Faculty profile

Gary Marcel Hasey

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Associate Professor (Part-Time)Psychiatry & Behavioural NeurosciencesMcMaster University

Gary Marcel Hasey

Associate Professor (Part-Time)

Psychiatry & Behavioural Neurosciences

Faculty of Health Sciences

McMaster University

Hamilton, Ontario, Canada

In this role since 2025

Supervision signals

Adjunct, part-time and visiting faculty usually co-supervise alongside a core faculty member.
No graduate courses on record.
11 publications in the last five years, latest in 2026.
Senior (last) author on 6 recent papers, a sign of leading a research group.

These signals come from public records. Ask the professor or the graduate program whether they are taking new students.

Academic metrics

Publications

1,467

Citations

h-index

Collaborators

Publications by year

Counts cover the works listed on the university profile; citation counts come from Dimensions.

Academic profiles

University Profile Search on Google Scholar OpenAlex

Social profiles

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Contact

haseyg@mcmaster.ca (905) 388-2511 ext. 4944

Research

Research areas, by share of publications

EEG and Brain-Computer InterfacesNeuroscience
Functional Brain Connectivity StudiesNeuroscience
Transcranial Magnetic Stimulation StudiesNeuroscience
Bipolar Disorder and TreatmentMedicine
Electroconvulsive Therapy StudiesMedicine

Research areas are derived from OpenAlex topics of their publications.

75 publications.

Evaluation of Short Term and Long Term Subjective and Objective Cognitive Outcomes Following ECT for Depression in a Naturalistic Ambulatory Setting: A Cohort Study

Goegan SA, Hasey GM, King JP, Losier BJ, Bieling PJ, McKinnon MC, McNeely HE

Anadolu Psikiyatri Dergisi20261 citations

DOI: 10.31083/ap45286

One Hundred Years Later! The Current Utility of EEG Tools in Psychiatry: Some Insights and Perspectives

Campanella S, Coffman B, Hasey G, Ingels A, Lepock J, Nicklas P, Popov V, Fisher D

Clinical EEG and Neuroscience2026

DOI: 10.1177/15500594251399705

Diagnostic deep learning algorithms that use resting EEG to distinguish major depressive disorder, bipolar disorder, and schizophrenia from each other and from healthy volunteers

Ravan M, Noroozi A, Sanchez MM, Borden L, Alam N, Flor-Henry P, Colic S, Khodayari-Rostamabad A, Minuzzi L, Hasey G

Journal of Affective Disorders202425 citationsSenior author

DOI: 10.1016/j.jad.2023.11.017

Using deep learning and pretreatment EEG to predict response to sertraline, bupropion, and placebo

Ravan M, Noroozi A, Gediya H, James Basco K, Hasey G

Clinical Neurophysiology20249 citationsSenior author

DOI: 10.1016/j.clinph.2024.09.002

Diagnosing Suicidal Ideation from Resting State EEG Data Using a Machine Learning Algorithm

Sanchez MM, Ravan M, Hasey G, Reilly J, Minuzzi L

Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings20242 citations

DOI: 10.1109/embc53108.2024.10782191

Discriminating between bipolar and major depressive disorder using a machine learning approach and resting-state EEG data

Ravan M, Noroozi A, Sanchez MM, Borden L, Alam N, Flor-Henry P, Hasey G

Clinical Neurophysiology202338 citationsSenior author

DOI: 10.1016/j.clinph.2022.11.014

EEG Biomarkers to Predict Response to Sertraline and Placebo Treatment in Major Depressive Disorder

Oakley T, Coskuner J, Cadwallader A, Ravan M, Hasey G

IEEE Transactions on Biomedical Engineering202320 citationsSenior author

DOI: 10.1109/tbme.2022.3204861

Competencies for Repetitive Transcranial Magnetic Stimulation in Postgraduate Medical Education: Expert Consensus Using a Modified Delphi Process

Lai KSP, Waxman R, Blumberger DM, Giacobbe P, Hasey G, McMurray L, Milev R, Palaniyappan L, Ramasubbu R, Rybak YE

Canadian Journal of Psychiatry20236 citations

DOI: 10.1177/07067437231164571

A Machine Learning Algorithm to Discriminating Between Bipolar and Major Depressive Disorders Based on Resting EEG Data

Sanchez MM, Borden L, Alam N, Noroozi A, Ravan M, Flor-Henry P, Hasey G

Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings202217 citationsSenior author

DOI: 10.1109/embc48229.2022.9871453

A machine learning approach to identification of self-harm and suicidal ideation among military and police Veterans

Colic S, He JC, Richardson JD, St. Cyr K, Reilly JP, Hasey GM

Journal of Military, Veteran and Family Health20228 citationsSenior author

DOI: 10.3138/jmvfh-2021-0035

Research institutes and memberships

Peter Boris Centre for Addictions Research (PBCAR)

Researchers with similar interests

Richard Kolesar

Anesthesia

EEG and Brain-Computer Interfaces, Functional Brain Connectivity Studies

Luciano Minuzzi

Psychiatry & Behavioural Neurosciences

Functional Brain Connectivity Studies, Bipolar Disorder and Treatment

Craig Beers

Oncology

Functional Brain Connectivity Studies, EEG and Brain-Computer Interfaces

Dante Duarte

Psychiatry & Behavioural Neurosciences

Transcranial Magnetic Stimulation Studies, Bipolar Disorder and Treatment

Benicio Frey

Psychiatry & Behavioural Neurosciences

Functional Brain Connectivity Studies, Bipolar Disorder and Treatment

Fabiano Alves Gomes

Psychiatry & Behavioural Neurosciences

Bipolar Disorder and Treatment, Electroconvulsive Therapy Studies

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Subject: Prospective PhD student: EEG and Brain-Computer Interfaces Dear Professor Hasey, My name is [your name], and I am a [your current degree or role] at [your institution]. I am applying for a PhD position starting in [term and year]. I read your paper "Evaluation of Short Term and Long Term Subjective and Objective Cognitive Outcomes Following ECT for Depression in a Naturalistic Ambulatory Setting: A Cohort Study" (2026), and it connects closely to my own work on [your research topic]. [One or two sentences on what you did and what you learned.] Are you accepting new PhD students for [term and year]? I have attached my CV and transcripts, and I would be glad to talk at a time that suits you. Thank you for your time. Kind regards, [your name]

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Gary Marcel Hasey

Research

Evaluation of Short Term and Long Term Subjective and Objective Cognitive Outcomes Following ECT for Depression in a Naturalistic Ambulatory Setting: A Cohort Study

One Hundred Years Later! The Current Utility of EEG Tools in Psychiatry: Some Insights and Perspectives

Diagnostic deep learning algorithms that use resting EEG to distinguish major depressive disorder, bipolar disorder, and schizophrenia from each other and from healthy volunteers

Using deep learning and pretreatment EEG to predict response to sertraline, bupropion, and placebo

Diagnosing Suicidal Ideation from Resting State EEG Data Using a Machine Learning Algorithm

Discriminating between bipolar and major depressive disorder using a machine learning approach and resting-state EEG data

EEG Biomarkers to Predict Response to Sertraline and Placebo Treatment in Major Depressive Disorder

Competencies for Repetitive Transcranial Magnetic Stimulation in Postgraduate Medical Education: Expert Consensus Using a Modified Delphi Process

A Machine Learning Algorithm to Discriminating Between Bipolar and Major Depressive Disorders Based on Resting EEG Data

A machine learning approach to identification of self-harm and suicidal ideation among military and police Veterans

Research institutes and memberships

Frequent collaborators

Jim Reilly

Huibregt Debruin

Bruno Losier

Heather McNeely

Margaret McKinnon

Peter Bieling

Researchers with similar interests

Richard Kolesar

Luciano Minuzzi

Craig Beers

Dante Duarte

Benicio Frey

Fabiano Alves Gomes