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Computer Science

D-Index
47
Citations
15428
World Ranking
6318
National Ranking
2823

Overview

Pang-Ning Tan is affiliated with Michigan State University in the United States. Their research covers significant areas within computer science and environmental science, contributing to both fields through numerous publications spanning several subfields and topics.

Their main fields of study include:

  • Computer Science
  • Environmental Science

Within these fields, their work further specializes into the following subfields:

  • Artificial Intelligence
  • Global and Planetary Change
  • Epidemiology
  • Public Health, Environmental and Occupational Health
  • Electrical and Electronic Engineering

The primary research topics covered in their work are:

  • Advanced Graph Neural Networks
  • Vaccine Coverage and Hesitancy
  • Climate Variability and Models
  • Energy Load and Power Forecasting
  • Hydrology and Drought Analysis
  • Complex Network Analysis Techniques
  • Soil Moisture and Remote Sensing

Pang-Ning Tan has contributed frequently to various publication venues including:

  • Proceedings of the AAAI Conference on Artificial Intelligence
  • arXiv (Cornell University)
  • Proceedings of the Annual Hawaii International Conference on System Sciences
  • Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence
  • ISPRS Journal of Photogrammetry and Remote Sensing

Their recent scholarly papers include:

  • "Bursting the Filter Bubble: Fairness-Aware Network Link Prediction," 2020, Proceedings of the AAAI Conference on Artificial Intelligence
  • "Using Machine Learning to Compare Provaccine and Antivaccine Discourse Among the Public on Social Media: Algorithm Development Study," 2021, JMIR Public Health and Surveillance
  • "Unsupervised Anomaly Detection by Robust Density Estimation," 2022, Proceedings of the AAAI Conference on Artificial Intelligence
  • "Review of synthetic aperture radar with deep learning in agricultural applications," 2024, ISPRS Journal of Photogrammetry and Remote Sensing
  • "Yield estimation from SAR data using patch-based deep learning and machine learning techniques," 2024, Computers and Electronics in Agriculture

Frequent collaborators in their research include:

  • Lifeng Luo
  • Francisco C. Santos
  • Abdol-Hossein Esfahanian
  • Farzan Masrour
  • Tyler Wilson

Best Publications

  • Web usage mining: discovery and applications of usage patterns from Web data

    Jaideep Srivastava;Robert Cooley;Mukund Deshpande;Pang-Ning Tan

  • Introduction to Data Mining, (First Edition)

    Pang-Ning Tan;Michael Steinbach;Vipin Kumar

  • Selecting the right interestingness measure for association patterns

    Pang-Ning Tan;Vipin Kumar;Jaideep Srivastava

  • Selecting the right objective measure for association analysis

    Pang-Ning Tan;Vipin Kumar;Jaideep Srivastava

  • Discovery of Web Robot Sessions Based on their Navigational Patterns

    Pang-Ning Tan;Vipin Kumar

  • Data Mining for Network Intrusion Detection

    Paul Dokas;Levent Ertoz;Vipin Kumar;Aleksandar Lazarevic

  • Multistep-ahead time series prediction

    Haibin Cheng;Pang-Ning Tan;Jing Gao;Jerry Scripps

  • Interestingness Measures for Association Patterns: A Perspective

    Pang-ning Tan;Vipin Kumar

  • Discovery of Interesting Usage Patterns from Web Data

    Robert Cooley;Pang-Ning Tan;Jaideep Srivastava

  • Cross‐scale interactions: quantifying multi‐scaled cause–effect relationships in macrosystems

    Patricia A. Soranno;Kendra S. Cheruvelil;Edward G. Bissell;Mary T. Bremigan

  • Hyperclique pattern discovery

    Hui Xiong;Pang-Ning Tan;Vipin Kumar

  • Mining strong affinity association patterns in data sets with skewed support distribution

    H. Xiong;P.-N. Tan;Vipin Kumar

  • Receiver Operating Characteristic.

    Pang-Ning Tan

  • Discovery of climate indices using clustering

    Michael Steinbach;Pang-Ning Tan;Vipin Kumar;Steven Klooster

  • Converting Output Scores from Outlier Detection Algorithms into Probability Estimates

    Jing Gao;Pang-Ning Tan

  • Detection and characterization of anomalies in multivariate time series

    Haibin Cheng;Pang-Ning Tan;Christopher Potter;Steven A. Klooster

  • Exploiting a support-based upper bound of Pearson's correlation coefficient for efficiently identifying strongly correlated pairs

    Hui Xiong;Shashi Shekhar;Pang-Ning Tan;Vipin Kumar

  • Introduction to Data Mining (2nd Edition)

    Pang-Ning Tan;Michael Steinbach;Anuj Karpatne;Vipin Kumar

  • LAGOS-NE: A multi-scaled geospatial and temporal database of lake ecological context and water quality for thousands of US lakes

    Patricia A. Soranno;Linda C. Bacon;Michael Beauchene;Karen E. Bednar

  • On ontology-driven document clustering using core semantic features

    Samah Fodeh;Bill Punch;Pang-Ning Tan

  • Proceedings of the 2014 SIAM International Conference on Data Mining

    Mohammed Zaki;Zoran Obradovic;Pang Ning Tan;Arindam Banerjee

Frequent Co-Authors

Vipin Kumar
Vipin Kumar University of Minnesota
Jiayu Zhou
Jiayu Zhou Michigan State University
Lifeng Luo
Lifeng Luo Michigan State University
Jaideep Srivastava
Jaideep Srivastava University of Minnesota
Jing Gao
Jing Gao Purdue University West Lafayette
Christopher Potter
Christopher Potter University of Cambridge
Hui Xiong
Hui Xiong Rutgers, The State University of New Jersey
Anil K. Jain
Anil K. Jain Michigan State University
Ranga B. Myneni
Ranga B. Myneni Boston University
Antonio Nucci
Antonio Nucci Cisco Systems (United States)

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