The focus is on the statistical analysis of non-Euclidean data, where random objects denote random variables and data samples that take values in general metric spaces. Data of such general type are increasingly prevalent in statistics and machine learning. The workshop covers theory, methodology and applications, with emphasis on applications to brain connectomics. Methodology for metric statistics is aimed at samples of networks, distributions, compositional data, covariance matrices and surfaces, tree data and data on manifolds, as well as complex Euclidean data such as high-dimensional and functional data that can be viewed as elements of a metric space.
Topics of interest include quantification of means, barycenters and variance and conditional Fréchet means and their implementation by regression models such as Fréchet regression and its variants. The workshop will also cover extensions of metric statistics and the analysis of random objects towards metric versions of principal component analysis, uncertainty quantification, deep learning, causal inference and longitudinal and time series methodology.
Lightning Talks and Poster Session
This workshop will include lightning talks and a poster session for early career researchers (including graduate students). If accepted, you will be asked to do both. In order to propose a lightning session talk and a poster, you must first register for the workshop, and then submit a proposal using the form that will become available on this page after you register. The registration form should not be used to propose a lightning session talk or poster.
The deadline for proposing is September 30, 2026. If your proposal is accepted, you should plan to attend the event in-person.
In-Person Registration
Seats are limited at the venue, which means that in-person registration may be capped prior to the workshop start date. If capacity is reached, a waitlist will be imposed, which the registration form will reflect. Early registration is strongly encouraged.
All in-person registrants must wait to receive an invitation to attend in-person from IMSI before traveling, which generally begin to be sent out 4-6 weeks in advance.
All registrants (online and in-person) will receive zoom links and are welcome to attend online.
Registration Fee
A non-refundable registration fee will be payable by credit card or debit card for any participants invited to attend this workshop in-person. In-person participants agree to pay the non-refundable fee by the deadline given by IMSI. Failure to pay the fee by the deadline may mean that the invitation to attend in-person is revoked.
Daisuke Kuriso
University of Tokyo, Graduate School of Economics
K
L
Kuang-Yao Lee
Temple University
H
L
Hongzhe Li
University of Pennsylvania
E
L
Eardi Lila
University of Washington
Z
L
Zhenhua Lin
National University of Singapore
T
N
Tom Nye
University of Newcastle
B
P
Byeong Park
Seoul National University
A
P
Alex Petersen
Brigham Young University
X
S
Xiaofeng Shao
Washington University in St. Louis
B
S
Bharath Sriperumbudur
Pennsylvania State University
Z
Y
Zhigang Yao
National University of Singapore
H
Z
Hang Zhou
University of North Carolina
Y
Z
Yidong Zhou
University of California, Davis
C
Z
Changbo Zhu
University of Notre Dame
H
Z
Hongtu Zhu
University of North Carolina
V
Z
Vadim Zipunnikov
Johns Hopkins University
C
C
Changwon Choi
Seoul National University
Y
W
Yichao Wu
University of Illinois Chicago
R
O
Ryo Okano
University of Tokyo
Registration
IMSI is committed to making all of our programs and events inclusive and accessible.
Contact [email protected] to request
disability-related accommodations.
In order to register for this workshop, you must have an IMSI account and be logged in.