Skip to content. | Skip to navigation

Personal tools


You are here: Home / Coming Up / Seminar Series: Partha Lahiri, Joint Program in Survey Methodology and Mathematics

Seminar Series: Partha Lahiri, Joint Program in Survey Methodology and Mathematics

Big Data, Big Promise, Big Challenge: Can Small Area Estimation Play a Role in the Big Data Centric World?
When Apr 18, 2016
from 12:00 PM to 01:00 PM
Where 1208 LeFrak Hall
Contact Name
Contact Phone 301-405-6403
Attendees Afnan Al-Ibrahim
Hsiang-Yuan Ho
Omkar Joshi
Mary Jung
Zhiyong Lin
Xiaohong Ma
Sangeetha Madhavan
Léa Pessin
Michael S. Rendall
Basheer M. Saeed
Liana Sayer
Matthew Staiger
Reeve Vanneman
Gregory White
Add event to calendar vCal

About the Talk

The demand for various socio-economic, transportation, and health statistics for small geographical areas is steadily increasing at a time when survey agencies are desperately looking for ways to reduce costs to meet fixed budgetary requirements.  In the current survey environment, the application of standard sample survey methods for small areas, which require a large sample, is generally not feasible when considering the costs.    One of the key factors that lead to the success of small area estimation (SAE) methodology is the availability of strong auxiliary variables.  The accessibility of big data from different sources is now bringing new opportunities for statisticians to develop innovative SAE methods.  In this talk, I will provide an outline of how SAE methods can be adapted to incorporate big data in improving local area statistics.  Then I will discuss my recent collaboration with my UMD colleagues --- Professor Cinzia Cirillo of Department of Civil and Environmental Engineering, and Professor Joseph JaJa of Department of Electrical and Computer Engineering, and the University of Maryland Institute for Advanced Computer Studies (UMIACS).  Finally, as an example from our different collaborative research projects, I will explain how SAE can help solve a seemingly different problem of predicting in real-time traffic by exploiting rich vehicle probe big data. 

About the Speaker

Dr. Partha Lahiri is a Professor of Survey Methodology and Mathematics at the University of Maryland, College Park and an Adjunct Research Professor at the Institute of Social Research, University of Michigan, Ann Arbor.  Before coming to Maryland, Dr. Lahiri was the Milton Mohr Distinguished Professor of Statistics at the University of Nebraska-Lincoln. His research interests include big data, Bayesian statistics, record linkage, and small-area estimation.  Dr. Lahiri has served on a number of advisory committees, including the U.S. Census Advisory committee and U.S. National Academy panel.  Over the years Dr. Lahiri advised various local and international organizations such as the United Nations Development Program, the World Bank, and the Gallup Organization.  He is a Fellow of the American Statistical Association and the Institute of Mathematical Statistics and an elected member of the International Statistical Institute.

Visit Professor Lahiri's webpage

Filed under:
« May 2024 »