Bardia Heidari, Ph.D., P.E.

Research Scientist at Texas Water Resources Institute
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Contact Information
us****@****om
(386) 825-5501
Location
Dallas, Texas, United States, US
Languages
  • English Full professional proficiency
  • French Elementary proficiency
  • Persian Native or bilingual proficiency

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Credentials

  • Professional Engineer (PE)
    Texas Board of Professional Engineers and Land Surveyors
    Aug, 2022
    - Nov, 2024
  • Engineer in Training (EIT)
    State of Virginia

Experience

    • United States
    • Research Services
    • 1 - 100 Employee
    • Research Scientist
      • Aug 2021 - Present

      • Analyzed precipitation projections using downsaling and bias correction to determine uncertainty bounds for extreme design storms in the North Texas region and their impact on drainage infrastructure. • Wrote 5+ grant proposals for advancing research in three distinct domains, climate change impact on urban flooding, Green stormwater Infrastructure (GSI) design and planning, urban water cycle modeling and watershed planning. • Successfully acquired two grants from the Texas Commission on Environmental Quality (TCEQ), Non-point Source Program (NPS) as a Principal Investigator, and from the National Science Foundation (NSF) as a Senior Personnel(total of more than $300K). • Co-executed, coordinated, and presented at four workshops titled as” Advancing Blue Green Infrastructure for a resilient DFW” for 50+ professional participants from 25+ entities in the DFW metroplex. • Led a team of researchers and published a peer-reviewed review article in the WIREs-Water to highlight barriers and solutions to wide GSI implementation. Show less

    • United States
    • Higher Education
    • 700 & Above Employee
    • Postdoctoral Researcher
      • Sep 2019 - Aug 2021

      • Led the technical and modeling aspects of a cross-functional and multi-institutional collaborative two year project with partners from governmental and non-profit agencies to analyze stormwater inlet flooding in the City of Dallas and the potential impact of GSI implementation in its mitigation. • Modeled stormwater network for nine main watersheds in the city of Dallas using EPA SWMM numerical model to identify stormwater inlet flooding hotspots. • Prioritized all subwatersheds with overflowing inlets for stormwater investments and computed the potential of overflow reduction via Green Stormwater Infrastructure using Python. • Generated maps using ArcGIS and presentation files and assisted in the preparation of the final public report to disseminate the findings on flooding and GSI impact. • Merged computational model results with machine learning techniques and produced two manuscripts demonstrating the methodology and the results for publication in peer-reviewed journals. • Mentored three early-career professionals on the spatial analysis and modeling aspects of the project. Show less

    • United States
    • Higher Education
    • 700 & Above Employee
    • Research Intern- Civil and Environmental Engineering
      • Aug 2017 - Aug 2019

      • Designed extractors and converters for GSI detection and performance modeling on a cloud-based scientific data repository platform using Python programming language. • Designed and executed numerical Monte Carlo simulations of urban hydrology models to quantify simulation uncertainties using High Performance Computing environment. • Arranged and organized five live demonstration presentations of computational web-based services to potential collaborators and investors in academic and non-academic nonprofit entities. Show less

    • United States
    • Higher Education
    • 700 & Above Employee
    • Graduate Research Assistant - Department of Civil and Environmental Engineering
      • Jun 2014 - Jul 2017

      • Collaborated with a 10-person interdisciplinary national research and development team, sponsored by the NSF, that created a web-based online platform to design GSI. • Designed back-end numerical watershed simulation models coupled with geospatial visualization tools. • Coupled optimization genetic algorithms with ensemble tree classifier and artificial neural network models to quickly recognize optimal locations for GSI implementation. • Published the results as a free resource for interactive design of green infrastructure practices using iPython, available as a public open-source resource at www.hydroshare.org. • Presented the results at more than five national conferences and workshops to stormwater practitioners and municipalities. Show less

    • United States
    • Higher Education
    • 700 & Above Employee
    • Graduate Research Assistant, Department of Civil and Environmental Engineering
      • Jan 2013 - May 2014

      • Served as a member of a research team sponsored by the Environmental Protection Agency (EPA) responsible for coupling construction equipment air pollutant emissions with image-based action recognition models. • Conducted on-site emission measurement tests on construction equipment at 15 different sites across Virginia. • Analyzed and published the results in a peer-reviewed journal paper. • Served as a member of a research team sponsored by the Environmental Protection Agency (EPA) responsible for coupling construction equipment air pollutant emissions with image-based action recognition models. • Conducted on-site emission measurement tests on construction equipment at 15 different sites across Virginia. • Analyzed and published the results in a peer-reviewed journal paper.

Education

  • University of Illinois at Urbana-Champaign
    Doctor of Philosophy (PhD), Civil and Environmental Engineering
    2014 - 2019
  • Virginia Tech
    Master of Science in Civil and Environmental Engineering, Environmental Engineering
    2012 - 2014
  • Sharif University of Technology
    B.Sc in Civil Engineering
    2007 - 2012

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