A Short Bio:

 

Ardeshir is an assistant professor in the department of civil, environmental, and geo-engineering at the University of Minnesota (U of M) as of September 2016. Prior to joining U of M, he has worked as an assistant professor in the department of civil and environmental engineering at Utah State University for a year and as a postdoctoral research fellow at Georgia Institute of Technology for two years. He received his doctoral degree in civil engineering from Saint Anthony Falls Laboratory at the University of Minnesota (UMN) in 2013, where he also received a master degree in mathematics from the School of Mathematics. In his last year at the University of Minnesota, he served as a NASA Earth and Space Science Fellow (NESSF) and as a University of Minnesota Doctoral Dissertation Fellow (DDF). 

Ardeshir received his B.Sc. in civil engineering from Iran University of Science and Technology (IUST) in 1999, where he also received two M.Sc. degrees in environmental and earthquake engineering. He has worked in industry as a design engineer for a few years prior to the start of his doctoral degree in the United States. 

His research experience includes hydrologic data sciences and inverse problems in hydro-meteorological systems, physical hydrology and land-atmosphere interactions, stochastic hydro-meteorology, and environmental risk and extreme value analysis. In the past few years, his major area of research has been focused on hydrologic remote sensing, data assimilation, and land-atmosphere interactions.  

 
Honors and Awards:

 

  • Editor Award, American Meteorological Society (2020) 

  • NASA New (Early Career) Investigator Program (NIP) Award in Earth Science  (2018-2021)

  • NASA Earth and Space Science Fellowship (2012-2014)

  • Doctoral Dissertation Fellowship, University of Minnesota (2012-2013) 

  • Edward Silberman Fellowship, Saint Anthony Falls Laboratory, University of Minnesota (2012-2013)

  • Outstanding Student Paper Award, American Geophysical Union (2011-2012)

  • Interdisciplinary Doctoral Fellowship, Minnesota Center for Industrial Mathematics (MCIM) and Department of Civil Engineering, University of Minnesota (2011-2012)

 

Conference Presentation

 

  1. American Geophysical Union (2009), Orographic Signature on Multiscale Statistics of Extreme Rainfall: The Rapidan Storm of June 1995, San Francisco, CA.

  2. NASA Precipitation Measurement Missions (PMM) Science Team Meeting (2010), Multi-sensor Precipitation Data Fusion with Emphasis on Extremes, Seattle, WA.

  3. American Geophysical Union (2010), Multi-sensor Precipitation Data Fusion with Emphasis on Extremes, San Francisco, CA.

  4. NASA Precipitation Measurement Missions (PMM) Science Team Meeting (2010), Sparse Precipitation Downscaling and Multisensor Retrieval, Denver, CO.

  5. American Geophysical Union (2011), Adaptive Fusion and Sparse Estimation of Multi-sensor Precipitation (oral presentation), San Francisco, CA.

  6. Goddard Space Flight Center, ESSIC (2012), On Estimation of Hydrometeorlogical Signals with Sparse Priors (invited talk), Greenbelt, MD.

  7. American Geophysical Union (2012), Regularized Data Assimilation and Fusion of non-Gaussian States Exhibiting Sparse Prior in Transform Domains, San Francisco, CA.

  8. American Geophysical Union (2012), Variational Rainfall Fusion and Downscaling via l1-Regularization in the Wavelet Domain (oral presentation), San Francisco, CA.

  9. American Geophysical Union (2012), On Adapting Data Assimilation Framework to Data Fusion of Multi-scale Precipitation Observations, San Francisco, CA.

  10. Society of Applied and Industrial Mathematics (AN13), Variational Data Assimilation via Sparse Regularization (oral presentation), San Diego, CA.

  11. European Geophysical Union (2013), Precipitation: From Measurement to Modelling and Application in Catchment Hydrology, Vienna, Austria.

  12. European Geophysical Union (2013), Variational Data Assimilation via Sparse Regularization, Vienna, Austria.

  13. American Geophysical Union (2013), Coping with Model Uncertainty in Data Assimilation using Optimal Mass Transport (oral presentation), San Francisco, CA.

  14. American Geophysical Union (2013), Passive Microwave Rainfall Retrieval: A Mathematical Approach via Sparse Learning, San Francisco, CA.

  15. European Geophysical Union (2014), From Rainfall Downscaling to Rainfall Retrieval: Inverse Problems of Similar Nature, Vienna, Austria.

  16. NASA Precipitation Measurement Mission (2014), A New Algorithm for GPM Passive Microwave Rainfall Retrieval: Extremes, Discontinuities and Spatial Structure (oral presentation), Baltimore, MD.

  17. NASA Precipitation Measurement Mission (2014), Shrunken Locally Linear Embedding Algorithm for Passive Retrieval of Precipitation (ShARP), Baltimore, MD.

  18. American Geophysical Union (2014), A New Framework for Robust Retrieval and Fusion of Active/Passive Multi-Sensor Precipitation (oral presentation), San Francisco, CA.

  19. NASA Precipitation Measurement Mission (2015), Rainfall Microwave Atoms: A New Variational Approach for Combined Passive Retrievals, Baltimore, MD.

  20. American Geophysical Union (2015), Rainfall Microwave Spectral Atoms: A New Class of Bayesian Algorithms for Passive Retrieval (oral presentation), San Francisco, CA.

 

Professional Activities

 

Editorial Services
  • Associate Editor, Journal of Hydrometeorology (March, 2016-present)

Reviewer

  • Journal of Geophysical Research-Atmosphere (AGU)

  • Journal of Water Resources Research (AGU)

  • Journal of Geophysical Research Letter (AGU)

  • Journal of Hydrometeorology (AMS)

  • Journal of Advances in Water Resources, and Journal of Hydrology

Membership
  • AGU hydrology section-precipitation technical committee member (2013-present)

  • American Geophysical Union

  • Society of Industrial and Applied Mathematics

  • American Society of Civil Engineers

  • Registered Professional Engineer (P.E.), Tehran, Iran

Meeting Organization
  • Sparse and Low-rank Modeling in the Geophysical Sciences, SIAM-AN13

Workshops
  • Interdisciplinary Summer School on Data Assimilation in Geosciences, Center for Scientific c Computation and Mathematical Modeling, University of Maryland, June 3-14, 2013

  • Applied Statistics and Machine Learning, Institute of Mathematics and its Applications, University of Minnesota, June 17-28, 2013

 

Advisers:

 

Rafael L. Bras, Post Doctoral Research --- Land-atmosphere interactions and satellite data assimilation into the WRF model 

Efi Foufoula-Georgiou, Ph.D in Civil Engineering (Hydrology)---Thesis: Advanced Frameworks for Precipitation Estimation from Space

Gilad Lerman, M.Sc. in Mathematics (Data Sciences)---Thesis: Leveraging Sparsity in Variational Data Assimilation

Ali Kaveh, M.Sc. in Earthquake Engineering 

Abbas Afshar, M.Sc. in Environmental Engineering

 

I also I would like to acknowledge the role of other mentors, especially, Chris Paola, Heinz Stefan, Tom Luo, and Ofer Zeitouni in my academic progress. 

© 2015 by Hydrologic Sciences and remote sensing laboratory

Do not fear to be eccentric in opinion, for every opinion

now accepted was once eccentric. - Bertrand Russell