World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
45
Citations
7972
World Ranking
7223
National Ranking
3153

Overview

Alexander G. Gray is affiliated with the Georgia Institute of Technology in the United States. Their research primarily spans the field of Computer Science, with a focused concentration on several subfields including Artificial Intelligence, Computer Vision and Pattern Recognition, Computational Theory and Mathematics, Parasitology, and Ecology, Evolution, Behavior and Systematics.

Their work encompasses a variety of topics related to artificial intelligence and machine learning, notably:

  • Topic Modeling
  • Natural Language Processing Techniques
  • Bayesian Modeling and Causal Inference
  • Reinforcement Learning in Robotics
  • Logic, Reasoning, and Knowledge
  • Explainable Artificial Intelligence (XAI)
  • Machine Learning and Data Classification

Alexander G. Gray has collaborated frequently with several researchers, including Parikshit Ram, Ryan Riegel, Pavan Kapanipathi, Salim Roukos, and Subhajit Chaudhury.

The main venues where their research has been published include:

  • arXiv (Cornell University)
  • Proceedings of the AAAI Conference on Artificial Intelligence
  • Frontiers in Oncology
  • Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
  • Current Research in Parasitology and Vector-Borne Diseases

Some of their recent papers are:

  • Logical Neural Networks, 2020, arXiv (Cornell University)
  • An ADMM Based Framework for AutoML Pipeline Configuration, 2020, Proceedings of the AAAI Conference on Artificial Intelligence
  • Systematic Review and Meta-Analysis of Correlation of Progression-Free Survival-2 and Overall Survival in Solid Tumors, 2020, Frontiers in Oncology
  • A Semantic Parsing and Reasoning-Based Approach to Knowledge Base Question Answering, 2021, Proceedings of the AAAI Conference on Artificial Intelligence
  • Neuro-Symbolic Reinforcement Learning with First-Order Logic, 2021, Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing

Best Publications

  • An Investigation of Practical Approximate Nearest Neighbor Algorithms

    Ting Liu;Andrew W. Moore;Ke Yang;Alexander G. Gray

  • Efficient photometric selection of quasars from the sloan digital sky survey: 100,000 z < 3 quasars from data release one

    Gordon T. Richards;Gordon T. Richards;Adam D. Myers;Alexander G. Gray;Ryan N. Riegel

  • Statistics, Data Mining, and Machine Learning in Astronomy: A Practical Python Guide for the Analysis of Survey Data

    Zeljko Ivezic;Andrew J. Connolly;Jacob T. VanderPlas;Alexander Gray

  • Human-AI Collaboration in Data Science: Exploring Data Scientists' Perceptions of Automated AI

    Dakuo Wang;Justin D. Weisz;Michael Muller;Parikshit Ram

  • `N-Body' Problems in Statistical Learning

    Alexander G. Gray;Andrew W. Moore

  • Statistics, Data Mining, and Machine Learning in Astronomy

    Željko Ivezić;Andrew J. Connelly;Jacob T. Vanderplas;Alexander Gray

  • Efficient Photometric Selection of Quasars from the Sloan Digital Sky Survey: 100,000 z<3 Quasars from Data Release One

    Gordon T. Richards;Robert C. Nichol;Alexander G. Gray;Robert J. Brunner

  • Stochastic Alternating Direction Method of Multipliers

    Hua Ouyang;Niao He;Long Tran;Alexander Gray

  • Nonparametric Density Estimation: Toward Computational Tractability.

    Alexander G. Gray;Andrew W. Moore

  • High redshift detection of the integrated Sachs-Wolfe effect

    Tommaso Giannantonio;Robert G. Crittenden;Robert C. Nichol;Ryan Scranton

  • Detecting spammers with SNARE: spatio-temporal network-level automatic reputation engine

    Shuang Hao;Nadeem Ahmed Syed;Nick Feamster;Alexander G. Gray

  • MLPACK: a scalable C++ machine learning library

    Ryan R. Curtin;James R. Cline;N. P. Slagle;William B. March

  • Maximum inner-product search using cone trees

    Parikshit Ram;Alexander G. Gray

  • Automated design of quantum circuits

    C. P. Williams;A. G. Gray

  • Ovarian cancer detection from metabolomic liquid chromatography/mass spectrometry data by support vector machines.

    Wei Guan;Manshui Zhou;Christina Young Hampton;Benedict B. Benigno

  • New Algorithms for Efficient High-Dimensional Nonparametric Classification

    Ting Liu;Andrew W. Moore;Alexander Gray

  • Fast euclidean minimum spanning tree: algorithm, analysis, and applications

    William B. March;Parikshit Ram;Alexander G. Gray

  • The three-point correlation function of luminous red galaxies in the Sloan Digital Sky Survey

    Gauri V. Kulkarni;Robert C. Nichol;Robert C. Nichol;Ravi K. Sheth;Hee-Jong Seo

  • Density estimation trees

    Parikshit Ram;Alexander G. Gray

  • Retrofitting decision tree classifiers using kernel density estimation

    Padhraic Smyth;Alexander G. Gray;Usama M. Fayyad

  • Logical Neural Networks

    Ryan Riegel;Alexander G. Gray;Francois P. S. Luus;Naweed Khan

  • New Algorithms for Efficient High Dimensional Non-parametric Classification

    Ting liu;Andrew W. Moore;Alexander Gray

  • SNARE: Spatio-temporal Network-level Automatic Reputation Engine

    Nick Feamster;Alexander G. Gray;Sven Krasser;Nadeem Ahmed Syed

  • Statistics, Data Mining, and Machine Learning in Astronomy : A Practical Python Guide for the Analysis of Survey Data, Updated Edition

    Željko Ivezić;Andrew J. Connolly;Jacob T. VanderPlas;Alexander Gray

Frequent Co-Authors

Gordon T. Richards
Gordon T. Richards Drexel University
Robert J. Brunner
Robert J. Brunner University of Illinois at Urbana-Champaign
Zeljko Ivezic
Zeljko Ivezic University of Washington
Robert C. Nichol
Robert C. Nichol University of Surrey
Andrew W. Moore
Andrew W. Moore Carnegie Mellon University
Salim Roukos
Salim Roukos IBM (United States)
Donald P. Schneider
Donald P. Schneider Pennsylvania State University
Adam D. Myers
Adam D. Myers University of Wyoming
Alexander S. Szalay
Alexander S. Szalay Johns Hopkins University
John F. McDonald
John F. McDonald Georgia Institute 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 online degree options for computer science and related fields can open many doors—no matter your academic background. Many students worry about their academic history, but plenty of best colleges for low gpa offer accessible programs, ensuring you can start your journey even if your grades weren’t perfect.

For those in a hurry, the fastest computer science degree programs online provide a way to earn your credentials in less time, helping you move quickly into the workforce.

If you’re interested in blending technology and environmental stewardship, consider the online environmental engineering degree science and engineering programs. These affordable options combine core science skills with hands-on engineering principles.

Career options after graduation are diverse. For inspiration, check out what’s possible with similar pathways in environmental science by exploring what can i do with an environmental science degree. Whether you focus on computer science or cross over into related areas, a wealth of online degree opportunities and promising careers await.

Best Scientists Citing Alexander G. Gray

Trending Scientists

Recently Published Articles