Research

Research Interests

Personalization and recommender systems, business intelligence, knowledge discovery and data mining, human-computer interactions 

Research Awards and Honors

• Women in RecSys Journal Paper of the Year Award (1st Place in Senior Category), ACM Conference on Recommender Systems, 2023 

• 2020 Best Published Paper Award, Information Systems Research (ISR), received in 2021

• ISS Sandra A. Slaughter Early Career Award, INFORMS Information Systems Society, 2020

• Best Student Paper Award, INFORMS Workshop on Data Science (DS), 2020

• Nominated for Indiana University Outstanding Junior Faculty Award, Indiana University, 2017 

• Nominated for Best Paper Award, Workshop on Information Technologies and Systems (WITS), 2016 

• Nominated for Best Paper Award, Conference on Information Systems and Technology (CIST), 2016 

• 3M Pre-Tenure Faculty Fellowship, Kelley School of Business, Indiana University, 2014, 2015, 2016 

• ISS Nunamaker-Chen Dissertation Award, INFORMS Information Systems Society, 2013

• Best Paper Award, Workshop on Information Technologies and Systems (WITS), 2011 

• Willoughby Fellowship in Management Information Systems, MIS Quarterly (MISQ), 2011

• McNamara Woman’s Fellowship, University of Minnesota, 2011 

• Ph.D. Dissertation Fellowship, Carlson School of Management, University of Minnesota, 2011-2012 

Journal Publications

1. "Longitudinal Impact of Preference Biases on Recommender Systems' Performance," (with Meizi Zhou and Gediminas Adomavicius), Information Systems Research, accepted. 

   • Best Student Paper Award,  INFORMS Workshop on Data Science, 2020

2. "Some Thoughts on Reviewing for Information Systems Research and Other Leading IS Journals," (with Sarker, S., Whitley, E., Goh, KY, Hong, Y., Mähring, M., Sanyal, P., Su, N., Xu, H., Xu, J., Zhao, H.), Information Systems Research (Editorial), forthcoming. 

3. "When Algorithms Err: Differential Impact of Early vs. Late Errors on Users' Reliance on Algorithms", (with Antino Kim, and Mochen Yang), ACM Transactions on Computer-Human Interactions, 30(1), 2023.

4. "Effects of Personalized versus Aggregate Recommendations on Consumer Preference Responses in Recommender Systems" (with Gediminas Adomavicius, Jesse Bockstedt, and Shawn Curley), MIS Quarterly (MISQ), 46(1), 627-643, 2022. 

5. "Recommender Systems, Ground Truth, Bias, and Preference Pollution" (with Gediminas Adomavicius, Jesse Bockstedt, and Shawn Curley), AI Magazine, 43(2), 177-189, 2022. 

6. “Effects of Personalized and Aggregate Top-N Lists on User Preference Ratings” (with Gediminas Adomavicius, Jesse Bockstedt, and Shawn Curley), ACM Transactions on Information Systems (TOIS), 39(2), 2021.

7. "Consumption and Performance: Understanding Longitudinal Dynamics of Recommender Systems Via An Agent-Based Simulation Framework" (with Gediminas Adomavicius, Alok Gupta, and Wolf Ketter), Information Systems Research, 31(1), 2020.

8. "Understanding the Impact of Individual Users’ Rating Characteristics on Predictive Accuracy of Recommender Systems" (with Xiaoye Cheng and Lucy Yan), INFORMS Journal on Computing (JOC), 32(2), 2020.

9. "Reducing Recommender Systems Biases: An Investigation of Display Designs" (with Gediminas Adomavicius, Jesse Bockstedt, and Shawn Curley), MIS Quarterly (MISQ), 43(4), 2019.

10. "Hidden Side Effects of Recommender Systems" (with Gediminas Adomavicius, Jesse Bockstedt, Shawn Curley, and Sam Ransbotham), MIT Sloan Management Review, 60(2), 2019.

11. "Effects of Online Recommendations on Consumers’ Willingness to Pay" (with Gediminas Adomavicius, Jesse Bockstedt, and Shawn Curley), Information Systems Research, 29(1), 2018.

12. "Exploring Explanation Effects on Consumers’ Trust in Online Recommender Agents" (with Shawn Curley), International Journal of Human-Computer Interaction (IJHCI), 34(5), 2018.

13. "Classification, Ranking, and Top-K Stability of Recommendation Algorithms" (with Gediminas Adomavicius), INFORMS Journal on Computing (JOC), 28(1), 2016. 

14. "Improving Stability of Recommender Systems: A Meta-Algorithmic Approach" (with Gediminas Adomavicius), IEEE Transactions on Knowledge and Data Engineering (TKDE), 27(6), 2015. 

    • Best Paper Award, Workshop on Information Technologies and Systems, 2011

15. "Do Recommender Systems Manipulate Consumer Preferences? A Study of Anchoring Effects" (with Gediminas Adomavicius, Jesse Bockstedt, and Shawn Curley), Information Systems Research, 24(4), 2013.

16. "Stability of Recommendation Algorithms" (with Gediminas Adomavicius), ACM Transactions on Information Systems (TOIS), 30(4), 2012. 

17. "Impact of Data Characteristics on Recommender Systems Performance" (with Gediminas Adomavicius), ACM Transactions on Management Information Systems (TMIS), 3(1), 2012.

Working Papers:

1. "It Takes Two to Tango: The Effects of Internal and External Information Integration on Healthcare Process and Outcomes" (with Hillol Bala, Xuan Feng, and Fujie Jin). 

2. "Incentive Schemes and Physician Engagement in Physician-Oriented Online Healthcare Community: A Regression Discontinuity Approach" (with Seyoung Seol, Lucy Yan, Hillol Bala, and Liuan Wang). 

3. "Impact of Recommender Systems on Consumers' Perceptions and Choice Behaviors" (with Xiaotong Sun and Alan Dennis). 

4. "Effects of Danmu on Content Contribution and Viewer Engagement on Short-Form Video Platforms" (with Xiaotong Sun and Fujie Jin).

5. "The Effect of Software Version Update Release on the Market Success of Mobile Applications: Free vs. Paid Apps" (with Fujie Jin and Vijay Khatri).

Early Research Theme: Healthcare Information Technologies 

1. “A Texture-Based Methodology for Identifying Tissue Type in Magnetic Resonance Images” (with Michael Barnathan, Erick Miranda, Vasileios Megalooikonomou, Scott Faro, Harvey Hensley, Luis Del Voile, Kamel Khalili, Jennifer Gordon, and Feroze Mohamed), IEEE International Symposium on Biomedical Imaging (ISBI’08), Paris, France, 2008, pp. 464-467. 

2. “Analyzing Tree-Like Structures in Biomedical Images Based on Texture and Branching: An Application to Breast Imaging” (with Michael Barnathan, Despina Kontos, Predrag Bakic, Andrew Maidment, and Vasileios Megalooikonomou), International Workshop on Digital Mammography (IWDM’08), Tucson, AZ, pp. 25-32, 2008. 

3. “A Web-Accessible Framework for Automated Storage and Texture Analysis of Biomedical Images” (with Michael Barnathan and Vasileios Megalooikonomou), IEEE International Symposium on Biomedical Imaging (ISBI’08), Paris, France, 2008, pp. 257-259. 

4. “An Effective and Efficient Technique for Searching for Similar Brain Activation Patterns” (with Vasileios Megalooikonomou), IEEE International Symposium on Biomedical Imaging (ISBI’07), Washington DC, 2007, pp. 428-431. 

5. “Analysis of Texture Patterns in Medical Images with an Application to Breast Imaging” (with Vasileios Megalooikonomou, Despina Kontos, and Predrag Bakic), SPIE Medical Imaging (SPIE’07), San Diego, CA, 2007.