Jeesung Ahn, Ph.D.

Postdoc Researcher @ Stanford | Translating Neuroscience into Precision Mental Health Care

San Francisco Bay Area

About

Passionate about translating scientific discoveries into real-world solutions, my research leverages brain function as a biomarker to improve the precision of depression treatments and develop personalized mental and behavioral health care models. Research keywords: precision psychiatry, mental health, behavioral health, depression, loneliness, behavior change, digital health intervention, social connection, neuroimaging, fMRI, predictive modeling, machine learning

Experience

  • Stanford University School of Medicine (On-site)
    • Postdoctoral Researcher
      Nov 2024 - Present · 1 yr 8 mos

    • Postdoctoral Researcher
      Nov 2024 - Present · 1 yr 8 mos

  • Social Connection Fellow at Global Initiative on Loneliness and Connection
    Sep 2024 - May 2025 · 9 mos

  • University of Pennsylvania (Philadelphia, Pennsylvania, United States)
    • Doctoral Researcher
      Aug 2019 - May 2024 · 4 yrs 10 mos

      • Led 8+ multi-disciplinary research projects analyzing brain and social network data to develop machine learning models predicting health intervention effectiveness to promote behavior change and improve well-being; presented findings at annual U.S. Army Research Office meetings • Collaborated with cross-functional teams from 10+ institutions and 80+ researchers; excelled in visualizing and communicating complex scientific findings to diverse audiences • Developed and maintained the lab's data preprocessing and analytic pipeline (Python, R, Jupyterhub) for streamlined analysis and visualization of complex multi-dimensional datasets (61TB), now actively used by global collaborators in 3+ countries • Coded and documented 30,000+ persuasive health messages across 17 neuroimaging datasets from 6 international labs; conducted a meta-analysis of behavioral and neuroimaging datasets; mentored and managed undergraduate research assistants • Passionate about communicating scientific findings to wider audiences; proficient in using R Markdown and visualization tools (e.g., ggplot2, Shiny) for data visualization • Working on 7+ first-authored papers for publication; presented at various conferences and departmental meetings to audiences of different sizes and backgrounds.

    • Teaching Assistant
      Jan 2021 - Dec 2021 · 1 yr

      • Mentored 100+ undergraduate students in developing effective study strategies during the challenging times of COVID-19 • Created evaluation tools, graded student essays, and provided constructive feedback • Introduction to Experimental Psychology (Spring 2021, Rebecca Waller, Ph.D.; Fall 2021, Anna Jenkins, Ph.D.)

  • Digital Healthcare Data Science Intern at Samsung Life Insurance
    Jul 2023 - Jul 2023 · 1 mo

    • Analyzed behavioral patterns and health conditions of Samsung healthcare app users (200K+ data points), driving substantial changes to the UI/UX design to reduce cognitive load and improve usability • Curated compelling well-being content to facilitate user acquisition and retention, presently integrated into the app

  • Research Associate at Yonsei University
    Apr 2015 - Jul 2019 · 4 yrs 4 mos

    • Designed and directed 7+ end-to-end behavioral and neuroimaging projects, resulting in 3 first-author publications, an award-winning Master’s thesis, and 6 international conference presentations • Provided consulting services to a start-up company on the efficacy of their novel neurostimulation technology in enhancing cognitive functions, such as attention capacity; designed and conducted A/B tests and usability studies of their product, which led to the successful acquisition of $100K in funding; led a team that presented findings to cross-functional stakeholders, including venture capital funders, designers, engineers, and clinicians, to inform and advocate the direction of product development • Collaborated with cross-functional teams to develop a mobile application for treating social anxiety; conducted behavioral and neuroimaging experiments, in-depth interviews, and supervised machine learning analyses to evaluate user experience and the clinical efficacy of the application • Provided extensive technical support and mentorship to onboarding researchers regarding research project management, neuroimaging analyses, data quality control, and MATLAB scripting