World's Best Scientists 2026 revealed!

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Computer Science

D-Index
41
Citations
9466
World Ranking
8680
National Ranking
3722

Overview

Kathryn B. Laskey is affiliated with George Mason University in the United States. Their research spans the field of Computer Science, with a focus on several subfields including Artificial Intelligence, Information Systems, Environmental Engineering, Sociology and Political Science, and Signal Processing.

The main topics addressed in their work include:

  • Spam and Phishing Detection
  • Advanced Malware Detection Techniques
  • Misinformation and Its Impacts
  • Bayesian Modeling and Causal Inference
  • Hydrological Forecasting Using AI
  • Groundwater and Watershed Analysis
  • Water Resources Management and Optimization

Their publication record includes papers in a range of venues with a concentration in conferences and journals related to information fusion and interdisciplinary computing. Frequent publication venues where their work appears include:

  • 2021 IEEE 24th International Conference on Information Fusion (FUSION)
  • Preprints.org
  • Water
  • Proceedings of the Annual Hawaii International Conference on System Sciences
  • ACM Transactions on Social Computing

Recent papers by Kathryn B. Laskey reflect a variety of research interests over the years. Selected papers include:

  • Experimental Investigation of Demographic Factors Related to Phishing Susceptibility, 2020, Proceedings of the Annual Hawaii International Conference on System Sciences
  • Experimental Investigation of Technical and Human Factors Related to Phishing Susceptibility, 2021, ACM Transactions on Social Computing
  • Assessing Resilience of Hospitals to Cyberattack, 2021, Digital Health
  • Groundwater Level Prediction with Machine Learning to Support Sustainable Irrigation in Water Scarcity Regions, 2023, Water
  • Investigation of Phishing Susceptibility with Explainable Artificial Intelligence, 2024, Future Internet

Their collaborations include frequent co-authors Wanru Li, Mekuanent Muluneh Finsa, Paul R. Houser, Rupert Douglas-Bate, and Kuo-Chu Chang, indicating an active network in interdisciplinary research efforts.

Best Publications

  • Stochastic blockmodels: First steps

    Paul W. Holland;Kathryn Blackmond Laskey;Samuel Leinhardt

  • MEBN: A language for first-order Bayesian knowledge bases

    Kathryn Blackmond Laskey

  • Sensitivity analysis for probability assessments in Bayesian networks

    K.B. Laskey

  • Network fragments: representing knowledge for constructing probabilistic models

    Kathryn Blackmond Laskey;Suzanne M. Mahoney

  • PR-OWL: a Bayesian ontology language for the semantic web

    Paulo Cesar G. Da Costa;Kathryn B. Laskey;Kenneth J. Laskey

  • PR-OWL: A Framework for Probabilistic Ontologies

    Paulo C. G. Costa;Kathryn B. Laskey

  • Neural Coding: Higher-Order Temporal Patterns in the Neurostatistics of Cell Assemblies

    Laura Martignon;Gustavo Deco;Kathryn Laskey;Mathew Diamond

  • Bayesian semantics for the semantic web

    Paulo Cesar G. Da Costa;Kathryn Blackmond Laskey

  • Towards unbiased evaluation of uncertainty reasoning: The URREF ontology

    Paulo C. G. Costa;Kathryn B. Laskey;Erik Blasch;Anne-Laure Jousselme

  • PR-OWL 2.0 - bridging the gap to OWL semantics

    Rommel N. Carvalho;Kathryn B. Laskey;Paulo C. G. Costa

  • Assumptions, beliefs and probabilities

    K. B. Laskey;P. E. Lehner

  • Network engineering for agile belief network models

    K.B. Laskey;S.M. Mahoney

  • Population Markov chain Monte Carlo

    Kathryn Blackmond Laskey;James W. Myers

  • Bayesian benchmarks for fast and frugal heuristics

    Laura Martignon;Kathryn Blackmond Laskey

  • Network engineering for complex belief networks

    Suzanne M. Mahoney;Kathryn B. Laskey

  • Learning Bayesian networks from incomplete data using evolutionary algorithms

    James W. Myers;Kathryn B. Laskey;Kenneth A. DeJong

  • Nonparametric Bayesian Co-clustering Ensembles.

    Pu Wang;Kathryn B. Laskey;Carlotta Domeniconi;Michael I. Jordan

  • Model uncertainty: theory and practical implications

    K.B. Laskey

  • Learning Bayesian networks from incomplete data with stochastic search algorithms

    James W. Myers;Kathryn Blackmond Laskey;Tod Levitt

  • Uncertainty reasoning for the world wide web: report on the URW3-XG incubator group

    Kenneth J. Laskey;Kathryn Blackmond Laskey

  • Proceedings of the Fifteenth conference on Uncertainty in artificial intelligence

    Kathryn B. Laskey;Henri Prade

Frequent Co-Authors

Erik Blasch
Erik Blasch United States Air Force Research Laboratory
Carlotta Domeniconi
Carlotta Domeniconi George Mason University
Thomas Lukasiewicz
Thomas Lukasiewicz University of Oxford
Eilon Vaadia
Eilon Vaadia Hebrew University of Jerusalem
Jean Dezert
Jean Dezert Office National d'Études et de Recherches Aérospatiales
Gustavo Deco
Gustavo Deco Pompeu Fabra University
Henri Prade
Henri Prade Paul Sabatier University
Mathew E. Diamond
Mathew E. Diamond International School for Advanced Studies
Winrich A. Freiwald
Winrich A. Freiwald Rockefeller University
Simon Parsons
Simon Parsons University of Lincoln

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