Modeling and optimization of PHEV charging queues. - Hesam Akbari; Xavier N. Fernando (CCECE, 2015)

A Novel Geometrical Method for Discrimination of Normal, Interictal and Ictal EEG Signals. - Hesam Akbari; Somayeh Saraf Esmaili (Traitement du Signal, 2020)

An Automatic Scheme with Diagnostic Index for Identification of Normal and Depression EEG Signals. - Hesam Akbari; Muhammad Tariq Sadiq; Siuly Siuly; Yan Li 002; Paul Wen 001 (HIS, 2021)

Schizophrenia recognition based on the phase space dynamic of EEG signals and graphical features. - Hesam Akbari; Sedigheh Ghofrani; Pejman Zakalvand; Muhammad Tariq Sadiq (Biomed. Signal Process. Control., 2021)

A novel computer-aided diagnosis framework for EEG-based identification of neural diseases. - Muhammad Tariq Sadiq; Hesam Akbari; Siuly Siuly; Adnan Yousaf; Ateeq Ur Rehman 002 (Comput. Biol. Medicine, 2021)

Classification of normal and depressed EEG signals based on centered correntropy of rhythms in empirical wavelet transform domain. - Hesam Akbari; Muhammad Tariq Sadiq; Ateeq Ur Rehman 002 (Health Inf. Sci. Syst., 2021)

Depression Detection Based on Geometrical Features Extracted from SODP Shape of EEG Signals and Binary PSO. - Hesam Akbari; Muhammad Tariq Sadiq; Malih Payan; Somayeh Saraf Esmaili; Hourieh Baghri; Hamed Bagheri (Traitement du Signal, 2021)

Fractional Fourier Transform Aided Computerized Framework for Alcoholism Identification in EEG. - Muhammad Tariq Sadiq; Hesam Akbari; Siuly Siuly; Yan Li 002; Paul Wen 001 (HIS, 2022)

Hybrid Generalized Normal Distribution Optimization with Sine Cosine Algorithm for Global Optimization. - Jingwei Too; Ali Safaa Sadiq; Hesam Akbari; Guo Ren Mong; Seyedali Mirjalili (ICHSA, 2022)

Identification of normal and depression EEG signals in variational mode decomposition domain. - Hesam Akbari; Muhammad Tariq Sadiq; Siuly Siuly; Yan Li 002; Paul Wen 001 (Health Inf. Sci. Syst., 2022)

Early Detection of Depression and Alcoholism Disorders by EEG Signal. - Hesam Akbari; Wael Korani (ICONIP (10), 2023)

Dynamical pattern of successive bits to predict the outcomes of the SSRI and rTMS depression therapies using EEG signals. - Hesam Akbari; Wael Korani; Priyan Malarvizhi Kumar; Reza Rostami; Reza Kazemi (Comput. Biol. Medicine, 2025)