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END:VTIMEZONE
BEGIN:VEVENT

RECURRENCE-ID;TZID=America/New_York:20251114T203000Z
CATEGORIES:Utilities
CATEGORIES:Main
CONTACT;X-BEDEWORK-UID=8a00ec8b-979413b9-0198-a4d89b28-00001675:Thompson\,
  Ekaterina
CREATED:20250904T132242Z
DESCRIPTION:TBD
DURATION:PT1H
DTSTAMP:20251110T223611Z
DTSTART;TZID=America/New_York:20251114T153000
LAST-MODIFIED:20251110T223611Z
LOCATION;X-BEDEWORK-UID=18832edc-1b27e154-011b-28365daf-0000006c:Old Chemi
 stry 116
STATUS:CONFIRMED
SUMMARY:Friday Seminar in the department of Statistical Science
UID:CAL-8a00ec8b-979413b9-0199-14e4ca9c-0000776cdemobedework@mysite.edu
X-BEDEWORK-ALIAS;X-BEDEWORK-PARAM-DISPLAYNAME=Main:/user/public-user/Utili
 ties/Main
X-BEDEWORK-SPEAKER:TBD
X-BEDEWORK-DUKE-SERIES:Friday Seminar in the department of Statistical Sci
 ence
X-BEDEWORK-SUBMITTEDBY:ek217 for Statistical Science (agrp_StatisticalScie
 nce)
EXDATE:20251010T193000Z
END:VEVENT
BEGIN:VEVENT

RECURRENCE-ID;TZID=America/New_York:20251121T203000Z
CATEGORIES:Utilities
CATEGORIES:Main
CONTACT;X-BEDEWORK-UID=8a00ec8b-979413b9-0198-a4d89b28-00001675:Thompson\,
  Ekaterina
CREATED:20250904T132242Z
DESCRIPTION:TBD
DURATION:PT1H
DTSTAMP:20251119T160701Z
DTSTART;TZID=America/New_York:20251121T153000
LAST-MODIFIED:20251119T160701Z
LOCATION;X-BEDEWORK-UID=18832edc-1b27e154-011b-28365daf-0000006c:Old Chemi
 stry 116
STATUS:CONFIRMED
SUMMARY:Friday Seminar in the department of Statistical Science
UID:CAL-8a00ec8b-979413b9-0199-14e4ca9c-0000776cdemobedework@mysite.edu
X-BEDEWORK-ALIAS;X-BEDEWORK-PARAM-DISPLAYNAME=Main:/user/public-user/Utili
 ties/Main
X-BEDEWORK-SPEAKER:TBD
X-BEDEWORK-DUKE-SERIES:Friday Seminar in the department of Statistical Sci
 ence
X-BEDEWORK-SUBMITTEDBY:ek217 for Statistical Science (agrp_StatisticalScie
 nce)
EXDATE:20251010T193000Z
END:VEVENT
BEGIN:VEVENT

CATEGORIES:Lectures/Conferences
CATEGORIES:Utilities
CATEGORIES:Lecture/Talk
CATEGORIES:Panel/Seminar/Colloquium
CATEGORIES:Main
CONTACT;X-BEDEWORK-UID=00f1fcdb-0f068baf-010f-068baf83-00000004:None
CREATED:20260109T162145Z
DESCRIPTION:Many modern datasets exhibit low-dimensional organization desp
 ite living in high ambient dimensions\, yet this structure is often impli
 cit\, noisy\, and not explicitly modeled. In this talk\, I discuss statis
 tical inference in such settings through two complementary examples. I fi
 rst present recent theoretical results on Gaussian process regression for
  data supported on unknown low-dimensional structures. Using a real-domai
 n small-bandwidth analysis\, I show how intrinsic geometry governs approx
 imation and posterior contraction behavior without relying on spectral or
  Laplacian machinery\, leading to adaptive rates driven by intrinsic rath
 er than ambient dimension. I then turn to a biological application in sin
 gle-cell genomics\, where local neighborhood graphs are used to define op
 timal-transport-based gene affinities and reveal gene trajectories and un
 derlying biological processes. These examples illustrate how latent geome
 tric structure\, when present but only weakly revealed by data\, can none
 theless be harnessed to enable reliable statistical inference in high dim
 ensions.
DURATION:PT1H
DTSTAMP:20260113T145537Z
DTSTART;TZID=America/New_York:20260116T153000
LAST-MODIFIED:20260113T145537Z
LOCATION;X-BEDEWORK-UID=18832edc-1b27e154-011b-28365daf-0000006c:Old Chemi
 stry 116
STATUS:CONFIRMED
SUMMARY:Intrinsic geometry and latent low dimensionality in data: manifold
 s and beyond
UID:CAL-8a00eca5-9af98aae-019b-a3905d65-00003415demobedework@mysite.edu
X-BEDEWORK-ALIAS;X-BEDEWORK-PARAM-DISPLAYNAME=Main:/user/public-user/Utili
 ties/Main
X-BEDEWORK-ALIAS;X-BEDEWORK-PARAM-DISPLAYNAME=Lecture_Talk:/user/public-us
 er/Lectures_Conferences/Lecture_Talk
X-BEDEWORK-ALIAS;X-BEDEWORK-PARAM-DISPLAYNAME=Panel_Seminar_Colloquium:/us
 er/public-user/Lectures_Conferences/Panel_Seminar_Colloquium
X-BEDEWORK-STUDENT-CONTACT;X-BEDEWORK-PARAM-EMAIL=ekaterina.thompson@duke.
 edu:Ekaterina Thompson
X-BEDEWORK-SPEAKER:Xiuyuan Cheng
X-BEDEWORK-DUKE-SERIES:Friday Seminar in the department of Statistical Sci
 ence
X-BEDEWORK-IMAGE-X1:142
X-BEDEWORK-IMAGE-Y1:157
X-BEDEWORK-IMAGE-X2:1069
X-BEDEWORK-IMAGE-Y2:775
X-BEDEWORK-IMAGE-CROP-WIDTH:927
X-BEDEWORK-IMAGE-CROP-HEIGHT:618
X-BEDEWORK-IMAGE-ALT-TEXT:Xiuyuan Cheng
X-BEDEWORK-SUBMITTEDBY:ek217 for Statistical Science (agrp_StatisticalScie
 nce)
X-BEDEWORK-IMAGE:/public/Images/Screenshot 2026-01-09 at 11.20.07 AM_20260
 113025537PM.png
X-BEDEWORK-THUMB-IMAGE:/public/Images/Screenshot 2026-01-09 at 11.20.07 AM
 _20260113025537PM-thumb.png
END:VEVENT
BEGIN:VEVENT

CATEGORIES:Utilities
CATEGORIES:Main
CONTACT;X-BEDEWORK-UID=00f1fcdb-0f068baf-010f-068baf83-00000004:None
CREATED:20260120T121156Z
DESCRIPTION:With breakthroughs in scientific computing\, virtual simulator
 s are increasingly used as "digital twins" for studying complex scientifi
 c phenomena\, e.g.\, particle collisions and nuclear reactions. Such simu
 lators\, however\, are highly time-intensive\, which hinders their effect
 ive use for scientific decision-making\, e.g.\, the optimization of a par
 ticle detector. There is a pressing need for novel Bayesian ML/AI methods
  that synergize with digital twins to enable timely\, uncertainty-aware\,
  and interpretable decision-making. One promising tool is Bayesian optimi
 zation (BO)\, which tackles the optimization of a costly black-box functi
 on (e.g.\, the response surface of the virtual simulator) using limited f
 unction evaluations. In this talk\, I will present a suite of novel BO me
 thods that address several important needs for scientific applications. T
 he first is a new BO method for identifying varied local optima of a blac
 k-box function\, which provides scientists with a basket of different opt
 imal solutions for flexible decision-making. The second method tackles th
 e challenging problem of high-dimensional black-box optimization\, offeri
 ng improved theoretical rates and empirical performance over existing tec
 hniques in the one-shot setting. The effectiveness of these methods will 
 be investigated in ongoing collaborative projects in the physical and eng
 ineering sciences.
DURATION:PT1H
DTSTAMP:20260120T121156Z
DTSTART;TZID=America/New_York:20260123T033000
LAST-MODIFIED:20260120T121156Z
LOCATION;X-BEDEWORK-UID=18832edc-1b27e154-011b-28365daf-0000006c:Old Chemi
 stry 116
STATUS:CONFIRMED
SUMMARY:Advances in Bayesian optimization for accelerating scientific deci
 sion-making
UID:CAL-8a00eca5-9af98aae-019b-db519adc-000026c6demobedework@mysite.edu
X-BEDEWORK-ALIAS;X-BEDEWORK-PARAM-DISPLAYNAME=Main:/user/public-user/Utili
 ties/Main
X-BEDEWORK-SPEAKER:Simon Mak
X-BEDEWORK-DUKE-SERIES:Friday Seminar in the department of Statistical Sci
 ence
X-BEDEWORK-STUDENT-CONTACT;X-BEDEWORK-PARAM-EMAIL=ekaterina.thompson@duke.
 edu:Ekaterina Thompson
X-BEDEWORK-IMAGE-X1:69
X-BEDEWORK-IMAGE-Y1:133
X-BEDEWORK-IMAGE-X2:1179
X-BEDEWORK-IMAGE-Y2:873
X-BEDEWORK-IMAGE-CROP-WIDTH:1110
X-BEDEWORK-IMAGE-CROP-HEIGHT:740
X-BEDEWORK-IMAGE-ALT-TEXT:Simon Mak
X-BEDEWORK-SUBMITTEDBY:ek217 for Statistical Science (agrp_StatisticalScie
 nce)
X-BEDEWORK-IMAGE:/public/Images/Screenshot 2026-01-20 at 7.10.38 AM_202601
 20121139PM.png
X-BEDEWORK-THUMB-IMAGE:/public/Images/Screenshot 2026-01-20 at 7.10.38 AM_
 20260120121139PM-thumb.png
END:VEVENT
BEGIN:VEVENT

RECURRENCE-ID;TZID=America/New_York:20260130T203000Z
CATEGORIES:Utilities
CATEGORIES:Main
CONTACT;X-BEDEWORK-UID=00f1fcdb-0f068baf-010f-068baf83-00000004:None
CREATED:20260122T165024Z
DESCRIPTION:TBD
DURATION:PT1H
DTSTAMP:20260126T141315Z
DTSTART;TZID=America/New_York:20260130T153000
LAST-MODIFIED:20260126T141315Z
LOCATION;X-BEDEWORK-UID=18832edc-1b27e154-011b-28365daf-0000006c:Old Chemi
 stry 116
STATUS:CONFIRMED
SUMMARY:Friday Seminar in the department of Statistical Science
UID:CAL-8a00eca5-9af98aae-019b-e69d42e9-00000e2fdemobedework@mysite.edu
X-BEDEWORK-ALIAS;X-BEDEWORK-PARAM-DISPLAYNAME=Main:/user/public-user/Utili
 ties/Main
X-BEDEWORK-SPEAKER:TBD
X-BEDEWORK-DUKE-SERIES:Friday Seminar in the department of Statistical Sci
 ence
X-BEDEWORK-SUBMITTEDBY:ek217 for Statistical Science (agrp_StatisticalScie
 nce)
X-BEDEWORK-STUDENT-CONTACT;X-BEDEWORK-PARAM-EMAIL=statsci-friday-seminars@
 duke.edu:StatSci Friday Seminars
EXDATE:20260306T203000Z
EXDATE:20260313T193000Z
EXDATE:20260320T193000Z
END:VEVENT
BEGIN:VEVENT

RECURRENCE-ID;TZID=America/New_York:20260206T203000Z
CATEGORIES:Utilities
CATEGORIES:Main
CONTACT;X-BEDEWORK-UID=00f1fcdb-0f068baf-010f-068baf83-00000004:None
CREATED:20260122T165024Z
DESCRIPTION:TBD
DURATION:PT1H
DTSTAMP:20260127T165335Z
DTSTART;TZID=America/New_York:20260206T153000
LAST-MODIFIED:20260127T165335Z
LOCATION;X-BEDEWORK-UID=18832edc-1b27e154-011b-28365daf-0000006c:Old Chemi
 stry 116
STATUS:CONFIRMED
SUMMARY:Friday Seminar in the department of Statistical Science
UID:CAL-8a00eca5-9af98aae-019b-e69d42e9-00000e2fdemobedework@mysite.edu
X-BEDEWORK-ALIAS;X-BEDEWORK-PARAM-DISPLAYNAME=Main:/user/public-user/Utili
 ties/Main
X-BEDEWORK-SPEAKER:TBD
X-BEDEWORK-DUKE-SERIES:Friday Seminar in the department of Statistical Sci
 ence
X-BEDEWORK-SUBMITTEDBY:ek217 for Statistical Science (agrp_StatisticalScie
 nce)
X-BEDEWORK-STUDENT-CONTACT;X-BEDEWORK-PARAM-EMAIL=statsci-friday-seminars@
 duke.edu:StatSci Friday Seminars
EXDATE:20260306T203000Z
EXDATE:20260313T193000Z
EXDATE:20260320T193000Z
END:VEVENT
BEGIN:VEVENT

RECURRENCE-ID;TZID=America/New_York:20260213T203000Z
CATEGORIES:Utilities
CATEGORIES:Main
CONTACT;X-BEDEWORK-UID=00f1fcdb-0f068baf-010f-068baf83-00000004:None
CREATED:20260122T165024Z
DESCRIPTION:TBD
DURATION:PT1H
DTSTAMP:20260209T145752Z
DTSTART;TZID=America/New_York:20260213T153000
LAST-MODIFIED:20260209T145752Z
LOCATION;X-BEDEWORK-UID=18832edc-1b27e154-011b-28365daf-0000006c:Old Chemi
 stry 116
STATUS:CONFIRMED
SUMMARY:Friday Seminar in the department of Statistical Science
UID:CAL-8a00eca5-9af98aae-019b-e69d42e9-00000e2fdemobedework@mysite.edu
X-BEDEWORK-ALIAS;X-BEDEWORK-PARAM-DISPLAYNAME=Main:/user/public-user/Utili
 ties/Main
X-BEDEWORK-SPEAKER:TBD
X-BEDEWORK-DUKE-SERIES:Friday Seminar in the department of Statistical Sci
 ence
X-BEDEWORK-SUBMITTEDBY:ek217 for Statistical Science (agrp_StatisticalScie
 nce)
X-BEDEWORK-STUDENT-CONTACT;X-BEDEWORK-PARAM-EMAIL=statsci-friday-seminars@
 duke.edu:StatSci Friday Seminars
EXDATE:20260306T203000Z
EXDATE:20260313T193000Z
EXDATE:20260320T193000Z
END:VEVENT
BEGIN:VEVENT

RECURRENCE-ID;TZID=America/New_York:20260220T203000Z
CATEGORIES:Utilities
CATEGORIES:Main
CONTACT;X-BEDEWORK-UID=00f1fcdb-0f068baf-010f-068baf83-00000004:None
CREATED:20260122T165024Z
DESCRIPTION:TBD
DURATION:PT1H
DTSTAMP:20260218T213537Z
DTSTART;TZID=America/New_York:20260220T153000
LAST-MODIFIED:20260218T213537Z
LOCATION;X-BEDEWORK-UID=18832edc-1b27e154-011b-28365daf-0000006c:Old Chemi
 stry 116
STATUS:CONFIRMED
SUMMARY:Friday Seminar in the department of Statistical Science
UID:CAL-8a00eca5-9af98aae-019b-e69d42e9-00000e2fdemobedework@mysite.edu
X-BEDEWORK-ALIAS;X-BEDEWORK-PARAM-DISPLAYNAME=Main:/user/public-user/Utili
 ties/Main
X-BEDEWORK-SPEAKER:TBD
X-BEDEWORK-DUKE-SERIES:Friday Seminar in the department of Statistical Sci
 ence
X-BEDEWORK-SUBMITTEDBY:ek217 for Statistical Science (agrp_StatisticalScie
 nce)
X-BEDEWORK-STUDENT-CONTACT;X-BEDEWORK-PARAM-EMAIL=statsci-friday-seminars@
 duke.edu:StatSci Friday Seminars
EXDATE:20260306T203000Z
EXDATE:20260313T193000Z
EXDATE:20260320T193000Z
END:VEVENT
BEGIN:VEVENT

RECURRENCE-ID;TZID=America/New_York:20260227T203000Z
CATEGORIES:Utilities
CATEGORIES:Main
CONTACT;X-BEDEWORK-UID=00f1fcdb-0f068baf-010f-068baf83-00000004:None
CREATED:20260122T165024Z
DESCRIPTION:TBD
DURATION:PT1H
DTSTAMP:20260218T213927Z
DTSTART;TZID=America/New_York:20260227T153000
LAST-MODIFIED:20260218T213927Z
LOCATION;X-BEDEWORK-UID=18832edc-1b27e154-011b-28365daf-0000006c:Old Chemi
 stry 116
STATUS:CONFIRMED
SUMMARY:Friday Seminar in the department of Statistical Science
UID:CAL-8a00eca5-9af98aae-019b-e69d42e9-00000e2fdemobedework@mysite.edu
X-BEDEWORK-ALIAS;X-BEDEWORK-PARAM-DISPLAYNAME=Main:/user/public-user/Utili
 ties/Main
X-BEDEWORK-SPEAKER:TBD
X-BEDEWORK-DUKE-SERIES:Friday Seminar in the department of Statistical Sci
 ence
X-BEDEWORK-SUBMITTEDBY:ek217 for Statistical Science (agrp_StatisticalScie
 nce)
X-BEDEWORK-STUDENT-CONTACT;X-BEDEWORK-PARAM-EMAIL=statsci-friday-seminars@
 duke.edu:StatSci Friday Seminars
EXDATE:20260306T203000Z
EXDATE:20260313T193000Z
EXDATE:20260320T193000Z
END:VEVENT
BEGIN:VEVENT

RECURRENCE-ID;TZID=America/New_York:20260327T153000
CATEGORIES:Utilities
CATEGORIES:Main
CONTACT;X-BEDEWORK-UID=00f1fcdb-0f068baf-010f-068baf83-00000004:None
CREATED:20260122T165024Z
DESCRIPTION:Random measures are a key component of many nonparametric mode
 ls in Bayesian Statistics. Their infinite-dimensionality guarantees remar
 kable flexibility and generality but makes the investigation of theoretic
 al and inferential properties more demanding. In this talk we underline h
 ow several of these properties can be investigated through suitable dista
 nces between the laws of the random measures. Some crucial desiderata for
  such distances are metrization of weak convergence\, numerical estimatio
 n through samples\, and tractability of analytical bounds: we achieve the
 m by relying on optimal transport and integral probability metrics. Appli
 cations of our findings include measuring dependence in Bayesian nonparam
 etric models\, defining merging rates of opinions\, developing two-sample
  tests for measure-valued data\, and quantifying the error in approximate
  posterior inference.
DURATION:PT1H
DTSTAMP:20260323T162828Z
DTSTART;TZID=America/New_York:20260327T153000
LAST-MODIFIED:20260323T162828Z
LOCATION;X-BEDEWORK-UID=18832edc-1b27e154-011b-28365daf-0000006c:Old Chemi
 stry 116
STATUS:CONFIRMED
SUMMARY:Distances on Random Measures for Bayesian Nonparametrics
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