Prof. Abbas Khosravi 

Department of Information Technology 

Deakin University, Australia 

Email: abbas.khosravi@deakin.edu.au 

Qualifications 

2010 Ph.D., Deakin University, Australia, Information Technology (machine learning and artificial intelligence) 

2005 M.A., Amirkabir University of Technology, Iran, Electrical Engineering (artificial intelligence control) 

2002 B.A., Sharif University of Technology, Iran, Electrical Engineering (control) 

Publications (Selected) 

1. D. Nahavandi, R. Alizadehsani, A. Khosravi, and U. R. Acharya, “Application of artificial intelligence in wearable devices: Opportunities and challenges,” Computer Methods and Programs in Biomedicine, vol. 213, 2022. 
2. M. Abdar, F. Pourpanah, S. Hussain, D. Rezazadegan, L. Liu, M. Ghavamzadeh, P. Fieguth, X. Cao, A. Khosravi, U. R. Acharya, V. Makarenkov, and S. Nahavandi, “A review of uncertainty quantification in deep learning: Techniques, applications and challenges,” Information Fusion, vol. 76, pp. 243-297, 2021. 
3. M. Abdar, M. Samami, S. Dehghani Mahmoodabad, T. Doan, B. Mazoure, R. Hashemifesharaki, L. Liu, A. Khosravi, U. R. Acharya, V. Makarenkov, and S. Nahavandi, “Uncertainty quantification in skin cancer classification using three-way decision-based Bayesian deep learning,” Computers in Biology and Medicine, vol. 135, 2021. 
4. S. Ahmadian, S. M. J. Jalali, S. M. S. Islam, A. Khosravi, E. Fazli, and S. Nahavandi, “A novel deep neuroevolution-based image classification method to diagnose coronavirus disease (COVID-19),” Computers in Biology and Medicine, vol. 139, 2021. 
5. M. Akbari, H. M. D. Kabir, A. Khosravi, and F. Nasirzadeh, “ANN-Based LUBE Model for Interval Prediction of Compressive Strength of Concrete,” Iranian Journal of Science and Technology - Transactions of Civil Engineering, 2021. 
6. A. Shoeibi, M. Khodatars, N. Ghassemi, M. Jafari, P. Moridian, R. Alizadehsani, M. Panahiazar, F. Khozeimeh, A. Zare, H. Hosseini-Nejad, A. Khosravi, A. F. Atiya, D. Aminshahidi, S. Hussain, M. Rouhani, S. Nahavandi, and U. R. Acharya, “Epileptic seizures detection using deep learning techniques: A review,” International Journal of Environmental Research and Public Health, vol. 18, no. 11, 2021. 
7. R. Alizadehsani, Z. Alizadeh Sani, M. Behjati, Z. Roshanzamir, S. Hussain, N. Abedini, F. Hasanzadeh, A. Khosravi, A. Shoeibi, M. Roshanzamir, P. Moradnejad, S. Nahavandi, F. Khozeimeh, A. Zare, M. Panahiazar, U. R. Acharya, and S. M. S. Islam, “Risk factors prediction, clinical outcomes, and mortality in COVID-19 patients,” Journal of Medical Virology, vol. 93, no. 4, pp. 2307-2320, 2021. 
8. A. Shoeibi, N. Ghassemi, R. Alizadehsani, M. Rouhani, H. Hosseini-Nejad, A. Khosravi, M. Panahiazar, and S. Nahavandi, “A comprehensive comparison of handcrafted features and convolutional autoencoders for epileptic seizures detection in EEG signals,” Expert Systems with Applications, vol. 163, 2021. 
9. R. Alizadehsani, A. Khosravi, M. Roshanzamir, M. Abdar, N. Sarrafzadegan, D. Shafie, F. Khozeimeh, A. Shoeibi, S. Nahavandi, M. Panahiazar, A. Bishara, R. E. Beygui, R. Puri, S. Kapadia, R. S. Tan, and U. R. Acharya, “Coronary artery disease detection using artificial intelligence techniques: A survey of trends, geographical differences and diagnostic features 1991–2020,” Computers in Biology and Medicine, vol. 128, 2021. 
10. S. M. S. Islam, S. Ahmed, R. Uddin, M. U. Siddiqui, M. Malekahmadi, A. Al Mamun, R. Alizadehsani, A. Khosravi, and S. Nahavandi, “Cardiovascular diseases risk prediction in patients with diabetes: Posthoc analysis from a matched case-control study in Bangladesh,” Journal of Diabetes and Metabolic Disorders, vol. 20, no. 1, pp. 417-425, 2021. 
11. S. M. J. Jalali, S. Ahmadian, A. Khosravi, M. Shafie-khah, S. Nahavandi, and J. P. S. Catalao, “A Novel Evolutionary-based Deep Convolutional Neural Network Model for Intelligent Load Forecasting,” IEEE Transactions on Industrial Informatics, 2021. 
12. S. M. S. Islam, and A. Khosravi, “The need for a prediction model assessment framework,” The Lancet Global Health, vol. 9, no. 4, pp. e404, 2021. 
13. R. Alizadehsani, M. Roshanzamir, S. Hussain, A. Khosravi, A. Koohestani, M. H. Zangooei, M. Abdar, A. Beykikhoshk, A. Shoeibi, A. Zare, M. Panahiazar, S. Nahavandi, D. Srinivasan, A. F. Atiya, and U. R. Acharya, “Handling of uncertainty in medical data using machine learning and probability theory techniques: a review of 30 years (1991–2020),” Annals of Operations Research, 2021. 
14. D. Sharifrazi, R. Alizadehsani, M. Roshanzamir, J. H. Joloudari, A. Shoeibi, M. Jafari, S. Hussain, Z. A. Sani, F. Hasanzadeh, F. Khozeimeh, A. Khosravi, S. Nahavandi, M. Panahiazar, A. Zare, S. M. S. Islam, and U. R. Acharya, “Fusion of convolution neural network, support vector machine and Sobel filter for accurate detection of COVID-19 patients using X-ray images,” Biomedical Signal Processing and Control, vol. 68, 2021. 
15. A. Shamsi, H. Asgharnezhad, S. S. Jokandan, A. Khosravi, P. M. Kebria, D. Nahavandi, S. Nahavandi, and D. Srinivasan, “An uncertainty-aware transfer learning-based framework for covid-19 diagnosis,” IEEE Transactions on Neural Networks and Learning Systems, vol. 32, no. 4, pp. 1408-1417, 2021. 
16. S. M. J. Jalali, M. Ahmadian, S. Ahmadian, A. Khosravi, M. Alazab, and S. Nahavandi, “An oppositional-Cauchy based GSK evolutionary algorithm with a novel deep ensemble reinforcement learning strategy for COVID-19 diagnosis,” Applied Soft Computing, vol. 111, 2021. 
17. S. M. J. Jalali, S. Ahmadian, A. Kavousi-Fard, A. Khosravi, and S. Nahavandi, “Automated Deep CNN-LSTM Architecture Design for Solar Irradiance Forecasting,” IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2021. 
18. Z. Senousy, M. Abdelsamea, M. M. Gaber, M. Abdar, R. U. Acharya, A. Khosravi, and S. Nahavandi, “MCUa: Multi-level Context and Uncertainty aware Dynamic Deep Ensemble for Breast Cancer Histology Image Classification,” IEEE Transactions on Biomedical Engineering, 2021. 
19. M. Mir, H. M. D. Kabir, F. Nasirzadeh, and A. Khosravi, “Neural network-based interval forecasting of construction material prices,” Journal of Building Engineering, vol. 39, 2021. 
20. P. Arora, A. Khosravi, B. K. Panigrahi, and P. N. Suganthan, “Remodelling State-Space Prediction With Deep Neural Networks for Probabilistic Load Forecasting,” IEEE Transactions on Emerging Topics in Computational Intelligence, 2021.