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Byung-Cheol Kim

Assistant Professor
Civil Engineering
STKR 139
kimb@ohio.edu
Phone: 740.593.1478

Dr. Kim joined Ohio University's Civil Engineering Department in Fall 2008. Prior to earning his doctorate, he worked for Samsung E&C Corporation as a construction engineer, bridge design planner, and project controls engineer. He is a registered structural engineer in Korea since 1998 and a PMP® (Project Management Professional) certified by PMI since 1999. He also wrote a book about Project Management (in Korean), which has been used as a textbook for project management courses in many universities.

Dr. Kim's principal research area is Construction Engineering and Management.  His research interest includes forecasting, project risk management, performance monitoring and control, risk assessment and analysis, reliability-based infrastructure management, and decision making under uncertainty. As a part of his dissertation, he developed two new probabilistic forecasting methods for project schedule risk assessment.  Programmed as an add-in for Microsoft Excel, those new methods can be used in most  projects managed based on the earned value method or any other cumulative progress metrics, for example, % complete.


Research Interests: forecasting, project risk management, performance monitoring and control, risk assessment and analysis,

All Degrees Earned: Ph.D., Construction Management in Civil Engineering, Texas A&M University, 2007

Journal Article, Academic Journal (13)

  • Kim, B., Kim, S. Credibility evaluation of project duration forecast using forecast sensitivity and forecast-risk compatibility. ASCE Journal of Civil Engineering and Management; http://ascelibrary.org/journal/jcemd4.
  • Kim, B. Integrating risk assessment and actual performance for probabilistic project cost forecasting: A second moment Bayesian model. IEEE Transactions on Engineering Management.
  • Kim, B. Dynamic Control Thresholds for Consistent Earned Value Analysis and Reliable Early Warning. ASCE Journal of Management in Engineering.
  • Kim, B., Kim, H. Sensitivity of earned value schedule forecast to S-curve patterns. 7. ASCE Journal of Civil Engineering and Management; 140: http://ascelibrary.org/journal/jcemd4.
  • Kim, B. Chemical Plant Construction: Probabilistic Schedule Forecasting and Risk Assessment. Encyclopedia of Chemical Processing.
  • Kim, B., Reinschmidt, K. Probability Distribution of the Project Payback Period using the Equivalent Cash Flow Decomposition. 2. The Engineering Economist; 58: 112-136.
  • Shim, E., Kim, B., Kim, S. Cash-flow simulation game for teaching project cash-flow forecasting. 2. The Technology Interface International Journal; 13: 12-19.
  • Shim, E., Kim, B. Batch-size based Repetitive Scheduling Method. The International Journal of Construction Education and Research.
  • Kim, B., Reinschmidt, K. A Second Moment Approach to Probabilistic IRR using Taylor Series. 1. The Engineering Economist; 57: 1-19.
  • Kim, B., Reinschmidt, K. Combination of Project Cost Forecasts in Earned Value Management. 11. Journal of Construction Engineering and Management, ASCE; 137: 958-966. http://scitation.aip.org/coo/.
  • Kim, B. Systematic Errors in Single-point Estimates of Project Cost. Journal of Construction Engineering and Management, ASCE; http://scitation.aip.org/coo/.
  • Kim, B., Reinschmidt, K. Probabilistic Forecasting of Project Duration Using Kalman Filter and the Earned Value Method. 8. Journal of Construction Engineering and Management, ASCE; 136: 834-843. http://dx.doi.org/10.1061/(ASCE)CO.1943-7862.0000192.
  • Kim, B., Reinschmidt, K. Probabilistic Forecasting of Project Duration Using Bayesian Inference and the Beta Distribution. 3. Journal of Construction Engineering and Management, ASCE; 135: 178-186.

Magazine/Trade Publication (1)

  • Kim, B., Shim, E., Reinschmidt, K. Dealing with uncertainty. 9. Norcross, GA : The Industrial Engineer Magazine; 45: 52. http://Texas A&M University.

Conference Proceeding (4)

  • Kim, B., Shim, E., Kim, S. Reclaiming multifaceted financial risk information from correlated cash flows under uncertainty. International Conference on Construction Engineering and Project Management.
  • Kim, B. Probabilistic performance risk evaluation of infrastructure projects. ASCE International Conference on Vulnerability and Risk Analysis and Management.
  • Kim, B., Reinschmidt, K. Project Schedule Risk Assessment and Completion Prediction Using a Bayesian Forecasting Method. Texas A&M University, College Station, TX: INFORMS Southwest Regional Conference.
  • Kim, B., Reinschmidt, K. An S-Curve Bayesian Model for Forecasting Probability Distributions on Project Duration and Cost at Completion. Reading, United Kingdom: Construction Management and Economics 25th Anniversary Conference.

Book, Textbook (1)

  • Kim, B. Introduction to Project Management . Sewha, Seoul: pp. 379.