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Bidhyananda Yadav, PhD

Research Associate & Geosensing Engineer
Byrd Polar and Climate Research Center
The Ohio State University, Columbus, OH 43210
Email: yadav.111@osu.edu

Technical Summary

A physical scientist and spatial engineer with more than 7 years of experience leading complex geospatial, remote sensing, and machine learning research for NASA and NSF initiatives. Expert in large-scale geocomputation on high-performance computers, multi-sensor satellite fusion, and machine learning architectures applied to hydrology, glaciology, and cryogenic systems.

Education

  • PhD in Civil Engineering — University of Florida (UF) | 08/2018
    • Dissertation: Modeling of surface runoff processes in ungauged basins – A geocomputational approach
  • MS in Civil Engineering (Geosensing Systems Engineering / LiDAR) — University of Florida | 2009
  • MSc in Geo-Information Science — Wageningen University, Netherlands | 2004
  • BSc in Environmental Science — Kathmandu University, Nepal | 2001

Professional Interests & Core Coursework

  • Engineering Geodesy & GIS: Spatial Modeling, Geo-statistics, Advanced GIS, Cartography, Database Management.
  • Remote Sensing: Laser-based Sensing (LiDAR), Optical Systems, Radar/SAR, Hyperspectral Image Processing.
  • Deep Learning & Signal Processing: Pattern Recognition, Computer Vision, Probability Theory, Least Squares Adjustment, Kalman Filtering.

Professional Representation & Experience

Research Associate 2-Physical (GIS/Remote Sensing)

The Ohio State University, Byrd Polar and Climate Research Center | 01/2019 – Present * NASA SWOT Satellite Mission: Co-led remote sensing workflows for river discharge and lake dynamics modeling. Developed and host the worldwide SWOT visual analytics dashboard (swotvis.cuahsi.io). * Continental Snow Water Equivalent Modeling: Fused land surface models (LIS) with MODIS and VIIRS observations to create a 20-year daily high-resolution (0.01°) Snow Water Equivalent (SWE) dataset for North America. * Deep Learning for Hydrology: Crafted Deep Neural Network (DNN) super-resolution architectures to classify water bodies from Sentinel-2 and high-resolution commercial imagery (supporting the ArcticDEM Hydrology project). * Greenland Glacier Fluxes: Automated satellite image processing pipelines using Sentinel-2 to detect glacier margins and correct systematic orthorectification offsets in glacier velocity maps. * ICESat-2 Geospatical Toolkit: Programmed pipeline wrappers to download and correct vertical bias across Antarctica and Arctic topography models (ArcticDEM, REMA, WorldDEM). * Fluid Earth Viewer (FEV): Technical lead for the web platform (fever.byrd.osu.edu) rendering real-time global atmospheric and ocean currents.

Graduate Research Assistant

University of Florida, Civil Engineering Department | 01/2010 – 01/2019 * Built automated spatial ETL and ML scripts utilizing Python (Arcpy) and Matlab to download, clean, and model ungauged watershed runoff, geomorphological configurations, and hourly rainfall profiles. * Merged heterogeneous raster/vector datasets (NEXRAD, soils, land use, and high-res DEMs) to predict baseflow indexes and calculate hourly watershed catchment evapotranspiration and NDVI profiles from MODIS (MOD16A2 and MOD13A1).

Research Assistant

National Center for Airborne Laser Mapping (NCALM) | 01/2006 – 12/2009 * Led QA/QC workflows, point processing, and feature extraction of airborne LiDAR point clouds, developing custom scripts to extract river fluvial geodynamics.

M&E / MIS Officer

United Nations Development Programme (UNDP), Nepal | 05/2005 – 12/2005 * Designed relational database systems (MS Access/SQL Server) to track, parse, and analyze questionnaire data. Provided software database training to analysts and QA/QC team leaders.

Granted Infrastructure & Funding

  • NASA Grant (Co-Investigator, 2022–2024, $925,353):
    Adopting SWOT measurements to improve decision making for currently ungated basins: Decision support for Alaska.
  • NSF Grant (Collaborator, 2019–2024, $106,230):
    The Permafrost Discovery Gateway – Navigating the New Arctic tundra through Big Imagery, artificial intelligence, & cyberinfrastructure.

Selected Publications

  1. Shutkin, T.Y. et al. (2025). Modeling the impacts of climate trends and lake formation on the retreat of a tropical Andean glacier (1962-2020), The Cryosphere, 19, 4835–4853.
  2. Andreadis, K.M., et al. (2025). A first look at river discharge estimation from SWOT satellite observations, Geophysical Research Letters, 52, e2024GL114185.
  3. Durand, M., Dai, C., Moortgat, J., Yadav, B. et al. (2024). Using river hypsometry to improve remote sensing of river discharge, Remote Sensing of Environment, 315, 114455.
  4. Ziwei, L., Leong, W. J., Durand, M., Howat, I., Wadkowski, K., Yadav, B., Moortgat, J. (2023). Super-resolution deep neural networks for water classification from free multispectral satellite imagery, Journal of Hydrology, 626, 130248.
  5. Moortgat, J., Ziwei, L., Durand, M., Howat, I., Yadav, B. (2022). Deep learning models for river classification at sub-meter resolutions from multispectral and panchromatic commercial satellite imagery, Remote Sensing of Environment, 282, 113279.
  6. Chudley, T.R., Howat, I.M., Yadav, B., and Noh, M.J. (2022). Empirical correction of systematic orthorectification error in Sentinel-2 velocity fields for Greenlandic outlet glaciers, The Cryosphere, 16, 2629–2642.
  7. Yadav, B. and Hatfield, K. (2018). Stream network conflation with topographic DEMs, Environmental Modelling & Software, 102, 241–249.

Professional Services & Community Leadership

  • Proposal Panelist: Evaluating technical submissions for NASA ROSES grants.
  • Academic Reviewer: Regular referee for International Journal of Digital Earth, Journal of Mountain Science, and NSF EarthCube Jupyter Notebook selections.
  • Committees: OSU Geospatial Steering Committee.
  • Web Architect: Maintained web portals for the National Center for Airborne Laser Mapping (NCALM), UF Nepalese Student Association, and UF Geosensing Engineering.