RAL

National Academies Board on Human-System Integration

Heng Xu will join leaders in science, engineering, and industry to serve on the Board on Human-Systems Integration, National Academies of Science, Engineering, and Medicine. The board was established in...

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)...

CES APA Panel on What Firms Need to Know about Privacy

Heng Xu joined a panel of experts hosted by the American Psychological Association (APA) at CES 2024 to discuss about what companies need to know about how people understand privacy....

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,...

Working Paper - Theorizing about the Complexity of Privacy Phenomena - A Configurational Approach

We posted on SSRN a working paper by Heng Xu and Nan Zhang, addressing challenges facing the theorization of complex privacy phenomena.

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...

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...

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....

Nature Forum on Empowering Data as a New Asset

In an upcoming Nature Conference, Forum on Empowering Data as A New Asset, Heng Xu will join a panel of industry leaders, data economists and policy makers to discuss about...

Working Paper - Fairness of Ratemaking for Catastrophe Insurance

We posted on SSRN a working paper by Nan Zhang and Heng Xu, addressing the problem of fair ratemaking in catastrophe insurance.

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...

Privacy Measurement Project

We gratefully acknowledge Meta Research for their generous support of our project “Addressing biases in measurement of self-reported privacy constructs”, which was selected as part of the 2021 People’s Expectations...

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.

RSA Conference Panel on "AI meets cybersecurity"

In an upcoming RSA Conference webcast, Heng Xu will join a panel of experts to discuss “AI meets cybersecurity: crossing the streams and how to manage the dynamic results”.

Fairness in AI Project

We gratefully acknowledge the National Science Foundation and Amazon for their generous support of our project “Using Machine Learning to Address Structural Bias in Personnel Selection”, which was selected as part of the NSF Program on Fairness in Artificial Intelligence...

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.

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....

Panel on Using Sensitive Data to Counter Bias and Discrimination

Heng Xu, co-director of the Robust Analytics Lab, will join a panel of experts discussing the use of sensitive data in research to counter hidden bias and discrimination at the...

Upcoming Talk at UCSD Health

Heng Xu and Nan Zhang, co-directors of the Robust Analytics Lab, will give a (virtual) presentation at the University of California San Diego Health Department of Biomedical Informatics (DBMI) lecture...

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...

Working Paper - Implications of Data Anonymization on the Statistical Evidence of Disparity

We posted on SSRN a working paper by Heng Xu and Nan Zhang, addressing the implications of data anonymization on the statistical evidence of disparity.

Facebook Live: COVID-19's Implications for Cybersecurity

Update: See Kogod News for a report of the event.

Upcoming Talk at Harvard Privacy Tools Working Group

Heng Xu and Nan Zhang, co-directors of the Robust Analytics Lab, will give a (virtual) presentation to the Harvard Privacy Tools project working group, Berkman Klein Center for Internet &...

Working Paper - From Contextualizing to Context-Theorizing in Privacy Research

We posted on SSRN a working paper co-authored by Heng Xu and Nan Zhang, “From Contextualizing to Context-Theorizing: Assessing Context Effects in Privacy Research”.

Robustness in Social Media Studies

On Tuesday, February 4, Nan Zhang gave a talk on robustness in social media studies at DAISY 2020, a Workshop on Trans-disciplinary Data Science in the University of Florida. The...

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...

Postdoc Opening

The Robust Analytics Lab in the Kogod School of Business at the American University in Washington, D.C. is looking for an exceptional candidate to fill a postdoctoral fellow position. The initial term of this position is one year with the...

Theore - DARPA Project

We gratefully acknowledge the Defense Advanced Research Projects Agency (DARPA) for their support on our project “Theore: Theory-Driven Curation and Reusable Evaluation of Research Claims in social and behavioral studies”.

Panel on Methodological Advances for Research Using Organic Data @ SIOP 2019

Heng Xu and Nan Zhang participated as panelists in discussions of the recent methodological developments in research using organic data, a panel at SIOP 2019 organized by Professor Betty Zhou...

Presentation on “Privacy Disparity” @ Data & Society

Heng Xu and Nan Zhang visited Data & Society Research Institute in New York City and discussed how various privacy preserving techniques may disproportionately suppress information for minorities or mask...

Panel on Cybersecurity Challenges and Opportunities

Heng Xu, co-director of the Robust Analytics Lab, will join a panel of expert discussing “Into the Cyber domain. A view from Academia and industry” at an Embassy of Italy’s...

Presentation on “Robust Data Analytics” @ AU Winter Academy Luncheon

Nan Zhang, co-director of the Robust Analytics Lab, gave a talk on robust data analytics at the American University’s inaugural Winter Academy Luncheon in Fort Lauderdale, Florida on Friday, March...

Kogod Business Briefing: Robust Analytics

Nan Zhang, co-director of the Robust Analytics Lab, discussed the importance of ensuring robustness in the data analytics process in Kogod Business Briefing on February 13, 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...

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...

Polishing Up Data Privacy Protections

Nan Zhang, co-director of the Robust Analytics Lab (RAL), was recently featured in Kogod News discussing the implications of data protection regulations like the European Union’s General Data Protection Regulation...

Key to Security and Privacy

Heng Xu, co-director of the Robust Analytics Lab (RAL), was recently featured in Kogod News discussing why cyber risk awareness is so essential, yet often lacking, for preventing data breaches....

AU Ed Talk: Data in the everyday

Heng Xu, co-director of the Robust Analytics Lab, will deliver one of the four AU Ed Talks in this year’s All American Weekend. Her talk, “Data in the Everyday”, will...

Privacy-Preserving Framework for Publishing Electronic Healthcare Records

In the 2018 Connections in Smart Health Workshop, Nan Zhang and collaborators presented a poster on their recent progress for an NSF-sponsored collaborative research project on “Privacy-Preserving Framework for Publishing...

Talk at UMD: Privacy Contextualization: the Good, the Bad, and the Ugly

Heng Xu, co-director of the Robust Analytics Lab, will give a talk at the iSchool, University of Maryland, College Park, titled “Privacy Contextualization: the Good, the Bad, and the Ugly”....

About Us

Robust Analytics Lab brings together an interdisciplinary team of researchers to understand the reliability and robustness of data analytics, particularly in the context of its complex interplay with societal issues such as privacy, disparity, fairness, freedom of information, etc. Our...

NSF Project: Robust Twitter Analytics

We gratefully acknowledge the National Science Foundation for their support on our project 1850605, “RR: Establishing and Boosting Confidence Levels for Empirical Research Using Twitter Data”.

NSF Project: Privacy Regrets in Smartphone Usage

We gratefully acknowledge the National Science Foundation for their support on our project 1801539, “SaTC: CORE: Medium: Situation-Aware Identification and Rectification of Regrettable Privacy Decisions”.

Sep 26: Cybersecurity & Privacy Forum: Bridging Research & Practice

Update: See the event re-cap article in Kogod News.

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...

Talk on Reliable Research in Business Workshop

Heng Xu and Nan Zhang, Co-directors of Robust Analytics Lab, recently gave a joint talk titled “Open Data + Robust Workflow: Towards Reproducible Empirical Research on Organic Data” in the...