Analytics, Information, Operations research

Research information
The Analytics, Information, Operations (AIO) academic area includes faculty who are experts in topics such as business analytics, information systems and supply chain management, as well as former industry professionals whose experience supplements our curriculum.
AIO faculty regularly publish in leading academic journals and lend their expertise to regional and national media. Their intellectual contributions generate new knowledge and understanding, particularly as industries continue to rely more heavily on data-driven decision making.
In the Media
Inbound Logistics
What's the difference between supply chain visibility and transparency?
Recent AIO research & news

Corporate victims of ransomware may make matters worse by paying attackers, study finds
In a new study, University of Kansas business researcher Debabrata Dey examines when organizations accede to ransomware payment demands and, in doing so, incentivize attackers to launch more attacks, elevating the chance of a future breach not just for themselves but for others.

Profit motivation of social media companies may compel them to inject bias and create polarization, study finds
Social media companies thrive on the subtle influencing of users’ behavior. “It is of interest to social media companies to nudge users in such a way that their engagement level increases, but as a result, echo chambers are created and the level of polarization increases,” said Debabrata Dey, a professor of business at the University of Kansas.

Airlines can improve travel efficiency and resilience by incorporating passenger-level data, study finds
Mazhar Arikan, associate professor of business at the University of Kansas, explores how airlines that incorporate passenger-level data along with flight-level data could make modest adjustments in passenger itineraries that result in major travel improvements without significantly deteriorating efficiency.

Human values and expertise improve AI reliability, study finds
In a new paper, Michael Lash, assistant professor of business at the University of Kansas, proposes a novel approach for incorporating human experts in machine learning models. This increases reliance, trusting and sense-making of the explanations returned by artificial intelligence.
Area directors

Debabrata "Deb" Dey
Davis Area Director, Analytics, Information, Operations, Ronald G. Harper Professor of Artificial Intelligence and Information Systems

Detelina Stoyanova
Assistant Area Director, Analytics, Information, Operations, Associate Teaching Professor
Analytics, Information, Operations faculty

Weimar Ardila-Rueda
Assistant Teaching Professor

Mazhar Arikan
Associate Professor, Anderson Family Fellow

Trambak Banerjee
Assistant Professor

Mark Best
Lecturer

Burcu Bolukbasi Arikan
Lecturer

Soudipta Chakraborty
Assistant Professor

Andrew N. K. Chen
Professor

Wei Chen
Associate Professor

Arunima Chhikara
Assistant Professor

Lidan Fan
Assistant Teaching Professor
Anurag Garg
Assistant Professor

Gilbert Karuga
Associate Professor

Michael Lash
Assistant Professor

Shaobo Li
Associate Professor

Suman Mallik
B. Allen and Dorothy V. Lay Professor

Mohammad Murad
Assistant Teaching Professor

Thomas "Tom" Patton
Professor of the Practice

Sara Reed
Assistant Professor

Jim Ritchie
Lecturer

Brady Rothrock
Lecturer

Brian R. Salmans
Associate Teaching Professor, Area Industry Mentor, AIO

Nagarajan "Naga" Sethuraman
Assistant Professor

Ben Sherwood
Associate Professor, Jack and Shirley Howard Mid-Career Professor

Karthik Srinivasan
Assistant Professor

Arvind Tripathi
Associate Professor

Joe Walden
Associate Teaching Professor

Jide Wintoki
Dean, Henry D. Price Professor

Jeff Zoroya
Lecturer, Area Industry Mentor, AIO