addition to his academic achievements, Dr Hajati has extensive experience in the Australian health industry. He worked as a Senior Data Scientist at the Australian Institute of Health and Welfare (AIHW) and the Australian Government Department of Health and Aged Care, applying machine learning models to analyse national health datasets, including Medicare Benefits Schedule (MBS), Pharmaceutical Benefits Scheme (PBS), National Disability Insurance Scheme (NDIS), and aged care services.In his current role at UNE, Dr Hajati teaches various Computer Science and Statistics subjects, leads research projects, and supervises master's and PhD students.

COSC102 - Data Science Studio 1

STAT330/430 - Statistical Learning

COSC240 -  Operating Systems

ICT100 -  Computational Thinking