• Skip to primary navigation
  • Skip to main content
  • Skip to footer
Logo for the Department of Civil and Environmental Engineering at the University of Michigan
  • Giving
  • News and Events
  • Contact

  • About
    • History
    • Strategic Directions
    • Diversity, Equity and Inclusion
      • CEE DEI Committee
      • DEI Resources
      • Have a concern?
    • Alumni
      • CEE Friends Association
        • CEEFA Board
      • Award Winners
    • Giving
      • Giving Legacy
    • Leadership and Governance
    • Faculty Search
      • Faculty Position in Environmental Engineering
      • Faculty Position in Intelligent Systems
    • Contact
      • Student Services Contacts
      • Master’s Advising Contacts
      • Undergraduate Advising Contacts
  • Undergraduate Studies
    • BSE Degree in Civil Engineering
    • BSE Degree in Environmental Engineering
    • Minor in Civil Engineering
    • Minor in Environmental Engineering
    • FocusCEE
      • Community Policy and Planning
      • Smart Cities
      • Sustainability
    • Undergraduate Opportunities
      • Undergraduate Externship
      • Student Research and Employment
        • CEE SURE/SROP Projects 2023
    • Schedule an Advising Appointment
    • Declare Your Major
    • Careers in CEE
      • What is a Civil or Environmental Engineer?
      • Career Pathways
      • Employers of CEE Graduates
      • How to Recruit CEE Graduates
    • Undergraduate Student Advisory Council
    • Student Life
  • Graduate Studies
    • Master’s Programs
    • PhD Programs
      • PhD Mentoring Framework
      • PhD Candidate Roster
    • Pelham Scholars Program
    • Online Learning
      • Construction Engineering and Management MasterTrack™
    • Admissions Information
      • International Applicants
      • Sequential Undergraduate/Graduate Studies (SUGS) Applicants
    • Graduate Handbook
    • Graduate Student Advisory Council
    • Student Life
  • People
    • Faculty
      • Affiliated Faculty
      • Core Faculty
      • Emeritus Faculty
    • Postdocs
    • Researchers
    • Staff
      • Administrative
      • Finance
      • Human Resources
      • IT & Web
      • Laboratory Technicians
      • Purchasing
      • Student Services
  • Research
    • New Grants
    • Civil Infrastructure Systems
      • Construction Engineering and Management
      • Geotechnical Engineering
      • Intelligent Systems
      • Next Generation Transportation Systems
      • Structural and Materials Engineering
    • Environment and Water Resources
      • Ecohydrology and Hydraulic Engineering
      • Energy and Clean Technology
      • Environmental Chemistry and Soil Physics
      • Environmental Microbiology and Biotechnology
    • Smart Infrastructure Finance
    • Urban Collaboratory
    • Facilities
      • Advanced Materials Research
      • Cementitious Composites
      • Center of Excellence in Bridges and Structures
      • Computational Community Resilience
      • Computational Structural Simulation
      • Construction Engineering Lab
      • Geotechnical Engineering Labs
      • Intelligent Structural Technology
      • Next Generation Infrastructure
      • Next Generation Transportation Systems Research Facilities
      • Pavement Research Center of Excellence
      • Structural Engineering Lab
  • Resources
    • Shipping
    • Purchasing
      • Purchasing Frequently Asked Questions
    • Reimbursement
    • IT Resources
    • Lab Safety
      • Lab Safety Basics
      • Minimum Training Requirements
    • Lab Requests and Procedures
    • Room Requests
    • Faculty Intranet
    • Giving
    • News and Events
    • Contact
Portrait of Vinh Tran

Vinh Tran

home_outline/People/Postdocs/Vinh Tran

Postdoc

Contact

vinhtn@umich.edu(734) 239-4925

Location

105 EWRE

  • Education
  • Teaching
  • Publications
  • Research Interests

Education

  • VNU University of Science (Hanoi, Vietnam) Hydrology Bachelor 2009-2014
  • University of Ulsan (Ulsan, South Korea) Hydrology Ph.D. 2018-2022

Research Interests

  • Ensemble (urban) Flood/Drought Forecasting
  • Uncertainty Quantification, Data Assimilation, Optimization
  • Modeling and Developing a fully coupled numerical model
  • Artificial Intelligence, Machine Learning, Surrogate Modeling
  • Climate Change, Downscaling, and Future projection of extremes at global and local scales
  • Geomorphic/Climate internal variability and scale-dependent controls of hydrologic response       
  • Erosion and sediment transport
  • Dam safety

Publications

  • Tran, V. N., & Kim, J. (2022),  Robust and Efficient Uncertainty Quantification for Extreme Events that Deviate Significantly from the Training Dataset Using Polynomial Chaos-Kriging, Journal of Hydrology, 609, 127716. https://doi.org/10.1016/j.jhydrol.2022.127716
  • Tran, V. N., & Kim, J. (2021). A robust surrogate data assimilation approach to real-time forecasting using polynomial chaos expansion. Journal of Hydrology, 598, 126367. https://doi.org/10.1016/j.jhydrol.2021.126367
  • Ivanov, V. Y., Xu, D., Dwelle, M. C., Sargsyan, K., Wright, D. B., Katopodes, N., Kim, J., Tran, V. N., Warnock, A., Fatichi, S., Burlando, P., Caporali, E., Restrepo, P., Sanders, B. F., Chaney, M. M., Nunes, A. M. B., Nardi, F., Vivoni, E. R., Istanbulluoglu, E., . . . Bras, R. L. (2021). Breaking Down the Computational Barriers to Real-Time Urban Flood Forecasting. Geophysical Research Letters, 48(20), e2021GL093585.
  • Tran, T. D., Tran, V. N., & Kim, J. (2021). Improving the Accuracy of Dam Inflow Predictions Using a Long Short-Term Memory Network Coupled with Wavelet Transform and Predictor Selection. Mathematics, 9(5), 551. https://doi.org/10.3390/math9050551
  • Tran, V. N., & Kim, J. (2021). Toward an Efficient Uncertainty Quantification of Streamflow Predictions Using Sparse Polynomial Chaos Expansion. Water, 13(2), 203. https://doi.org/10.3390/w13020203
  • Tran, V. N., Dwelle, M. C., Sargsyan, K., Ivanov, V. Y., & Kim, J. (2020). A Novel Modeling Framework for Computationally Efficient and Accurate Real-Time Ensemble Flood Forecasting With Uncertainty Quantification. Water Resources Research, 56(3), e2019WR025727. https://doi.org/10.1029/2019wr025727
  • Tran, V. N., & Kim, J. (2019). Quantification of predictive uncertainty with a metamodel: toward more efficient hydrologic simulations. Stochastic Environmental Research and Risk Assessment, 33(7), 1453-1476. https://doi.org/10.1007/s00477-019-01703-0


Footer

Logo for Michigan Engineering at the University of Michigan

  • Giving
  • News and Events
  • Contact
  • Sign up for our newsletter
  • U-M Engineering Home
  • Strategic Vision
  • Graduate and Professional
  • Undergraduate
  • U-M Engineering Research News
  • U-M Home

  • Giving
  • News and Events
  • Contact
  • Sign up for our newsletter

© 2023 The Regents of the University of Michigan Ann Arbor, MI 48109 USA Privacy Policy | Non-Discrimination Policy | Campus Safety

  • Facebook
  • Instagram
  • LinkedIn
  • Twitter
  • YouTube