 Ph.D., UNSW Sydney, School of Civil and Env. Eng., Australia, Nov 2017.  M.Eng., Korea University, Department of Civil and Environmental Engineering, South Korea, Feb 2008.  B.Eng, Korea University, Department of Civil and Environmental Engineering, South Korea, Feb 2001.

 Assistant Professor, Kyung Hee University, South Korea, Mar 2022–present  Postdoctoral Research Associate, UNSW Sydney, Australia, Apr 2017–Feb 2022  Associate manager, Water resources engineering in HDEC, South Korea, Jan 2008–Jul 2013  Compulsory military service (1st lieutenant), Republic of Korea Army, Jul 2001–Sept 2004

 Kim S., Sharma A., Wasko C., Nathan R. (2022) Linking total precipitable water to precipitation extremes globally, Earth’s Future, 10(2), e2021EF002473.  Yoon H.N., Marshall L., Sharma A., Kim S. (2022) Bayesian model calibration using surrogate streamflow in ungauged catchments, Water Resour. Res., 58, e2021WR031287.  Kim S., Sharma, A., Liu, Y., Young, S. I. (2022) Rethinking Satellite Data Merging: From Averaging to SNR Optimization, IEEE Trans. Geosci. Remote Sens., 60, 1–15.  Kim S., Dong J., Sharma A. (2021) A triple collocation-based comparison of three L-band soil moisture datasets, SMAP, SMOS-IC, and SMOS, over varied climates and land covers, Front. Water., 3, 64.  Zhang R., Kim S., Sharma A., Lakshmi V. (2021). Identifying relative strengths of SMAP, SMOS-IC, and ASCAT to capture temporal variability using a model combination approach, Remote Sens. Environ., 252, 112126.  Kim S., Anabalón A., Sharma A. (2021) An Assessment of Concurrency in Evapotranspiration Trends Across Multiple Global Datasets, J. Hydrometeorol., 22(1), 231–244.  Kim S., Pham H., Liu Y., Marshall L., Sharma A. (2020). Improving the combination of satellite soil moisture datasets by considering error cross-correlation: A comparison between triple collocation (TC) and extended double instrumental variable (EIVD) alternatives, IEEE Trans. Geosci. Remote Sens., 59(9), 7285–7295.  Kim S., Ajami H., Sharma A. (2020). Using remotely sensed information to improve vegetation parameterization in a semi-distributed hydrological model (SMART) for upland catchments in Australia, Remote Sens., 12(18), 3501,  Kim S., Eghdamirad S., Sharma A., Kim J. H. (2020). Quantification of uncertainty in projections of extreme daily precipitation, Earth and Space Sci., 2020, e2019EA001052-T.  Kim S., Zhang R., Pham H., Sharma A. (2019). A review of satellite-derived soil moisture and its usage for flood estimation, Remote Sens. Earth Syst. Sci., 2, 225–246.  Zhang R., Kim S., Sharma A. (2019). A comprehensive validation of the SMAP Enhanced Level-3 Soil Moisture product using ground measurements over varied climates and landscapes, Remote Sens. Environ., 223, 82-94.  Kim S., Sharma A. (2019). The role of floodplain topography in deriving basin discharge using passive microwave remote sensing, Water Resour. Res., 55(2), 1707-1716.  Kim S., Paik K., Johnson F., Sharma A. (2018). Building a flood warning framework for ungauged locations using low resolution, open access remotely sensed surface soil moisture, precipitation, soil and topographic information, IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens., 11(2), 375-387.  Kim S., Balakrishnan K., Liu Y., Johnson F., Sharma A. (2017). Spatial Disaggregation of Coarse Soil Moisture Data by Using High Resolution Remotely Sensed Vegetation Products, IEEE Geosci. Remote. Sens. Lett., 14(9), 1604-1608.  Kim S., Parinussa R., Liu Y., Johnson F., Sharma A. (2015). A framework for combining multiple soil moisture retrievals based on maximizing temporal correlation, Geophys. Res. Lett., 42 (16), 2015GL064981.  Kim S., Liu Y., Johnson F., Parinussa R., Sharma A. (2015). A global comparison of alternate AMSR2 soil moisture products: Why do they differ? Remote Sens. Environ., 161, 43-62.

 Member, Korean Society of Civil Engineers (KSCE)  Member, Korea Water Resources Association (KWRA)  Member, Korean Society of Remote Sensing (KSRS)  Conference session convener: MODSIM 2021  Editorial board: MDPI Remote Sensing (topic editor and volunteer reviewer)

 Remote sensing in hydrology (validation, improvement and application)  Data analysis  Climate change and extreme events  Data merging  Optimization of water systems  Climate change impact analysis