World's Best Scientists 2026 revealed!
Usama M. Fayyad

Usama M. Fayyad

D-Index & Metrics

Computer Science

D-Index
63
Citations
43021
World Ranking
2669
National Ranking
1324

Research.com Recognitions

  • 2006 - ACM Fellow For contributions to machine learning, data mining and knowledge discovery.
  • 2005 - Fellow of the Association for the Advancement of Artificial Intelligence (AAAI) For significant research contributions to machine learning, data mining and KDD, exceptional service in founding a new AI subfield/community, and for successfully fielding and commercializing AI and KDD technologies.

Overview

Usama M. Fayyad is affiliated with Open Insights in the United States. Their research spans several areas within computer science, focusing particularly on management information systems, artificial intelligence, health informatics, safety research, and management science and operations research.

The scientist has contributed to multiple main topics, including:

  • Big Data and Business Intelligence
  • Artificial Intelligence in Healthcare and Education
  • Ethics and Social Impacts of AI
  • Explainable Artificial Intelligence (XAI)
  • Data Quality and Management
  • Big Data Technologies and Applications
  • Machine Learning and Data Classification

Fayyad's recent publications include the following papers:

  • Analytics and Data Science Standardization and Assessment Framework, 2020, Harvard Data Science Review
  • From Stochastic Parrots to Intelligent Assistants-The Secrets of Data and Human Interventions, 2023, IEEE Intelligent Systems
  • From Unicorn Data Scientist to Key Roles in Data Science: Standardizing Roles, 2022, Harvard Data Science Review
  • How Can We Train Data Scientists When We Can't Agree on Who They Are?, 2021, Harvard Data Science Review

They have also co-authored with several frequent collaborators:

  • Hamit Hamutcu
  • Padhraic Smyth
  • Jia Li
  • Guang Cheng
  • Ranjan Maitra

Publication venues that frequently feature their work include:

  • Harvard Data Science Review
  • IEEE Intelligent Systems
  • Statistical Analysis and Data Mining The ASA Data Science Journal
  • Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining

In addition to journal articles, Usama M. Fayyad has contributed a book published by Springer Science+Business Media titled Advances in Knowledge Discovery and Data Mining (2021).

Awards received by the scientist include:

  • ACM Fellow (2006) for contributions to machine learning, data mining and knowledge discovery
  • Fellow of the Association for the Advancement of Artificial Intelligence (AAAI) (2005) for significant research contributions to machine learning, data mining and KDD, exceptional service in founding a new AI subfield/community, and commercialization of AI and KDD technologies

Best Publications

  • From Data Mining to Knowledge Discovery in Databases

    Usama M. Fayyad;Gregory Piatetsky-Shapiro;Padhraic Smyth

  • Multi-Interval Discretization of Continuous-Valued Attributes for Classification Learning

    Usama M. Fayyad;Keki B. Irani

  • The KDD process for extracting useful knowledge from volumes of data

    Usama Fayyad;Gregory Piatetsky-Shapiro;Padhraic Smyth

  • From data mining to knowledge discovery: an overview

    Usama M. Fayyad;Gregory Piatetsky-Shapiro;Padhraic Smyth

  • Refining Initial Points for K-Means Clustering

    Paul S. Bradley;Usama M. Fayyad

  • Knowledge discovery and data mining: towards a unifying framework

    Usama Fayyad;Gregory Piatetsky-Shapiro;Padhraic Smyth

  • On the Handling of Continuous-Valued Attributes in Decision Tree Generation

    Usama M. Fayyad;Keki B. Irani

  • Scaling clustering algorithms to large databases

    P. S. Bradley;Usama Fayyad;Cory Reina

  • Information Visualization in Data Mining and Knowledge Discovery

    Usama Fayyad;Georges G. Grinstein;Andreas Wierse

  • Hierarchical Clustering Algorithms for Document Datasets

    Ying Zhao;George Karypis;Usama Fayyad

  • Data mining and knowledge discovery in databases

    Usama Fayyad;Ramasamy Uthurusamy

  • Proceedings of the Second International Conference on Knowledge Discovery and Data Mining

    Evangelos Simoudis;Jiawei Han;Usama Fayyad

  • Inferring Ground Truth from Subjective Labelling of Venus Images

    Padhraic Smyth;Usama M. Fayyad;Michael C. Burl;Pietro Perona

  • Mathematical Programming for Data Mining: Formulations and Challenges

    P. S. Bradley;Usama M. Fayyad;O. L. Mangasarian

  • Evolving data into mining solutions for insights

    Usama Fayyad;Ramasamy Uthurusamy

  • The attribute selection problem in decision tree generation

    Usama M. Fayyad;Keki B. Irani

  • Data mining and KDD: promise and challenges

    Usama Fayyad;Paul Stolorz

  • Initialization of iterative refinement clustering algorithms

    Usama Fayyad;Cory Reina;P. S. Bradley

  • Mining scientific data

    Usama Fayyad;David Haussler;Paul Stolorz

  • On the handling of continuous-valued attributes in decision tree generation

    Unknown

  • Knowledge discovery in databases: An overview

    Usama Fayyad

  • The KDD process for extracting useful knowledge from volumes of data : Data mining and knowledge discovery in databases

    U. Fayyad;G. Piatetsky-Shapiro;P. Smyth

Frequent Co-Authors

Padhraic Smyth
Padhraic Smyth University of California, Irvine
S. G. Djorgovski
S. G. Djorgovski California Institute of Technology
Surajit Chaudhuri
Surajit Chaudhuri Microsoft (United States)
Michael C. Burl
Michael C. Burl Jet Propulsion Lab
Pietro Perona
Pietro Perona California Institute of Technology
Alexander G. Gray
Alexander G. Gray Georgia Institute of Technology
Andrew Tomkins
Andrew Tomkins Google (United States)
David Haussler
David Haussler University of California, Santa Cruz
Jiawei Han
Jiawei Han University of Illinois at Urbana-Champaign
John E. Laird
John E. Laird University of Michigan–Ann Arbor

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 online degrees in Computer Science opens up a variety of career pathways and possibilities. Many students are interested in short careers that pay well, making accelerated or specialized programs appealing for those seeking quick workforce entry and strong earning potential.

Budget-conscious learners often look for affordable degree options. For those interested in cutting-edge fields, there are various cheapest online masters in artificial intelligence that combine cost-effectiveness with high-demand AI expertise.

Choosing the right major can shape future opportunities. Some of the top degrees for the future include technology, data science, and engineering—all highly relevant to Computer Science students considering online study options.

If balancing school with work or other responsibilities is important, learners may consider programs recognized as some of the easy masters programs. These can offer flexibility and manageable coursework while still advancing career goals in tech and related fields.

Best Scientists Citing Usama M. Fayyad

Trending Scientists

Recently Published Articles