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Abbas Khosravi

Abbas Khosravi

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Computer Science
Australia
2025

D-Index & Metrics

Computer Science

D-Index
77
Citations
21102
World Ranking
1290
National Ranking
35

Research.com Recognitions

  • 2025 - Research.com Computer Science in Australia Leader Award
  • 2022 - Research.com Computer Science in Australia Leader Award

Overview

Abbas Khosravi is a researcher affiliated with Deakin University in Australia with significant contributions in the fields of computer science, medicine, and engineering. Their scholarly output spans a diverse range of topics, particularly focusing on artificial intelligence, computer vision and pattern recognition, radiology and nuclear medicine imaging, cognitive neuroscience, and biomedical engineering.

The researcher has been involved in investigations on a number of main topics including COVID-19 diagnosis using AI, anomaly detection techniques and applications, energy load and power forecasting, EEG and brain-computer interfaces, AI in cancer detection, adversarial robustness in machine learning, and machine learning in healthcare.

Some of the recent publications by Abbas Khosravi include the following papers:

  • "A review of uncertainty quantification in deep learning: Techniques, applications and challenges" (2021), published in Information Fusion
  • "Epileptic Seizures Detection Using Deep Learning Techniques: A Review" (2021), published in International Journal of Environmental Research and Public Health
  • "Application of artificial intelligence in wearable devices: Opportunities and challenges" (2021), published in Computer Methods and Programs in Biomedicine
  • "Deep Learning for Neuroimaging-based Diagnosis and Rehabilitation of Autism Spectrum Disorder: A Review" (2020), published in arXiv (Cornell University)
  • "Uncertainty quantification in skin cancer classification using three-way decision-based Bayesian deep learning" (2021), published in Computers in Biology and Medicine

Frequent co-authors working alongside Abbas Khosravi include:

  • Saeid Nahavandi
  • Roohallah Alizadehsani
  • U. Rajendra Acharya
  • Afshin Shoeibi
  • Moloud Abdar

The researcher often publishes in venues such as:

  • arXiv (Cornell University)
  • Computers in Biology and Medicine
  • SSRN Electronic Journal
  • Information Fusion
  • IEEE Systems Man and Cybernetics Magazine

Abbas Khosravi's work covers extensive interdisciplinary applications of artificial intelligence and machine learning, with a focus on healthcare and biomedical engineering. Their research addresses challenges across diagnostic imaging, EEG-based brain-computer interfaces, and AI-driven disease detection systems.

Best Publications

  • A Review of Uncertainty Quantification in Deep Learning: Techniques, Applications and Challenges

    Moloud Abdar;Farhad Pourpanah;Sadiq Hussain;Dana Rezazadegan

  • A review on artificial intelligence based load demand forecasting techniques for smart grid and buildings

    Muhammad Qamar Raza;Muhammad Qamar Raza;Abbas Khosravi

  • Lower Upper Bound Estimation Method for Construction of Neural Network-Based Prediction Intervals

    A Khosravi;S Nahavandi;D Creighton;A F Atiya

  • Comprehensive Review of Neural Network-Based Prediction Intervals and New Advances

    A. Khosravi;S. Nahavandi;D. Creighton;A. F. Atiya

  • Short-Term Load and Wind Power Forecasting Using Neural Network-Based Prediction Intervals

    Hao Quan;Dipti Srinivasan;Abbas Khosravi

  • Epileptic Seizures Detection Using Deep Learning Techniques: A Review.

    Afshin Shoeibi;Marjane Khodatars;Navid Ghassemi;Navid Ghassemi;Mahboobeh Jafari

  • Application of artificial intelligence in wearable devices: Opportunities and challenges.

    Darius Nahavandi;Roohallah Alizadehsani;Abbas Khosravi;U Rajendra Acharya

  • Prediction Intervals for Short-Term Wind Farm Power Generation Forecasts

    A. Khosravi;S. Nahavandi;D. Creighton

  • Construction of Optimal Prediction Intervals for Load Forecasting Problems

    Abbas Khosravi;Saeid Nahavandi;Doug Creighton

  • Machine learning-based coronary artery disease diagnosis: A comprehensive review.

    Roohallah Alizadehsani;Moloud Abdar;Mohamad Roshanzamir;Abbas Khosravi

  • Neural Network-Based Uncertainty Quantification: A Survey of Methodologies and Applications

    H. M. Dipu Kabir;Abbas Khosravi;Mohammad Anwar Hosen;Saeid Nahavandi

  • A New Fuzzy-Based Combined Prediction Interval for Wind Power Forecasting

    Abdollah Kavousi-Fard;Abbas Khosravi;Saeid Nahavandi

  • Deep learning for neuroimaging-based diagnosis and rehabilitation of Autism Spectrum Disorder: A review.

    Marjane Khodatars;Afshin Shoeibi;Afshin Shoeibi;Delaram Sadeghi;Navid Ghaasemi

  • Uncertainty quantification in skin cancer classification using three-way decision-based Bayesian deep learning

    Moloud Abdar;Maryam Samami;Sajjad Dehghani Mahmoodabad;Thang Doan

  • Interval Type-2 Fuzzy Logic Systems for Load Forecasting: A Comparative Study

    A. Khosravi;S. Nahavandi;D. Creighton;D. Srinivasan

  • Prediction Intervals to Account for Uncertainties in Travel Time Prediction

    A Khosravi;E Mazloumi;S Nahavandi;D Creighton

  • A computational framework for uncertainty integration in stochastic unit commitment with intermittent renewable energy sources

    Hao Quan;Dipti Srinivasan;Ashwin M. Khambadkone;Abbas Khosravi

  • An expert system for selecting wart treatment method

    Fahime Khozeimeh;Roohallah Alizadehsani;Mohamad Roshanzamir;Abbas Khosravi

  • A Novel Evolutionary-Based Deep Convolutional Neural Network Model for Intelligent Load Forecasting

    Seyed Mohammad Jafar Jalali;Sajad Ahmadian;Abbas Khosravi;Miadreza Shafie-khah

  • An intelligent driven deep residual learning framework for brain tumor classification using MRI images

    Unknown

  • Automated Detection and Forecasting of COVID-19 using Deep Learning Techniques: A Review

    Afshin Shoeibi;Marjane Khodatars;Roohallah Alizadehsani;Navid Ghassemi

  • Prediction Interval Estimation of Electricity Prices Using PSO-Tuned Support Vector Machines

    Nitin Anand Shrivastava;Abbas Khosravi;Bijaya Ketan Panigrahi

  • Deep Learning for Neuroimaging-based Diagnosis and Rehabilitation of Autism Spectrum Disorder: A Review

    Marjane Khodatars;Afshin Shoeibi;Navid Ghassemi;Mahboobeh Jafari

Frequent Co-Authors

Saeid Nahavandi
Saeid Nahavandi Swinburne University of Technology
U. Rajendra Acharya
U. Rajendra Acharya University of Southern Queensland
Roohallah Alizadehsani
Roohallah Alizadehsani Deakin University
Dipti Srinivasan
Dipti Srinivasan National University of Singapore
Moloud Abdar
Moloud Abdar Deakin University
Chee Peng Lim
Chee Peng Lim Swinburne University of Technology
Abdollah Kavousi-Fard
Abdollah Kavousi-Fard Shiraz University of Technology
Amir F. Atiya
Amir F. Atiya Cairo University
Houshyar Asadi
Houshyar Asadi Deakin University
Dongrui Wu
Dongrui Wu Huazhong University of Science and Technology

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