publications

Goal Orientation for Fair Machine Learning Algorithms

A key challenge facing the use of Machine Learning (ML) in organizational selection settings (e.g., the processing of loan or job applications) is the potential bias against (racial and gender)...

Robust Analytics Lab Robust Analytics Lab
22 Jan 2024

Information privacy - Challenges and opportunities for technology and measurement

We recently published a book chapter, “Information privacy: Challenges and opportunities for technology and measurement”, in Technology and Measurement around the Globe edited by Drs. Louis Tay, Sang Eun Woo,...

Robust Analytics Lab Robust Analytics Lab
09 Nov 2023

An Onto-Epistemological Analysis of Information Privacy Research

Privacy is one of the most urgent issues associated with the advancement of information technology. Yet, there is a growing concern that the issues surrounding privacy have been too complex...

Robust Analytics Lab Robust Analytics Lab
07 Sep 2023

Reducing Adverse Impact Through Machine Learning

Machine learning has emerged as a popular tool for personnel selection, leveraging data to enhance hiring processes. An article forthcoming at Personnel Psychology studies the potential of machine learning in...

Robust Analytics Lab Robust Analytics Lab
01 Jun 2023

Fair Ratemaking for Catastrophe Insurance

Catastrophe insurance is an important element of disaster management. Yet the historical presence of inequalities in insurance, from redlining to pricing disparity, has had a devastating impact on minority communities....

Robust Analytics Lab Robust Analytics Lab
07 Dec 2022

Why Privacy Still Matters

In the December 2022 issue of MIS Quarterly, Heng Xu and Tamara Dinev co-wrote a reflection, “Why Privacy Still Matters”, for their 2011 publication that won the inaugural MIS Quaterly Impact Award in 2021.

Heng Xu Heng Xu
01 Dec 2022

Organic Data and the Design of Studies

We recently published a book chapter, “Organic Data and the Design of Studies”, in collaboration with Dr. Le Zhou (University of Minnesota), in Data, Methods and Theory in the Organizational...

Robust Analytics Lab Robust Analytics Lab
01 Mar 2022

From Contextualizing to Context-Theorizing

In an article forthcoming at Management Science, we developed a conceptual framework and its associated methodological instantiation for assessing how context-oriented nuances influence privacy concerns.

Robust Analytics Lab Robust Analytics Lab
01 Sep 2021

Implications of Anonymization on Disparity Detection

In an article forthcoming at Management Science, we examined the extent to which data anonymization could mask the gross statistical disparities between sub-populations in the data.

Robust Analytics Lab Robust Analytics Lab
18 Jan 2021

Reconcile Paradoxical Findings Through an Analytical Lens

In an article forthcoming at MIS Quarterly, we launched an interdisciplinary inquiry into the feasibility of leveraging advanced analytical techniques to collectively reason about the conflicting findings in behavioral research....

Robust Analytics Lab Robust Analytics Lab
16 Jan 2021

CACM Research Highlight

In the research highlights section of the February 2021 issue, Communications of the ACM (CACM) published an article co-authored by Nan Zhang, “Scalable Signal Reconstruction for a Broad Range of Applications”.

Nan Zhang Nan Zhang
15 Jan 2021

Disentangling Effect Size Heterogeneity in Meta-analysis - A Latent Mixture Approach

An article co-authored by Nan Zhang, Mo Wang, and Heng Xu was recently accepted for publication at Psychological Methods. In the article, we leveraged the recent advances in theoretical machine...

Robust Analytics Lab Robust Analytics Lab
05 Sep 2020

Validity Concerns in Using Organic Data

An article co-authored by Heng Xu, Nan Zhang, and Le (Betty) Zhou was recently accepted for publication at the Journal of Management. In the article, we provide an overview of...

Robust Analytics Lab Robust Analytics Lab
12 Nov 2019

AMA Best Paper Award

Heng Xu and Nan Zhang recently received a Best Paper Award from the Consumer 360° Track of the 2019 American Marketing Association (AMA) Summer Academic Conference for paper “How Much Choice is Too Much? A Machine Learning Based Meta-Analysis of...

Robust Analytics Lab Robust Analytics Lab
12 Aug 2019

SIGMOD Research Highlight Award

Nan Zhang and coauthors (A. Asudeh, J. Augustine, A. Nazi, S. Thirumuruganathan, G. Das and D. Srivastava) recently received a Research Highlight Award from ACM SIGMOD for their paper “Efficient...

Nan Zhang Nan Zhang
11 Aug 2019

How your friends affect your privacy on Twitter

Among the existing solutions for protecting privacy on social media, a popular doctrine is privacy self-management, which asks users to directly control the sharing of their personal information through privacy...

Robust Analytics Lab Robust Analytics Lab
10 Jan 2019

Privacy disparity? Addressing privacy concerns in health disparity research

Background: Most research on identifying and understanding health disparities focused on measurement strategies and analytics design over administrative and survey data. What has received less attention, however, is the complex...

Robust Analytics Lab Robust Analytics Lab
14 Nov 2018

Heng Xu won the Operational Research Society’s Stafford Beer Medal for 2018

Heng Xu was recently awarded The Operational Research Society’s Stafford Beer Medal for 2018 for her paper:

Heng Xu Heng Xu
19 Oct 2018

SIGMOD 2019 Paper: Compact Data Representation with Bounded Rank Regret

Selecting the best items in a dataset is a common task in data exploration. However, the concept of “best” lies in the eyes of the beholder - different users may...

Nan Zhang Nan Zhang
15 Oct 2018

National Academies Report on Open Data

The National Academies of Sciences, Engineering, and Medicine today released a new report on “Open Science By Design: Realizing a Vision for 21st Century Research”, which introduces a framework of...

Heng Xu Heng Xu
16 Jul 2018