Michael Horejsei

Lead Estimator Ohio State University

Michael Horejsei is a seasoned construction management professional with a proven track record in estimating, pre-construction, and project delivery. As Lead Estimator for Facilities Design & Construction at The Ohio State University, he oversees complex projects with a focus on accuracy, cost efficiency, and strategic planning. His expertise includes data analysis, conceptual estimating, Building Information Modeling (BIM), and advanced estimating methodologies, enabling him to support large-scale institutional projects from concept through execution.
Michael’s academic foundation includes a Master of Engineering from the University of Alabama at Birmingham and a Bachelor of Science in Construction Management from The Ohio State University, where he was a varsity baseball letter winner and Big Ten Champion. His career spans roles with leading construction firms and a unique chapter as a professional baseball player after being selected in the Major League Baseball draft within the Chicago White Sox Organization.

Seminars

Thursday 7th May 2026
Strengthening Project Viability by Proactively Supporting Clients Through Market Uncertainty
10:05 am
  • Anticipating project stall points across different markets by identifying where cost volatility, risk aversion, and misaligned expectations can slow momentum
  • Increasing your value as a project partner: How can contractors share cost intelligence, market signals, and escalation updates that help clients make informed decisions earlier?
  • Reducing financing and budget risk collaboratively by improving communication, predicting cost pressures, and aligning stakeholders around protecting project feasibility
Thursday 7th May 2026
Case Study: Establishing Robust Data Governance Standards & Practices to Turn Cost Data into a Valuable Tool for Predicting Cost Insights
12:55 pm
  • Defining generalized, applicable parameters for classifying cost data across different projects and markets
  • Integrating consistent data gathering practices into existing workflows to make data governance easier to implement
  • Building a robust quality control process to ensure that data input consistently meets governance standards and practices

Case Study

Michael Horejsei