BEGIN:VCALENDAR
PRODID:-//github.com/ical-org/ical.net//NONSGML ical.net 4.0//EN
VERSION:2.0
BEGIN:VTIMEZONE
TZID:America/New_York
X-LIC-LOCATION:America/New_York
BEGIN:STANDARD
DTSTART:20241103T020000
RRULE:FREQ=YEARLY;BYDAY=1SU;BYMONTH=11
TZNAME:EST
TZOFFSETFROM:-0400
TZOFFSETTO:-0500
END:STANDARD
BEGIN:DAYLIGHT
DTSTART:20250309T020000
RRULE:FREQ=YEARLY;BYDAY=2SU;BYMONTH=3
TZNAME:EDT
TZOFFSETFROM:-0500
TZOFFSETTO:-0400
END:DAYLIGHT
END:VTIMEZONE
BEGIN:VEVENT
DESCRIPTION:Note: BIS 526 students are required to attend in person. Other
 s are invited to attend in person but may also attend via zoom. Speaker- 
 Ying Guo\, Ph.D. Title- "A Statistical AI Method for Learning Directed Co
 nnectomes and Uncovering Subpopulation Differences in Brain Organization"
  Abstract In recent years\, connectome-based research has become a centra
 l focus in neuroscience\, offering essential insights into brain organiza
 tion and advancing predictive modeling of cognitive\, behavioral\, and me
 ntal health outcomes. While most existing approaches focus on undirected 
 brain connectivity\, they overlook the directionality and causal influenc
 es between brain regions. To address this limitation\, we propose a stati
 stical AI method for learning directed brain connectomes from neuroimagin
 g data. Our approach integrates principled statistical modeling with deep
  learning to infer sparse\, interpretable directed connectivity graphs th
 at characterize latent causal interactions across the brain. At the same 
 time\, the method learns low-dimensional graph embeddings optimized for d
 ownstream prediction tasks\, including demographic attributes and clinica
 l phenotypes. The proposed method uncovers whole-brain directed connectiv
 ity patterns and reveals novel subpopulation-specific connectomic differe
 nces\, highlighting its potential to advance both mechanistic understandi
 ng and predictive modeling in neuroscience\n\nSpeaker:\nYing Guo\, Ph.D.\
 n\nAdmission:\nFree\n\nDetails URL:\nhttps://medicine.yale.edu/event/ysph
 -biostatistics-seminar-16/\n
DTEND;TZID=America/New_York:20260428T130000
DTSTAMP:20261023T045700Z
DTSTART;TZID=America/New_York:20260428T120000
GEO:41.302961;-72.931638
LOCATION:106 A&B\, 47 College Street\, New Haven\, CT\, United States
SEQUENCE:0
STATUS:Confirmed
SUMMARY:YSPH Biostatistics Seminar- "A Statistical AI Method for Learning 
 Directed Connectomes and Uncovering Subpopulation Differences in Brain Or
 ganization"
UID:cbe6ecec-46ff-4406-88d3-e85e12cacb12
END:VEVENT
END:VCALENDAR