World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
50
Citations
14526
World Ranking
5499
National Ranking
210

Research.com Recognitions

  • 2000 - Fellow of the Association for the Advancement of Artificial Intelligence (AAAI) For significant contributions to the fields of abductive inference and default and probabilistic reasoning with applications to diagnosis and decision-making.

Overview

David Poole is affiliated with the University of British Columbia in Canada. Their research spans multiple fields, primarily focusing on computer science and environmental science. Their work integrates artificial intelligence methodologies with applications in spectroscopy, geochemistry, and environmental analysis.

Poole's main fields of study include:

  • Computer Science
  • Environmental Science

Their research extends into several subfields, particularly:

  • Artificial Intelligence
  • Global and Planetary Change
  • Analytical Chemistry
  • Plant Science
  • Sociology and Political Science

The primary topics covered in their scientific work are:

  • Spectroscopy and Chemometric Analyses
  • Geochemistry and Geologic Mapping
  • Bayesian Modeling and Causal Inference
  • Smart Agriculture and AI
  • Leaf Properties and Growth Measurement
  • Mineral Processing and Grinding
  • Nuclear Physics and Applications

Among their recent publications are:

  • Automatic neural network hyperparameter optimization for extrapolation: Lessons learned from visible and near-infrared spectroscopy of mango fruit (2022), published in Chemometrics and Intelligent Laboratory Systems
  • Auto-encoder neural network incorporating x-ray fluorescence fundamental parameters with machine learning (2023), published in X-Ray Spectrometry
  • Structure learning for relational logistic regression: an ensemble approach (2021), published in Data Mining and Knowledge Discovery
  • INSPIRE standards as a framework for artificial intelligence applications: a landslide example (2020), published in Natural hazards and earth system sciences
  • Spectral sensor fusion for prediction of Li and Zr in rocks: Neural network and PLS methods (2023), published in Chemometrics and Intelligent Laboratory Systems

Their frequent coauthors include:

  • Matthew Dirks
  • Seyed Mehran Kazemi
  • Guy Van den Broeck
  • Nandini Ramanan
  • Gautam Kunapuli

David Poole has published in a variety of venues, most notably:

  • Chemometrics and Intelligent Laboratory Systems
  • X-Ray Spectrometry
  • Data Mining and Knowledge Discovery
  • Natural hazards and earth system sciences
  • The "journal of cetacean research and management. Special issue

They have also contributed to book publications through several publishers including Bloomsbury Academic eBooks with a title on entrepreneurship and SMEs in Rwanda (2020), Cambridge University Press with a book on Artificial Intelligence (2023), and Zed Books with a work on War, Women, and Post-conflict Empowerment (2021).

David Poole was awarded the status of Fellow of the Association for the Advancement of Artificial Intelligence (AAAI) in 2000 for their contributions to abductive inference and probabilistic reasoning, particularly in diagnosis and decision-making applications.

Best Publications

  • CP-nets: a tool for representing and reasoning with conditional ceteris paribus preference statements

    Craig Boutilier;Ronen I. Brafman;Carmel Domshlak;Holger H. Hoos

  • A logical framework for default reasoning

    David Poole

  • Computational Intelligence: A Logical Approach

    David Poole;Alan Mackworth;Randy Goebel

  • Probabilistic Horn abduction and Bayesian networks

    David Poole

  • Exploiting causal independence in Bayesian network inference

    Nevin Lianwen Zhang;David Poole

  • First-order probabilistic inference

    David Poole

  • Theorist: A Logical Reasoning System for Defaults and Diagnosis

    David Poole;Randy Goebel;Romas Aleliunas

  • SimplE embedding for link prediction in knowledge graphs

    Seyed Mehran Kazemi;David Poole

  • A simple approach to Bayesian network computations

    Nevin L. Zhang;D. Poole

  • The independent choice logic for modelling multiple agents under uncertainty

    David Poole

  • Reasoning with conditional ceteris paribus preference statements

    Craig Boutilier;Ronen I. Brafman;Holger H. Hoos;David Poole

  • Artificial Intelligence: Agents in the World: What Are Agents and How Can They Be Built?

    David L. Poole;Alan K. Mackworth

  • On the comparison of theories: preferring the most specific explanation

    David L. Poole

  • Explanation and prediction: an architecture for default and abductive reasoning

    David Poole

  • CP-nets: A Tool for Representing and Reasoning withConditional Ceteris Paribus Preference Statements

    C. Boutilier;R. I. Brafman;C. Domshlak;H. H. Hoos

  • Computing optimal policies for partially observable decision processes using compact representations

    Craig Boutilier;David Poole

  • Normality and faults in logic-based diagnosis

    David Poole

  • Preference-Based Constrained Optimization with CP-Nets

    Craig Boutilier;Ronen I. Brafman;Carmel Domshlak;Holger H. Hoos

  • MULTIPLY SECTIONED BAYESIAN NETWORKS AND JUNCTION FORESTS FOR LARGE KNOWLEDGE-BASED SYSTEMS

    Yang Xiang;David Poole;Michael P. Beddoes

  • ILP turns 20

    Stephen Muggleton;Luc Raedt;David Poole;Ivan Bratko

Frequent Co-Authors

Alan K. Mackworth
Alan K. Mackworth University of British Columbia
Giuseppe Carenini
Giuseppe Carenini University of British Columbia
Craig Boutilier
Craig Boutilier Google (United States)
Kristian Kersting
Kristian Kersting Technical University of Darmstadt
Ronen I. Brafman
Ronen I. Brafman Ben-Gurion University of the Negev
Nando de Freitas
Nando de Freitas DeepMind (United Kingdom)
Holger H. Hoos
Holger H. Hoos RWTH Aachen University
Carmel Domshlak
Carmel Domshlak Technion – Israel Institute of Technology
Cristina Conati
Cristina Conati University of British Columbia
Luc De Raedt
Luc De Raedt KU Leuven

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