Dr Farshid Hajati

Lecturer - School of Science and Technology

Phone: +61 +61 2 6773 1578

Biography

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 Scientific Reports (Nature) and NeurIPS 2023.

In addition to his academic achievements, Dr Hajati has extensive experience in the Australian health industry. He worked as a 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 IT subjects, leads research projects, and supervises master's and PhD students.

Qualifications

PhD (Western Sydney University)
Master of Engineering (Amirkabir University of Technology)
Bachelor of Engineering (K.N. Toosi University of Technology)

Awards

Three Teaching Excellence Awards, Victoria University, 2020-2023

Teaching Areas

Data Science
Statistical Learning
Neural Networks and Deep Learning
Programming
Database Systems
Operating Systems

Research Interests

Data Science
Machine Learning
Artificial Intelligence
Computer Vision
AI in Medicine
Digital Health

Publications

Selected publications include:

Shahadat Uddin, Arif Khan, Haohui Lu, Fangyu Zhou, Shakir Karim, Farshid Hajati, Mohammad Ali Moni, Road Networks and Socio-Demographic Factors to Explore Covid-19 Infection During its Different Waves, Scientific Reports (Nature), Volume 14, Issue 1, Pages 1-10, 2024.
Md Wahiduzzaman Khan, Hongwei Sheng, Hu Zhang, Heming Du, Sen Wang, Minas Coroneo, Farshid Hajati, Sahar Shariflou, Michael Kalloniatis, Jack Phu, Ashish Agar, Zi Huang, S.Mojtaba Golzan, Xin Yu, RVD: A Handheld Device-Based Fundus Video Dataset for Retinal Vessel Segmentation, 37th Annual Conference on Neural Information Processing Systems (NeurIPS), New Orleans, 2023.
Amirhossein Panahi, Alireza Rezaee, Farshid Hajati, Sahar Shariflou, Ashish Agar, S.Mojtaba Golzan, Autonomous Assessment of Spontaneous Retinal Venous Pulsations in Fundus Videos Using a Deep Learning Framework, Scientific Reports (Nature), Volume 13, Issue 1, 2023.
Haohui Lu, Shahadat Uddin, Farshid Hajati, Mohammad Ali Moni, Matloob Khushi, A Patient Network-Based Machine Learning Model for Disease Prediction: The Case of Type 2 Diabetes Mellitus, Applied Intelligence, Volume 52, Issue 3, Pages 2411-2422, 2022.
Farshid Hajati, Federico Girosi, Alireza Rafiei, EISI: Extended Inter-Spike Interval for Mental Health Patients Clustering Based on Mental Health Services and Medications Utilisation, Medical Engineering and Physics, Volume 110, Pages 103780, 2022.
Shahadat Uddin, Shangzhou Wang, Haohui Lu, Arif Khan, Farshid Hajati, Matloob Khushi, Comorbidity and Multimorbidity Prediction of Major Chronic Diseases Using Machine Learning and Network Analytics, Expert Systems with Applications, Volume 205, Pages 117761, 2022.
Alireza Tavakolian, Farshid Hajati, Alireza Rezaee, Amirhossein Oliaei Fasakhodi, Shahadat Uddin, Fast COVID-19 Versus H1N1 Screening Using Optimized Parallel Inception, Expert Systems with Applications, Volume 204, Pages 117551, 2022.
Alireza Rafiei, Alireza Rezaee, Farshid Hajati, Soheila Gheisari, Mojtaba Golzan, “SSP: Early Prediction of Sepsis Using Fully Connected LSTM-CNN Model”, Computers in Biology and Medicine, Volume 128, Pages 104110, 2021.
Samuele Fiorini, Farshid Hajati, Annalisa Barla, Federico Girosi, “Predicting Diabetes Second-Line Therapy Initiation in the Australian Population via Timespan-Guided Neural Attention Network”, PLOS ONE, Volume 10, Issue 14, e0211844, 2019.
Farshid Hajati, Mohammad Tavakolian, Soheila Gheisari, Yongsheng Gao, and Ajmal S. Mian, “Dynamic Texture Comparison Using Derivative Sparse Representation: Application to Video-Based Face Recognition”, IEEE Transactions on Human-Machine Systems, Volume 47, Issue 6, Pages 970-982, 2017.
Farshid Hajati, Ali Cheraghian, Soheila Gheisari, Yongsheng Gao, and Ajmal S. Mian, “Surface Geodesic Pattern for 3D Deformable Texture Matching”, Pattern Recognition, Volume 62, Pages 21-32, 2017.
Farshid Hajati, Abolghasem A. Raie, and Yongsheng Gao, “2.5D Face Recognition Using Patched Geodesic Moments”, Pattern Recognition, Volume 45, Issue 3, Pages 969-982, 2012.