World's Best Scientists 2026 revealed!
Bamshad Mobasher

Bamshad Mobasher

D-Index & Metrics

Computer Science

D-Index
78
Citations
30156
World Ranking
1178
National Ranking
624

Overview

Bamshad Mobasher is affiliated with DePaul University in the United States and specializes in research within the field of Computer Science. Their academic work focuses extensively on areas including Information Systems, Artificial Intelligence, Management Science and Operations Research, Sociology and Political Science, as well as Economics and Econometrics.

Their main topics of research span several distinct areas:

  • Recommender Systems and Techniques
  • Advanced Bandit Algorithms Research
  • Sports Analytics and Performance
  • Artificial Intelligence in Games
  • Digital Games and Media
  • Consumer Market Behavior and Pricing
  • Gambling Behavior and Treatments

Mobasher has frequently published in specialized venues, with numerous contributions to arXiv (Cornell University), alongside publications in ACM SIGIR Forum, ACM Transactions on Information Systems, User Modeling and User-Adapted Interaction, and Companion Proceedings of the Web Conference 2021.

Representative recent papers include:

  • A Graph-Based Approach for Mitigating Multi-Sided Exposure Bias in Recommender Systems, 2021, ACM Transactions on Information Systems
  • Research directions in session-based and sequential recommendation, 2020, User Modeling and User-Adapted Interaction
  • Toward the Next Generation of News Recommender Systems, 2021, Companion Proceedings of the Web Conference 2021
  • Unbiased Cascade Bandits: Mitigating Exposure Bias in Online Learning to Rank Recommendation, 2021, arXiv (Cornell University)
  • Addressing the Multistakeholder Impact of Popularity Bias in Recommendation Through Calibration, 2020, arXiv (Cornell University)

Collaborations have been a significant part of their research output. Frequent coauthors include Masoud Mansoury, Arman Dehpanah, Muheeb Faizan Ghori, Jonathan Gemmell, and Himan Abdollahpouri. The number of joint publications with these coauthors ranges from eight to fourteen.

Best Publications

  • Context-Aware Recommender Systems

    Gediminas Adomavicius;Bamshad Mobasher;Francesco Ricci;Alexander Tuzhilin

  • Data Preparation for Mining World Wide Web Browsing Patterns

    Robert Cooley;Bamshad Mobasher;Jaideep Srivastava

  • Web mining: information and pattern discovery on the World Wide Web

    R. Cooley;B. Mobasher;J. Srivastava

  • Automatic personalization based on Web usage mining

    Bamshad Mobasher;Robert Cooley;Jaideep Srivastava

  • Discovery and Evaluation of Aggregate Usage Profiles for Web Personalization

    Bamshad Mobasher;Honghua Dai;Tao Luo;Miki Nakagawa

  • Personalized recommendation in social tagging systems using hierarchical clustering

    Andriy Shepitsen;Jonathan Gemmell;Bamshad Mobasher;Robin Burke

  • Effective personalization based on association rule discovery from web usage data

    Bamshad Mobasher;Honghua Dai;Tao Luo;Miki Nakagawa

  • Toward trustworthy recommender systems: An analysis of attack models and algorithm robustness

    Bamshad Mobasher;Robin Burke;Runa Bhaumik;Chad Williams

  • Data mining for web personalization

    Bamshad Mobasher

  • Semantically enhanced Collaborative Filtering on the Web

    Bamshad Mobasher;Xin Jin;Yanzan Zhou

  • Intelligent Techniques for Web Personalization

    Sarabjot Singh Anand;Bamshad Mobasher

  • Web search personalization with ontological user profiles

    Ahu Sieg;Bamshad Mobasher;Robin Burke

  • A Framework for the Evaluation of Session Reconstruction Heuristics in Web-Usage Analysis

    Myra Spiliopoulou;Bamshad Mobasher;Bettina Berendt;Miki Nakagawa

  • Integrating Web Usage and Content Mining for More Effective Personalization

    Bamshad Mobasher;Honghua Dai;Tao Luo;Yuqing Sun

  • Creating adaptive Web sites through usage-based clustering of URLs

    B. Mobasher;R. Cooley;J. Srivastava

  • Controlling Popularity Bias in Learning-to-Rank Recommendation

    Himan Abdollahpouri;Robin Burke;Bamshad Mobasher

  • Grouping Web page references into transactions for mining World Wide Web browsing patterns

    R. Cooley;B. Mobasher;J. Srivastava

  • Partitioning-based clustering for Web document categorization

    Daniel Boley;Maria Gini;Robert Gross;Eui-Hong Han

  • Context-aware music recommendation based on latenttopic sequential patterns

    Negar Hariri;Bamshad Mobasher;Robin Burke

  • Clustering Based on Association Rule Hypergraphs

    Eui-Hong Han;George Karypis;Vipin Kumar;Bamshad Mobasher

  • Context-aware recommender systems

    Gediminas Adomavicius;Alexander Tuzhilin

Frequent Co-Authors

Robin Burke
Robin Burke University of Colorado Boulder
Maria Gini
Maria Gini University of Minnesota
Olfa Nasraoui
Olfa Nasraoui University of Louisville
Myra Spiliopoulou
Myra Spiliopoulou Otto-von-Guericke University Magdeburg
Jane Cleland-Huang
Jane Cleland-Huang University of Notre Dame
Jaideep Srivastava
Jaideep Srivastava University of Minnesota
Dietmar Jannach
Dietmar Jannach University of Klagenfurt
Alexander Tuzhilin
Alexander Tuzhilin New York University
Mykola Pechenizkiy
Mykola Pechenizkiy Eindhoven University of Technology

If you think any of the details on this page are incorrect, let us know.

Report an issue

We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below:

Related Online Degrees & Career Pathways

Exploring Computer Science in the USA opens the door to many flexible study options, especially for those seeking online education. If you’re looking to jumpstart your career quickly, a degree in 6 months online can offer foundational skills and credentials in a short time frame. These accelerated programs are ideal for motivated learners eager to enter the tech workforce rapidly.

For those interested in broader business or interdisciplinary roles, online business degree programs accredited by reputable institutions also provide tech-focused tracks, combining management skills with IT knowledge. This can expand your career options in both business and technical fields.

Budget-conscious students can consider affordable online bachelor degree programs that offer reliable quality without breaking the bank. These programs are flexible, allowing you to balance studies with other commitments.

Finally, if you’re drawn to applied engineering, several engineering degrees online provide a strong alternative or complement to Computer Science degrees, opening pathways in industries like robotics, telecommunications, and more.

Best Scientists Citing Bamshad Mobasher

Trending Scientists

Recently Published Articles