2026 Rayid Ghani: Computer Science Researcher – H-Index, Publications & Awards

Overview

Rayid Ghani is affiliated with Carnegie Mellon University in the United States and conducts research primarily in the field of Computer Science, with a strong focus on Artificial Intelligence. Their scholarly work spans subfields including Artificial Intelligence, Safety Research, Electrical and Electronic Engineering, General Health Professions, and Management Science and Operations Research.

Their research addresses topics such as Explainable Artificial Intelligence (XAI), Ethics and Social Impacts of AI, Machine Learning and Data Classification, Homelessness and Social Issues, Health Systems, Economic Evaluations, Quality of Life, HIV/AIDS Research and Interventions, and HIV, Drug Use, Sexual Risk.

Frequent publication venues for their research include arXiv (Cornell University), Proceedings of the AAAI Conference on Artificial Intelligence, Data & Policy, BMJ, and Scientific Reports.

Recent papers authored or co-authored by Rayid Ghani include:

Machine learning and artificial intelligence research for patient benefit: 20 critical questions on transparency, replicability, ethics, and effectiveness, 2020, BMJ
Empirical observation of negligible fairness-accuracy trade-offs in machine learning for public policy, 2020, arXiv (Cornell University)
Explainable machine learning for public policy: Use cases, gaps, and research directions, 2023, Data & Policy
Predictive Analytics for Retention in Care in an Urban HIV Clinic, 2020, Scientific Reports
Validation of a Machine Learning Model to Predict Childhood Lead Poisoning, 2020, JAMA Network Open

Co-authors frequently collaborating with Rayid Ghani include Kit T. Rodolfa, Kasun Amarasinghe, Hemank Lamba, Sebastian J. Vollmer, and Bilal A. Mateen.

Best Publications

Analyzing the effectiveness and applicability of co-training

Kamal Nigam;Rayid Ghani

1441
Citations
A Study of Approaches to Hypertext Categorization

Yiming Yang;Seán Slattery;Rayid Ghani

476
Citations
Machine learning and artificial intelligence research for patient benefit: 20 critical questions on transparency, replicability, ethics, and effectiveness

S Vollmer;B A Mateen;B A Mateen;B A Mateen;G Bohner;G Bohner;F J Király;F J Király

430
Citations
Text mining for product attribute extraction

Rayid Ghani;Katharina Probst;Yan Liu;Marko Krema

294
Citations
A Machine Learning Framework to Identify Students at Risk of Adverse Academic Outcomes

Himabindu Lakkaraju;Everaldo Aguiar;Carl Shan;David Miller

199
Citations
System for individualized customer interaction

Andrew E. Fano;Chad M. Cumby;Rayid Ghani;Marko Krema

182
Citations
Combining Labeled and Unlabeled Data for MultiClass Text Categorization

Rayid Ghani

169
Citations
Using Error-Correcting Codes for Text Classification

Rayid Ghani

155
Citations
Big Data and Social Science: A Practical Guide to Methods and Tools

Ian Foster;Rayid Ghani;Ron S. Jarmin;Frauke Kreuter

151
Citations
Mining the web to create minority language corpora

Rayid Ghani;Rosie Jones;Dunja Mladenić

138
Citations
Data Mining on Symbolic Knowledge Extracted from the Web

Rayid Ghani;Seán Slattery

111
Citations
Hypertext Categorization using Hyperlink Patterns and Meta Data

Rayid Ghani;Seán Slattery;Yiming Yang

106
Citations
Aequitas: A Bias and Fairness Audit Toolkit.

Pedro Saleiro;Benedict Kuester;Abby Stevens;Ari Anisfeld

98
Citations
Data mining to predict and prevent errors in health insurance claims processing

Mohit Kumar;Rayid Ghani;Zhu-Song Mei

95
Citations
Promotion planning system

Andrew E. Fano;Chad M. Cumby;Rayid Ghani;Marko Krema

91
Citations
Semi-supervised learning of attribute-value pairs from product descriptions

Katharina Probst;Rayid Ghani;Marko Krema;Andrew Fano

90
Citations
Combining labeled and unlabeled data for text classification with a large number of categories

R. Ghani

89
Citations
Price prediction and insurance for online auctions

Rayid Ghani

73
Citations
A Machine Learning Based System for Semi-Automatically Redacting Documents

Chad M. Cumby;Rayid Ghani

68
Citations
Empirical observation of negligible fairness–accuracy trade-offs in machine learning for public policy

Kit T. Rodolfa;Hemank Lamba;Rayid Ghani

53
Citations

Frequent Co-Authors

Frauke Kreuter Ludwig-Maximilians-Universität München

Julia Lane New York University

Rosie Jones Spotify

Dunja Mladenic Jožef Stefan Institute

Ian Foster University of Chicago

Yiming Yang Carnegie Mellon University

Ron S. Jarmin United States Census Bureau

John A. Schneider University of Chicago

Jure Leskovec Stanford University

Geoffrey J. McLachlan University of Queensland

External Links

Personal website of Rayid Ghani

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