2026 Gediminas Adomavicius: Computer Science Researcher – H-Index, Publications & Awards

Discipline name	D-Index	World Ranking	Current World Ranking	National Ranking	Current National Ranking	Publications	Citations
Computer Science	52	4940	4804	2294	2215	162	30649

Overview

Gediminas Adomavičius is affiliated with the University of Minnesota in the United States. Their research spans multiple fields including Computer Science and Decision Sciences, with a focus on subfields such as Management Science and Operations Research, Information Systems, Marketing, Electrical and Electronic Engineering, and Artificial Intelligence.

The scientist's work has concentrated on several main topics including Recommender Systems and Techniques, Consumer Market Behavior and Pricing, Advanced Bandit Algorithms Research, Auction Theory and Applications, Decision-Making and Behavioral Economics, Smart Grid Energy Management, and Explainable Artificial Intelligence (XAI).

Frequent publication venues for Gediminas Adomavičius encompass:

SSRN Electronic Journal
arXiv (Cornell University)
Information Systems Research
INFORMS journal on computing
User Modeling and User-Adapted Interaction

Key recent papers include:

"Multistakeholder recommendation: Survey and research directions," 2020, User Modeling and User-Adapted Interaction
"Consumption and Performance: Understanding Longitudinal Dynamics of Recommender Systems via an Agent-Based Simulation Framework," 2020, Information Systems Research
"Improving Sales Forecasting Accuracy: A Tensor Factorization Approach with Demand Awareness," 2022, INFORMS journal on computing
"Integrating Behavioral, Economic, and Technical Insights to Understand and Address Algorithmic Bias: A Human-Centric Perspective," 2022, ACM Transactions on Management Information Systems
"Effects of Personalized Recommendations Versus Aggregate Ratings on Post-Consumption Preference Responses," 2022, MIS Quarterly

Gediminas Adomavičius has collaborated frequently with several coauthors, including Mochen Yang, Jingjing Zhang, Shawn P. Curley, Xuan Bi, and Robin Burke. The number of joint publications with these coauthors ranges from four to ten.

Best Publications

Toward the next generation of recommender systems: a survey of the state-of-the-art and possible extensions

G. Adomavicius;A. Tuzhilin

14520
Citations
Context-Aware Recommender Systems

Gediminas Adomavicius;Bamshad Mobasher;Francesco Ricci;Alexander Tuzhilin

2828
Citations
Incorporating contextual information in recommender systems using a multidimensional approach

Gediminas Adomavicius;Ramesh Sankaranarayanan;Shahana Sen;Alexander Tuzhilin

1733
Citations
Selecting content for a user

Alexander S. Tuzhilin;Gediminas Adomavicius

1235
Citations
Improving Aggregate Recommendation Diversity Using Ranking-Based Techniques

G. Adomavicius;YoungOk Kwon

871
Citations
New Recommendation Techniques for Multicriteria Rating Systems

G. Adomavicius;YoungOk Kwon

694
Citations
Personalization technologies: a process-oriented perspective

Gediminas Adomavicius;Alexander Tuzhilin

538
Citations
Using data mining methods to build customer profiles

G. Adomavicius;A. Tuzhilin

429
Citations
Multi-Criteria Recommender Systems

Gediminas Adomavicius;YoungOk Kwon

384
Citations
Making sense of technology trends in the information technology landscape: a design science approach

Gediminas Adomavicius;Jesse C. Bockstedt;Alok Gupta;Robert J. Kauffman

344
Citations
Context-aware recommender systems

Gediminas Adomavicius;Alexander Tuzhilin

319
Citations
A Parallel Multilevel Method for Adaptively Refined Cartesian Grids with Embedded Boundaries

M. J. Aftosmis;M. J. Berger;G. Adomavicius

317
Citations
Do Recommender Systems Manipulate Consumer Preferences? A Study of Anchoring Effects

Gediminas Adomavicius;Jesse C. Bockstedt;Shawn P. Curley;Jingjing Zhang

289
Citations
Multistakeholder recommendation: Survey and research directions

Himan Abdollahpouri;Gediminas Adomavicius;Robin Burke;Ido Guy

287
Citations
Expert-Driven Validation of Rule-Based User Models in Personalization Applications

Gediminas Adomavicius;Alexander Tuzhilin

272
Citations
Understanding User-Generated Content and Customer Engagement on Facebook Business Pages

Mochen Yang;Yuqing Ren;Gediminas Adomavicius

256
Citations
Technology roles and paths of influence in an ecosystem model of technology evolution

Gediminas Adomavicius;Jesse C. Bockstedt;Alok Gupta;Robert J. Kauffman

214
Citations
User profiling in personalization applications through rule discovery and validation

Gediminas Adomavicius;Alexander Tuzhilin

210
Citations
Recommendations with a Purpose

Dietmar Jannach;Gediminas Adomavicius

205
Citations
Impact of data characteristics on recommender systems performance

Gediminas Adomavicius;Jingjing Zhang

178
Citations
CEUR Workshop Proceedings

Gediminas Adomavicius;Young Ok Kwon

52
Citations
Personalization technologies: A process-oriented perspective

D. Adomavicius;A. Tuzhilin

48
Citations

Frequent Co-Authors

Alexander Tuzhilin New York University

Alok Gupta University of Minnesota

Dietmar Jannach University of Klagenfurt

Bamshad Mobasher DePaul University

Joseph A. Konstan University of Minnesota

Martin Bichler Technical University of Munich

Robin Burke University of Colorado Boulder

Francesco Ricci Free University of Bozen-Bolzano

Robert J. Kauffman Singapore Management University

Yehuda Koren Google (United States)

External Links

Personal website of Gediminas Adomavicius Google Scholar page

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