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METHOD:REQUEST
PRODID:Microsoft Exchange Server 2010
VERSION:2.0
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DTSTART:16010101T020000
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BEGIN:VEVENT
ORGANIZER;CN="Hunter, Tiffany":mailto:huntert1@ohio.edu
ATTENDEE;ROLE=REQ-PARTICIPANT;PARTSTAT=NEEDS-ACTION;RSVP=TRUE;CN=ziyang.son
g@mail.mcgill.ca:mailto:ziyang.song@mail.mcgill.ca
ATTENDEE;ROLE=REQ-PARTICIPANT;PARTSTAT=NEEDS-ACTION;RSVP=TRUE;CN="Liu, Jundo
ng":mailto:liuj1@ohio.edu
ATTENDEE;ROLE=REQ-PARTICIPANT;PARTSTAT=NEEDS-ACTION;RSVP=TRUE;CN="Steinberg,
Eric":mailto:steinber@ohio.edu
ATTENDEE;ROLE=REQ-PARTICIPANT;PARTSTAT=NEEDS-ACTION;RSVP=TRUE;CN="Fox, Patri
ck":mailto:pfox@ohio.edu
ATTENDEE;ROLE=REQ-PARTICIPANT;PARTSTAT=NEEDS-ACTION;RSVP=TRUE;CN="Juedes, Da
vid":mailto:juedes@ohio.edu
ATTENDEE;ROLE=REQ-PARTICIPANT;PARTSTAT=NEEDS-ACTION;RSVP=TRUE;CN="Patterson,
James":mailto:pattersj@ohio.edu
ATTENDEE;ROLE=REQ-PARTICIPANT;PARTSTAT=NEEDS-ACTION;RSVP=TRUE;CN="Abukamail,
Nasseef":mailto:abukamai@ohio.edu
ATTENDEE;ROLE=REQ-PARTICIPANT;PARTSTAT=NEEDS-ACTION;RSVP=TRUE;CN="Allwine, D
aniel":mailto:allwined@ohio.edu
ATTENDEE;ROLE=REQ-PARTICIPANT;PARTSTAT=NEEDS-ACTION;RSVP=TRUE;CN="Bartone, C
hris":mailto:bartone@ohio.edu
ATTENDEE;ROLE=REQ-PARTICIPANT;PARTSTAT=NEEDS-ACTION;RSVP=TRUE;CN="Goble, Jam
es":mailto:goble@ohio.edu
ATTENDEE;ROLE=REQ-PARTICIPANT;PARTSTAT=NEEDS-ACTION;RSVP=TRUE;CN="Irwin, Den
nis":mailto:irwind@ohio.edu
ATTENDEE;ROLE=REQ-PARTICIPANT;PARTSTAT=NEEDS-ACTION;RSVP=TRUE;CN="Jadwisienc
zak, Wojciech":mailto:jadwisie@ohio.edu
ATTENDEE;ROLE=REQ-PARTICIPANT;PARTSTAT=NEEDS-ACTION;RSVP=TRUE;CN="Karanth, A
vinash":mailto:karanth@ohio.edu
ATTENDEE;ROLE=REQ-PARTICIPANT;PARTSTAT=NEEDS-ACTION;RSVP=TRUE;CN="Kaya, Sava
s":mailto:kaya@ohio.edu
ATTENDEE;ROLE=REQ-PARTICIPANT;PARTSTAT=NEEDS-ACTION;RSVP=TRUE;CN="Liu, Chang"
:mailto:liuc@ohio.edu
ATTENDEE;ROLE=REQ-PARTICIPANT;PARTSTAT=NEEDS-ACTION;RSVP=TRUE;CN="Mourning,
Chad":mailto:mourning@ohio.edu
ATTENDEE;ROLE=REQ-PARTICIPANT;PARTSTAT=NEEDS-ACTION;RSVP=TRUE;CN="Ostermann,
Shawn":mailto:osterman@ohio.edu
ATTENDEE;ROLE=REQ-PARTICIPANT;PARTSTAT=NEEDS-ACTION;RSVP=TRUE;CN="Rahman, Fa
iz":mailto:rahmanf@ohio.edu
ATTENDEE;ROLE=REQ-PARTICIPANT;PARTSTAT=NEEDS-ACTION;RSVP=TRUE;CN="Schlicher,
Jared":mailto:schliche@ohio.edu
ATTENDEE;ROLE=REQ-PARTICIPANT;PARTSTAT=NEEDS-ACTION;RSVP=TRUE;CN="Ugazio, Sa
brina":mailto:ugazio@ohio.edu
ATTENDEE;ROLE=REQ-PARTICIPANT;PARTSTAT=NEEDS-ACTION;RSVP=TRUE;CN="Vasiliadis
, Konstantinos":mailto:vassilia@ohio.edu
ATTENDEE;ROLE=REQ-PARTICIPANT;PARTSTAT=NEEDS-ACTION;RSVP=TRUE;CN="Welch, Lon
nie":mailto:welch@ohio.edu
ATTENDEE;ROLE=REQ-PARTICIPANT;PARTSTAT=NEEDS-ACTION;RSVP=TRUE;CN="Zhu, Jim":m
ailto:zhuj@ohio.edu
ATTENDEE;ROLE=REQ-PARTICIPANT;PARTSTAT=NEEDS-ACTION;RSVP=TRUE;CN="Wang, Zhew
ei":mailto:wangz1@ohio.edu
ATTENDEE;ROLE=REQ-PARTICIPANT;PARTSTAT=NEEDS-ACTION;RSVP=TRUE;CN="Lindner, P
atricia":mailto:lindnerp@ohio.edu
ATTENDEE;ROLE=REQ-PARTICIPANT;PARTSTAT=NEEDS-ACTION;RSVP=TRUE;CN="Ardrey, Gr
egory":mailto:gardrey@ohio.edu
ATTENDEE;ROLE=REQ-PARTICIPANT;PARTSTAT=NEEDS-ACTION;RSVP=TRUE;CN="Yadav, Ani
mesh":mailto:yadava@ohio.edu
ATTENDEE;ROLE=REQ-PARTICIPANT;PARTSTAT=NEEDS-ACTION;RSVP=TRUE;CN="Plis, Kevi
n":mailto:plis@ohio.edu
ATTENDEE;ROLE=REQ-PARTICIPANT;PARTSTAT=NEEDS-ACTION;RSVP=TRUE;CN="Oun, Ahmed"
:mailto:oun@ohio.edu
ATTENDEE;ROLE=REQ-PARTICIPANT;PARTSTAT=NEEDS-ACTION;RSVP=TRUE;CN="Mirzanezha
d, Majid":mailto:miirza@ohio.edu
ATTENDEE;ROLE=REQ-PARTICIPANT;PARTSTAT=NEEDS-ACTION;RSVP=TRUE;CN="Dolan, Joh
n":mailto:dolan@ohio.edu
ATTENDEE;ROLE=REQ-PARTICIPANT;PARTSTAT=NEEDS-ACTION;RSVP=TRUE;CN="Khalili, F
atemeh":mailto:khalili@ohio.edu
ATTENDEE;ROLE=REQ-PARTICIPANT;PARTSTAT=NEEDS-ACTION;RSVP=TRUE;CN=eecs_bscs@
listserv.ohio.edu:mailto:eecs_bscs@listserv.ohio.edu
ATTENDEE;ROLE=REQ-PARTICIPANT;PARTSTAT=NEEDS-ACTION;RSVP=TRUE;CN=eecs_bsee@
listserv.ohio.edu:mailto:eecs_bsee@listserv.ohio.edu
ATTENDEE;ROLE=REQ-PARTICIPANT;PARTSTAT=NEEDS-ACTION;RSVP=TRUE;CN=eecs_mscs@
listserv.ohio.edu:mailto:eecs_mscs@listserv.ohio.edu
ATTENDEE;ROLE=REQ-PARTICIPANT;PARTSTAT=NEEDS-ACTION;RSVP=TRUE;CN=eecs_phd@l
istserv.ohio.edu:mailto:eecs_phd@listserv.ohio.edu
ATTENDEE;ROLE=REQ-PARTICIPANT;PARTSTAT=NEEDS-ACTION;RSVP=TRUE;CN=eecs_msee@
listserv.ohio.edu:mailto:eecs_msee@listserv.ohio.edu
ATTENDEE;ROLE=REQ-PARTICIPANT;PARTSTAT=NEEDS-ACTION;RSVP=TRUE;CN="Schultz, A
dam":mailto:schultza@ohio.edu
ATTENDEE;ROLE=REQ-PARTICIPANT;PARTSTAT=NEEDS-ACTION;RSVP=TRUE;CN="Tirtom, Is
mail":mailto:itirtom@ohio.edu
DESCRIPTION;LANGUAGE=en-US:Title: Deep and Probabilistic Representation Lea
rning for Electronic Health Records\nAbstract:\nArtificial Intelligence (A
I) has achieved remarkable success across a broad range of fields\; howeve
r\, it often remains insufficiently prepared for deployment in high-stakes
scenarios like healthcare. Recent advancements in AI for language and vis
ion have increasingly prioritized accuracy over explainability\, thereby c
onstraining their practical utility and potentially posing risks to human
lives. In contrast\, while statistical machine learning models excel in pr
oviding interpretable analyses\, they often fall short in predictive perfo
rmance. We aim to explore AI solutions for healthcare applications that co
mbine strong predictive performance with strong explainability. In this ta
lk\, I will discuss three key research topics: (1) generative AI for healt
hcare time series\, enabling interpretable trajectory analysis\; (2) proba
bilistic models for medical language modeling\, integrating neural network
s into inference for greater flexibility\; (3) a long-term vision for comb
ining deep learning and statistical machine learning to advance scientific
discovery.\nBio:\nZiyang Song is a Ph.D. candidate in the School of Compu
ter Science at McGill University. His research revolves around Artificial
Intelligence for health\, with a particular focus on generative artificial
intelligence and statistical machine learning. Specifically\, his researc
h designs AI models with explainability by bridging deep learning and stat
istical models for healthcare applications. He has published in top-tier m
achine learning (e.g.\, ICLR\, KDD) and interdisciplinary conferences (e.g
.\, MLHC\, ACM-BCB). He also received notable honors\, including KDD Healt
h Day Best Paper Award (2022) and ACM BCB Rising Star Award (2024). He als
o secured Quebec’s prestigious FRQNT Doctoral Research Scholarship (2022
-2026) for deploying real-world AI systems for at-risk population. He has
collaborated with Université de Montréal (UdeM) and conducted research a
t Centre hospitalier universitaire Sainte-Justine (CHU-SJ)\, where he desi
gned AI models to identify high-risk patients with interpretable analysis
in clinical settings.\n___________________________________________________
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