About me
I am a computational modeler currently completing my PhD at University of Illinois at Urbana-Champaign. My PhD focuses on computational modeling of earth systems and water sustainability issues under climate change. Before that, I received my B.S. in Hydraulic engineering and a second Bachelor of Economics from Tsinghua University, China. I am passionate about applying machine learning, combined with insights of physical modeling, to solve real world issues. I’m looking for full-time positions in both industry and academia starting from 2024.
Education
Aug 2018 - Apr 2024
Ph.D. in Earth System Science
College of Agricultural, Consumer and Environmental Sciences
University of Illinois at Urbana-Champaign
B.S. in Hydraulic Engineering
Department of Hydraulic Engineering
Tsinghua University
B.S. in Economics
School of Economics and Management
Tsinghua University
Research Interest
Computational modeling of complex systems
I use combined physical (process-based) and statistical (machine learning) models to simulate complex systems, with a focus currently on earth and climate science. Especially, how complex physical models can be simplified for increased efficiency in estimation and prediction, how to quantify and improve the robustness and trustworthiness of inferred process understanding from model-data fusion given the scarcity and uncertainty of observation data (a ubiquitous issue in earth and climate science), and how process-based and machine learning-based models can be combined to reliably and efficiently simulate complex systems constrained by observation data of varying uncertainties.
Water sustainability under climate change
The sustainability of water resources is a major concern under climate change. My PhD specifically focuses on how plants respond to drought and the sustainability issues of water resources in agricultural ecosystems.
Publications
Yang Y., Guan, K., Peng, B., Feng, X., et al. A unified framework to reconcile different theories of modeling transpiration response to drought: plant hydraulics, supply-demand balance, and empirical soil water stress. [In review. Link to conference presentation]
Yang Y., Guan, K., Peng, B., Liu, Y., Pan, M., 2024. Explicit consideration of plant xylem hydraulic transport improves the simulation of crop response to atmospheric dryness in the US Corn Belt. Water Resources Research, 60(6), p.e2023WR036468. [Link]
Yang Y., Peng, B., Guan, K., Pan, M., Franz, T.E., Cosh, M.H. and Bernacchi, C.J., 2024. Within-field soil moisture variability and time-invariant spatial structures of agricultural fields in the US Midwest. Vadose Zone Journal, e20337. [Link][News]
Zhang, J., Guan, K., Zhou, W., Jiang, C., Peng, B., Pan, M., Grant, R.F., Franz, T.E., Suyker, A., Yang, Y. and Chen, X., 2023. Combining Remotely Sensed Evapotranspiration and an Agroecosystem Model to Estimate Center‐Pivot Irrigation Water Use at High Spatio‐Temporal Resolution. Water Resources Research, 59(3), p.e2022WR032967. [Link]
Wang, S., Guan, K., Zhang, C., Zhou, Q., Wang, S., Wu, X., Jiang, C., Peng, B., Mei, W., Li, K., Li, Z., Yang, Y., Zhou, W., Huang Y. and Ma Z., 2023. Cross-scale sensing of field-level crop residue cover: Integrating field photos, airborne hyperspectral imaging, and satellite data. Remote Sensing of Environment, 285, p.113366. [Link]
Pal, S., Dominguez, F., Bollatti, P., Oncley, S.P., Yang, Y., Alvarez, J. and Garcia, C.M., 2021. Investigating the effects of land use change on subsurface, surface, and atmospheric branches of the hydrologic cycle in central Argentina. Water Resources Research, 57( 11), p.e2021WR029704. [Link]
Zhang, J., Guan, K., Peng, B., Pan, M., Zhou, W., Jiang, C., Kimm, H., Franz, T.E., Grant, R.F., Yang, Y. and Rudnick, D.R., 2021. Sustainable irrigation based on co-regulation of soil water supply and atmospheric evaporative demand. Nature communications, 12(1), p.5549. [Link]
Zhang, J., Guan, K., Peng, B., Pan, M., Zhou, W., Grant, R.F., Franz, T.E., Rudnick, D.R., Heeren, D.M., Suyker, A. and Yang, Y., Assessing different plant‐centric water stress metrics for irrigation efficacy using soil‐plant‐atmosphere‐continuum simulation. Water Resources Research, 57(9), p.e2021WR030211. [Link]
Yang, Y., Guan, K., Peng, B., Pan, M., Jiang, C. and Franz, T.E., 2021. High-resolution spatially explicit land surface model calibration using field-scale satellite-based daily evapotranspiration product. Journal of Hydrology, 596, p.125730. [Link]
Zhang, J., Guan, K., Peng, B., Jiang, C., Zhou, W., Yang, Y., Pan, M., Franz, T.E., Heeren, D.M., Rudnick, D.R. and Abimbola, O.,2021. Challenges and opportunities in precision irrigation decision-support systems for center pivots. Environmental Research Letters, 16(5), p.053003. [Link]
Wang, C., Xu, J., Tang, G., Yang, Y. and Hong, Y., 2020. Infrared precipitation estimation using convolutional neural network. IEEE Transactions on Geoscience and Remote Sensing, 58(12), pp.8612-8625. [Link]
Teaching Experience
NRES405 Watershed Hydrology (Spring 2019)
Teaching Assistant
@University of Illinois at Urbana-Champaign
Introduction to Coastal Engineering (Spring 2017 & Spring 2018)
Teaching Assistant
@Tsinghua University
Journal Reviewer
Water Resources Research, Remote Sensing of Environment, Global Change Biology, Plant, Cell & Environment, Journal of Hydrology, Agricultural Water Management, Atmospheric Research, Agronomy Journal, Applied Water Science