2025 LiDS Conference

2025 Lifetime Data Science Conference
Lifetime Data Science and the World

The 4th Conference on Lifetime Data Science

New York Marriott at the Brooklyn Bridge

Brooklyn, New York, USA

May 28-30, 2025

The fourth Lifetime Data Science (LiDS) Conference is scheduled to take place from May 28 to May 30, 2025, at the New York Marriott at the Brooklyn Bridge in Brooklyn, NY. Under the theme 'Lifetime Data Science and the World,' the conference will host distinguished keynote speakers, including Drs. Nicholas P. Jewell and Mei-Ling Ting Lee, prominent figures in the field of survival analysis. The program will feature a day of short courses and two days of parallel invited sessions. A highlight of the event will be the banquet on May 29, 2025. In addition to being held at a top-tier venue, New York City is home to myriad world-class academic institutions, tech, and pharmaceutical companies, and health care organizations. Building on the success of previous LiDS conferences held in 2017, 2019, and 2023, we anticipate an engaging and informative event showcasing the latest advancements in lifetime data science research.

Registration

Registration for the 2025 Lifetime Data Science conference, short courses, and banquet is open through the following link:

Register for the 2025 LiDS Conference

The early-bird conference and short course registration rate will end on April 15, 2025. 

*For any questions about cancellations/refunds, please contact Clarissa Davis (clarissa@amstat.org). 

Conference Registration Rates:

Program Book and Schedule

The 2025 LiDS Conference program book is available here and a web version of the schedule is available here.

Accommodations

Rooms can be reserved at the New York Marriott at the Brooklyn Bridge with the discounted conference rate using the following links:

General Attendees

U.S. Government Employees (Choose "Government and Military" under the SPECIAL RATES tab)

Keynote Presentations

Current Status Data and Immortal Time Bias: Two Old Problems Revisited Nicholas P Jewell, University of California at Berkeley Current status data and immortal time bias are two (unrelated) problems that have long attracted interest from survival analysis researchers. This talk revisits these two problems, motivated by current day applications to Covid-19 data, and presents both questions and some solutions.

Longitudinal Survival Analysis and Neural Network Using First Hitting Time Regression  Mei-Ling Ting Lee, University of Maryland, College Park Disease progression in a patient can be described mathematically as a stochastic process. The patient experiences a failure event when his/her disease progression first reaches a critical threshold level. This happening defines the failure event itself and the first hitting time (FHT) is the event time. First hitting time threshold regression (TR) models incorporate regression functions for parameters of the underlying stochastic process. The TR models are intuitive and do not require the proportional hazards assumption, therefore represent a realistic alternative to the Cox model. Recently the TR model has been extended to the family of processes with stationary independent increments and a cumulant generating function. Using the Markov property of the stationary independent increments, the TR models can easily handle longitudinal time-to-event data.  I’ll demonstrate longitudinal threshold regression (LTR) and predictive inference using real data examples. Longitudinal threshold regression has also been extended to neural network applications.

The 2025 Lifetime Data Science conference is proudly sponsored by:

Gold Sponsor(s)
Silver Sponsor(s)
Bronze Sponsor(s)
Other Sponsor(s)
Charles B. Hall Professor, Division of Biostatistics, Department of Epidemiology and Population Health, Saul R. Korey Department of Neurology, Albert Einstein College of Medicine

Student Paper Competition

Award Description (Applications Closed)

Congratulations to the 2025 LiDS Conference Student Paper Competition Winners!

• Lingxuan Kong (University of Michigan), "Adaptive risk-weighted learning for optimizing kidney transplant decisions under resource constraints"
• Weidong Wang (University of Massachusetts Amherst), "Conformal prediction for time-to-event outcome subject to truncation"
• Yuxiang Wu (University of Missouri), "Conformal two sample conditional tests for survival comparison"

Poster Session (Student Poster Competition)

A poster session will be held with the Conference Opening Mixer (Wednesday, May 28, 6:30—8:30 pm). Any registered attendee can present a poster, although the poster competition is among student presenters. Those who wish to present a poster should email their proposed poster title to Dr. Dayu Sun (dayusun@iu.edu) by April 30, 2025.

Call for Invited Session Proposals (CLOSED)

The conference scientific program committee welcomes invited session proposals. An invited session consists of either 3 or 4 presenters, and the session proposal needs to provide a title, a short description of the session, and the information about the speakers, including their talk titles and abstracts, names, emails, and affiliations. The one-talk rule will be applied (i.e., each speaker can only give one invited talk). It is required to confirm all speakers’ availability before the proposal submission. Proposal submission is closed. The acceptance of invited sessions will be determined by August 31, 2024. In order to secure the invited session slot, the presenters will be required to register to the conference and submit the abstracts online by a deadline to be given later. For more information, please contact Scientific Program Committee Chair Professor (Tony) Jianguo Sun at sunj@missouri.edu or Co-Chair Professor Zhezhen Jin at zj7@cumc.columbia.edu.

Scientific Program Committee

(Tony) Jianguo Sun (Co-Chair, University of Missouri)

Zhezhen Jin (Co-Chair, Columbia University)

Din (Ding-Geng) Chen (Arizona State University)

Ming-Hui Chen (University of Connecticut)

Richard Cook (University of Waterloo)

Joan Hu (Simon Fraser University)

Esra Kurum (University of California, Riverside)

Ingrid Van Keilegom (KU Leuven)

Gang Li (University of California, Los Angeles)

Xuewen Lu (University of Calgary)

Wenbin Lu (North Carolina State University)

Edsel Peña (University of South Carolina)

Ryan Sun (University of Texas MD Anderson Cancer Center)

Mei-Cheng Wang (Johns Hopkins University)

Ronghui (Lily) Xu (University of California, San Diego)

Grace Y. Yi (University of Western Ontario)

Ying Zhang (University of Nebraska)

Bin Zhang (University of Cincinnati) 

Shanshan Zhao (National Institutes of Health)

Xingqiu Zhao (The Hong Kong Polytechnic University)

Yichuan Zhao (Georgia State University)

Qingning Zhou (University of North Carolina at Charlotte)

Local Organizing Committee

Wenbo Wu (Co-Chair, NYU Grossman School of Medicine)

Iván Díaz (Co-Chair, NYU Grossman School of Medicine)

Rebecca Betensky (NYU School of Global Public Health)

Zhonghua Liu (Columbia University Mailman School of Public Health)

Yuqi Gu (Columbia University)

Cuiling Wang (Albert Einstein College of Medicine)

Charles Hall (Albert Einstein College of Medicine)

Myeonggyun (Matt) Lee (NYU Grossman School of Medicine)

Michele Santacatterina (NYU Grossman School of Medicine and Google)

Online Platform Committee

Nicholas Hartman (Chair, University of Michigan)

Dayu Sun (Indiana University School of Medicine)

Wenbo Wu (NYU Grossman School of Medicine)

Program Book Committee

Dayu Sun (Chair, Indiana University School of Medicine)

Short Course Committee

Mengling Liu (NYU Grossman School of Medicine)

Myeonggyun (Matt) Lee (NYU Grossman School of Medicine)