Computational Biology Thesis Proposal

  • Remote Access - Zoom
  • Virtual Presentation - ET
  • Ph.D. Student
  • Computational Biology Department
  • Carnegie Mellon University
Thesis Proposals

Modeling individual differences in the brain in the presence and absence of disease

Studying the brain is crucial to improve the treatment of neurological and psychiatric diseases. Recent work suggests that neuroimaging data may explain the personalized presentations of disease that clinicians see every day. If we can measure and understand the personalized presentation associated with specific diagnoses and/or prognoses, clinicians could use this information to inform optimal patient-specific treatments. 

However, even finding an association between the personalized presentation and specific diagnoses and prognoses is difficult due to the noise inherent in the data and the small sample sizes typical in research studies. To mitigate these limitations, we propose new approaches to help identify and understand the baseline differences associated with health, as well as the clinical differences associated with diagnosis and prognosis. We propose to (1) assess the baseline variability between healthy individuals, (2) assess variability between individuals with a psychiatric disease that doesn’t present with visible structural differences, and (3) assess variability associated with structural differences due to stroke and draw causal connections to disease prognosis. This work will increase our understanding of the brain as well as neurological and psychiatric diseases. 

Thesis Committee:
Leila Wehbe (Chair)
Tom Mitchell
Ashok Panigrahy (University of Pittsburgh)
Timothy Verstynen (Psychology/CMU)

Zoom Participation. See announcement.

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