LabCompass

Kibum Kim

Engineering · Purdue University West Lafayette

OpenAlex ORCID
Mid career · publishing since 2011
Water Systems and OptimizationGeotechnical Engineering and Underground StructuresEngineering Applied ResearchWater resources management and optimizationStructural Integrity and Reliability Analysis

Publications

64

Citations

197

Est. group size

~1

Recurring co-author estimate

Active years

14

Publishing since 2011

Research summary
AI-generated

Kibum Kim's research focuses on managing and maintaining water distribution infrastructure, including detecting pipe corrosion and leaks, assessing risks of pipe failure, and using machine learning to predict pipeline conditions. The work often combines statistical and machine-learning methods with practical applications like trenchless pipe rehabilitation and water quality forecasting for utility management.

Water distribution network managementPipeline corrosion and failure predictionMachine learning for infrastructure monitoringRisk assessment and decision-making methods (e.g., TOPSIS, fault tree analysis)Trenchless pipe rehabilitation technology

Publication output has fluctuated over the last decade with a peak in 2019, a decline through 2021, and a moderate rebound in 2023 before tapering again in 2024.

Generated by claude-sonnet-5 from public bibliographic data · Jul 20, 2026

Publication cadence
Publications per year over the last 10 years — averaging 3.4/year recently
2017: 9 publications172018: 5 publications182019: 11 publications11192020: 6 publications202021: 4 publications212022: 5 publications222023: 8 publications232024: 4 publications242526
Recent publications
Publishes in
  • Journal of The Korean Society of Water and Wastewater×13
  • Desalination and Water Treatment×7
  • Journal of Industrial Science and Technology Institute×5
  • Water Science & Technology Water Supply×3
  • AQUA - Water Infrastructure Ecosystems and Society×2
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This profile was generated automatically from public scholarly data (OpenAlex). Group size and activity levels are estimates derived from co-authorship patterns.

Last updated Jul 20, 2026.

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