Academic Credentials
  • Ph.D., Environmental Science and Engineering, University of Texas, San Antonio, 2018
  • M.Sc., Civil and Environmental Engineering, Iran University of Science and Technology, 2012
  • B.S., Civil and Environmental Engineering, Shiraz University, 2010
Professional Affiliations
  • American Society of Civil Engineers (ASCE)
Languages
  • Persian

Dr. Omranian's expertise focuses on advanced big data analytics, numerical modeling, statistical analysis, machine learning, software development, and data visualization. His research experience spans the areas of water resources engineering, hurricane detection, climate change, and traffic safety. 

In his previous role as a lead engineer, Dr. Omranian combined numerical models with advanced machine learning techniques to prepare floodplain maps and provide master flood mitigation plans under FEMA regulations. He designs innovative solutions to complex engineering problems using data-driven approaches.

At Exponent, Dr. Omranian works on a variety of projects involving software development, data analytics and validation, building advanced machine learning prediction models, data engineering and pipelines, and developing forecasting algorithms. His work touches multiple fields such as health sciences, utilities, and electronics and increases work efficiencies by automating analytics and calculations.

Dr. Omranian received, the Dwight David Eisenhower Transportation Fellowship from U.S. Department of Transportation, Federal Highway Administration in 2017 for his novel research on predicting large-scale effects of adverse weather conditions on transportation safety using a big data approach. He developed a cloud-based prediction software to connect satellite real-time precipitation products to crashes for the entire state of Texas. He utilized parallel programming and distributed system concepts/tools to analyze and develop the prediction model.