Research Team

Joseph Gyorda, BA

MS Candidate, Program in Quantitative Biomedical Sciences, Geisel School of Medicine at Dartmouth

Health Data Science; Applied Machine Learning; Digital Mental Health Dynamics

Contact

Joseph Gyorda, BA
MS Candidate, Program in Quantitative Biomedical Sciences, Geisel School of Medicine at Dartmouth

joseph.a.gyorda.gr@dartmouth.edu


Joseph (Joe) is a current Master’s student in the Department of Quantitative Biomedical Sciences with a concentration in Health Data Science at Dartmouth College Geisel School of Medicine. Joe graduated with a Bachelor’s degree in Mathematical Data Science from Dartmouth College in 2022 and has been a member of Dr. Nicholas Jacobson’s AIM HIGH laboratory since 2020. Within Dr. Jacobson’s lab, Joe has implemented predictive models to examine the factors which contribute to changes in mental health, and has also conducted reviews of the existing literature of emotion regulation, substance use, eating disorders, predictive modeling of mental health disorders, and mental health dynamics—particularly during COVID-19—to assist in preparing academic manuscripts. As a graduate student, Joe is interested in learning additional computational tools and techniques with hopes to further investigate what factors influence changes in mental health, particularly by examining different forms of passively collected data in conjunction with mood and self-perception data.

In his free time, Joe enjoys being outdoors training for triathlons or hiking in the Upper Valley. Joe is also an avid Boston sports fan and also follows English Premier League Soccer.

Joe’s LinkedIn page


Selected Publications
  • type-published
    1672531200
    1
    2023
    Lekkas D, Gyorda JA, Jacobson NC. A machine learning investigation into the temporal dynamics of physical activity-mediated emotional regulation in adolescents with anorexia nervosa and healthy controls. Eur Eat Disord Rev. 2023 Jan;31(1):147-165. doi: 10.1002/erv.2949. PMID: 36005065.
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  • type-published
    1672531200
    1
    2023
    Gyorda JA, Nemesure MD, Price G, Jacobson NC. Applying ensemble machine learning models to predict individual response to a digitally delivered worry postponement intervention. J Affect Disord. 2023 Jan 1;320:201-210. doi: 10.1016/j.jad.2022.09.112. PMID: 36167247.
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  • type-published
    1669852800
    12
    2022
    Klein RJ, Nguyen ND, Gyorda JA, Jacobson NC. Adolescent emotion regulation and future psychopathology: A prospective transdiagnostic analysis. J Res Adolesc. 2022 Dec;32(4):1592-1611. doi: 10.1111/jora.12743. PMID: 35301763.
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  • type-published
    1669766400
    11
    2022
    Lekkas D, Gyorda JA, Moen EL, Jacobson NC. Using passive sensor data to probe associations of social structure with changes in personality: A synthesis of network analysis and machine learning. PLoS One. 2022 Nov 30;17(11):e0277516. doi: 10.1371/journal.pone.0277516. PMID: 36449466.
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  • type-published
    1653350400
    5
    2022
    Klein RJ, Gyorda JA, Jacobson NC. Anxiety, depression, and substance experimentation in childhood. PLoS One. 2022 May 24;17(5):e0265239. doi: 10.1371/journal.pone.0265239. PMID: 35609016.
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  • type-published
    1643241600
    1
    2022
    Lekkas D, Gyorda JA, Price GD, Wortzman Z, Jacobson NC. Using the COVID-19 pandemic to assess the influence of news affect on online mental health-related search behavior across the United States: Integrated sentiment analysis and the circumplex model of affect. J Med Internet Res. 2022 Jan 27;24(1):e32731. doi: 10.2196/32731. PMID: 34932494; PMCID: PMC8805454.
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