I am a Research Assistant Professor at Department of Natural Resources and Environmental Sciences (NRES) and Senior Research Scientist at Institute for Sustainability, Energy, and Environment (ISEE), University of Illinois at Urbana-Champaign (UIUC). I was broadly trained in both science (geography, agriculture, hydrology, ecology, crop physiology, global climate change) and engineering (computer engineering and high-performance computing, civil & environmental engineering, and geoinformatics engineering). My primary research interests are computational and process-based modeling (hydrological, cropping system, ecosystem and earth system modeling), remote sensing, model-data integration, geospatial big data and artificial intelligence for digital agriculture, sustainable agri-food systems and human-environment interactions. The overarching goal of my research is to deepen our understanding of terrestrial carbon-water-nutrient cycles and human impacts on managed or unmanaged ecosystems under climate change and land use intensification, to develop innovative engineering technologies and finally find systems solutions for sustainable agri-food systems and ecosystem management. The societal drivers for these research interests include climate change adaptation and mitigation, managing the risk of hydrometeorological and hydroclimatological disasters like droughts and floods, ensuring water, energy and food securities and environmental sustainability, as well as fostering rural economy and farmer wellbeing. Over the past years, I have been focusing on the U.S. Midwestern agroecosystems.

  • Ecohydrology
  • Agroecology
  • Remote Sensing
  • Ecosystem modeling
  • Crop modeling
  • Ph.D. in Geoinformatics, 2016

    Chinese Academy of Sciences

  • B.S. in Geography, 2011

    Nanjing University


University of Illinois at Urbana-Champaign
Research Assistant Professor
Nov 2021 – Present Urbana-Champaign
University of Illinois at Urbana-Champaign
Senior Research Scientist
Nov 2021 – Present Urbana-Champaign
University of Illinois at Urbana-Champaign
Research Scientist
Apr 2020 – Nov 2021 Urbana-Champaign
University of Illinois at Urbana-Champaign
Postdoctoral Research Fellow
Jul 2016 – Apr 2020 Urbana-Champaign
Chinese Academy of Sciences
Graduate Research Assistant
Sep 2012 – Jul 2016 Beijing

Journal Publications

† Equally contributed, * Corresponding author.

  1. Guan, K.*, Jin, Z.*, Peng, B.*, Tang, J.*, DeLucia, E., West, P., Jiang, C., Wang, S., Kim, T., Zhou, W., Griffis, T., Liu, L., Yang, W., Qin, Z., Yang, Q., Margenot, A., Stuchiner, E., Kumar, V., Bernacchi, C., Coppess, J., Novick, K., Gerber, J., Jahn, M., Khanna, M., Lee, D., Chen, Z., Yang, S. (2023). A scalable framework for quantifying field-level agricultural carbon outcomes. Earth-Science Reviews.
  2. Zhang, J., Guan, K., Fu, R., Peng, B., Zhao, S., Zhuang, Y. (2023). Evaluating seasonal climate forecasts from dynamical models over South America. Journal of Hydrometeorology.
  3. Kimball, B. et al (including Peng, B.). (2023). Simulation of evapotranspiration and yield of maize: An inter-comparison among 41 maize models. Agricultural and Forest Meteorology.
  4. Zhang, J., Guan, K., Zhou, W., Jiang, C., Peng, B., Pan, M., Grant, R.,Franz, T., Suyker, A., Yang, Y., Chen, X., Lin, K., Ma, Z. (2023). Combining remotely sensed evapotranspiration and an agroecosystem model to estimate center-pivot irrigation water use at high spatio-temporal resolution. Water Resource Research.
  5. Qin, Z., Guan, K., Zhou, W., Peng, B., Tang, J., Jin, Z., Grant, R., Hu, T., Villamil, M.B., DeLucia, E., Margenot, A.J., Mishra, U., Chen, Z., & Coppess, J. (2023). Assessing long-term impacts of cover crops on soil organic carbon in the central U.S. Midwestern agroecosystems. Global Change Biology.
  6. Liu, K., Harrison, M.T., Yan, H., Liu, D.L., Meinke, H., Hoogenboom, G., Wang, B., Peng, B., Guan, K., Jaegermeyr, J., Wang, E., Zhang, F., Yin, X., Archontoulis, S., Nie, L., Badea, A., Man, J., Wallach, D., Zhao, J., Benjumea, A.B., Fahad, S., Tian, X., Wang, W., Tao, F., Zhang, Z., Rötter, R., Yuan, Y., Zhu, M., Dai, P., Nie, J., Yang, Y., Zhang, Y., & Zhou, M. (2023). Silver lining to a climate crisis in multiple prospects for alleviating crop waterlogging under future climates. Nature communications.
  7. Zhou, Q., Wang, S., Liu, N., Townsend, P., Jiang, C., Peng, B., Verhoef, W., Guan, K. (2023). Towards operational atmospheric correction of airborne hyperspectral imaging spectroscopy: Algorithm evaluation, key parameter analysis, and machine learning emulators. Remote Sensing of Environment.
  8. Zhou, W., Guan, K., Peng, B., Margenot, A., Lee, D.K., Tang, J., Jin, Z., Grant, R., DeLucia, E., Qin, Z., Wander, M., Wang, S. (2023). How does uncertainty of soil organic carbon stock affect the calculation of carbon budgets and soil carbon credits for croplands in the US Midwest? Geoderma.
  9. 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., 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.
  10. Burroughs, C., Montes, C., Moller, C., Mitchell, N., Michael, A., Peng, B., Kimm, H., Pederson, T., Lipka, A., Bernacchi, C., Guan, K., Ainsworth, E. (2022). Reductions in Leaf Area Index, Pod Production, Seed Size and Harvest Index Drive Yield Loss to High Temperatures in Soybean. Journal of Experimental Botany.
  11. Ma, Z., Guan, K.*, Peng, B.*, Sivapalan, M., Li, L., Pan, M., Zhou, W., Warner, R., Zhang, J. (2022). Agricultural Nitrate Export Patterns Shaped by Crop Rotation and Tile Drainage. Water Research.
  12. Zhou, Q., Guan, K., Wang, S., Jiang, C., Huang, Y., Peng, B., Chen, Z., Wang, S., Hipple, J., Schaefer, D., Qin, Z., Stroebel, S., Coppess, J., Khanna, M., Cai, Y. (2022). Recent rapid increase of cover crop adoption across the US Midwest detected by fusing multi‐source satellite data. Geophysical Research Letters.
  13. Yang, Y., Liu, L., Zhou, W., Guan, K., Tang, J., Kim, T., Grant, R., Peng, B., Zhu, P., Li, Z., Griffis, T., Jin, Z. (2022). Distinct driving mechanisms of non-growing season N2O emissions call for spatial-specific mitigation strategies in the US Midwest. Agricultural and Forest Meteorology.
  14. Jong, M., Guan, K., Wang, S., Huang, Y., Peng, B. (2022). Improving field boundary delineation in ResUNets via adversarial deep learning . International Journal of Applied Earth Observation and Geoinformation.
  15. Li, Z., Guan, K., Zhou, W., Peng, B., Jin, Z., Tang, J., Grant, R., Nafziger, E., Margenot, A., Gentry, L., DeLucia, E., Yang, W., Cai, Y., Qin, Z., Archontoulis, S., Fernández, F., Yu, Z., Lee, D.K., Yang, Y. (2022). Assessing the impacts of pre-growing-season weather conditions on soil nitrogen dynamics and corn productivity in the U.S. Midwest. Field Crops Research.
  16. Liu, L., Xu, S., Jin, Z., Tang, J., Guan, K., Griffis, T., Erickson, M., Frie, A., Jia, X., Kim, T., Miller, L., Peng, B., Wu, S., Yang, Y., Zhou, W., Kumar, V. (2022). KGML-ag: A Modeling Framework of Knowledge-Guided Machine Learning to Simulate Agroecosystems: A Case Study of Estimating N2O Emission using Data from Mesocosm Experiments. Geoscientific Model Development.
  17. Xu, R., Li, Y., Guan, K., Zhao, L., Peng, B., Miao, C., Fu, B. (2021). Divergent responses of maize yield to precipitation in the United States. Environmental Research Letters.
  18. Peng, B.*, Guan, K. (2021). Harmonizing climate-smart and sustainable agriculture. Nature Food.
  19. Kumagai, E., Burroughs, C., Pederson, T., Montes, C., Peng, B., Kimm, H., Guan, K., Ainsworth, E., Bernacchi, C. (2021). Predicting biochemical acclimation of leaf photosynthesis in soybean under in-field canopy warming using hyperspectral reflectance. Plant, Cell & Environment.
  20. Li, K., Guan, K., Jiang, C., Wang, S., Peng, B., and Cai, Y. (2021). Evaluation of four new land surface temperature (LST) products in the U.S. Corn Belt: ECOSTRESS, GOES-R, Landsat, and Sentinel-3. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.
  21. Zhang, J., Guan, K., Peng, B., Pan, M., Zhou, W., Grant, R., Franz, T., Rudnick, D., Heeren, D., Suyker, A., Yang, Y., Wu, G. (2021). Assessing different plant-centric water stress metrics for irrigation efficacy using soil-plant-atmosphere-continuum simulation. Water Resources Research.
  22. Zhou, W.*, Guan, K.*, Peng, B.*, Wang, Z., Fu, R., Li, B., Ainsworth, E., DeLucia, E., Zhao, L., and Chen, Z. (2021). A generic risk assessment framework to evaluate historical and future climate-induced risk for rainfed corn and soybean yield in the U.S. Midwest. Weather and Climate Extremes.
  23. Qin, Z., Guan, K., Zhou, W., Peng, B., Villamil, M., Jin, Z., Tang, J., Grant, R., Gentry, L., Margenot, A., Bollero, G., Li, Z. (2021). Assessing the impacts of cover crops on maize and soybean yield in the U.S. Midwestern agroecosystems. Field Crops Research.
  24. Zhang, J.*, Guan, K.*, Peng, B.*, Pan, M., Zhou, W., Jiang, C., Kimm, H., Franz, T., Grant, R., Yang, Y., Rudnick, D., Heeren, D., Suyker, A., Bauerle, W., Miner, G. (2021). Sustainable irrigation based on co-regulation of soil water supply and atmospheric evaporative demand. Nature Communications.
  25. Kim, T., Jin, Z., Smith, T., Liu, L., Yang, Y., Yang, Y., Peng, B., Phillips, K., Guan, K., Hunter, L., Zhou, W. (2021). Quantifying nitrogen loss hotspots and mitigation potential for individual fields in the US Corn Belt with a metamodeling approach. Environmental Research Letters.
  26. Zhou, W.*, Guan, K.*, Peng, B.*, Tang, J., Jin, Z., Jiang, C., Grant, R., Mezbahuddin, S. (2021). Quantifying carbon budget, crop yields and their responses to environmental variability using the ecosys model for U.S. Midwestern agroecosystems. Agricultural and Forest Meteorology.
  27. Xu, T., Guan, K., Peng, B., Wei, S., Zhao, L. (2021). Machine Learning-Based Modeling of Spatio-Temporally Varying Responses of Rainfed Corn Yield to Climate, Soil, and Management in the U.S. Corn Belt. Frontiers in Artificial Intelligence, 4.
  28. Kimm, H., Guan, K., Burroughs, C. H., Peng, B., Ainsworth, E. A., Bernacchi, C. J., Moore, C. E., Kumagai, E., Yang, X., Berry, J. A., Wu, G. (2021). Quantifying high-temperature stress on soybean canopy photosynthesis: The unique role of sun-induced chlorophyll fluorescence. Global Change Biology 27, 2403-2415.
  29. Zhang, J., Guan, K., Peng, B., Jiang, C., Zhou, W., Yang, Y., Pan, M., Franz, T., Heeren, D., Rudnick, Peng Abimbola, O., Kimm, H., Caylor, K., Good, S., Khanna, M., Gates, J., Cai, Y. (2021). Challenges and opportunities in precision irrigation decision-support systems for center pivots. Environmental Research Letters.
  30. Jiang, C., Guan, K., Wu, G., Peng, B., Wang, S. (2021). A daily, 250 m, and real-time gross primary productivity product (2000 – present) in the Contiguous United States. Earth System Science Data.
  31. Yang, Y., Guan, K., Peng, B., Pan, M., Jiang, C., Franz, T. (2021). High-resolution spatially explicit land surface model calibration using field-scale satellite-based daily evapotranspiration product. Journal of Hydrology.
  32. Peng, B.*, Guan, K.*, Tang, J., Ainsworth, E.A., Asseng, S., Bernacchi, C.J., Cooper, M., Delucia, E.H., Elliott, J.W., Ewert, F., Grant, R.F., Gustafson, D.I., Hammer, G.L., Jin, Z., Jones, J.W., Kimm, H., Lawrence, D.M., Li, Y., Lombardozzi, D.L., Marshall-Colon, A., Messina, C.D., Ort, D.R., Schnable, J.C., Vallejos, C.E., Wu, A., Yin, X., Zhou, W. (2020). Towards a multiscale crop modelling framework for climate change adaptation assessment. Nature Plants, 6, 338-348. (ESI Highly Cited Paper)
  33. Peng, B.*, Guan, K.*, Zhou, W., Jiang, C., Frankenberg, C., Sun, Y., He, L., Köhler, P. (2020). Assessing the benefit of satellite-based Solar-Induced Chlorophyll Fluorescence in crop yield prediction. International Journal of Applied Earth Observation and Geoinformation, 90, 102126.
  34. Zhou, W., Guan, K., Peng, B., Shi, J., Jiang, C., Wardlow, B., Pan, M., Kimball, J., Franz, T., Gentine, P., He, M., Zhang, J. (2020). Connections between hydrological cycle and crop yield in the rainfed U.S. Corn Belt. Journal of Hydrology.
  35. Paul, R., Cai, Y., Peng, B., Yang, W., Guan, K., DeLucia, E. (2020). Spatiotemporal derivation of intermittent ponding in a maize-soybean landscape from Planet Labs CubeSat images. Remote Sensing.
  36. He, L., Magney, T., Dutta, D., Yin, Y., Köhler, P., Grossmann, K., Stutz, J., Dold, C., Hatfield, J., Guan, K., Peng, B., Frankenberg, C. (2020). From the ground to space: Using solar-induced chlorophyll fluorescence to estimate crop productivity. Geophysical Research Letters, 47 (7), e2020GL087474.
  37. Wang, C., Guan, K., Peng, B., Chen, M., Jiang, C., Zeng, Y., Wang, S., Wu, J., Yang, X.,Frankenberg, C., Köhler, P., Berry, J., Bernacchi, B., Zhu, K., Alden, C., Miao, G. (2020). Satellite footprint data from OCO-2 and TROPOMI reveal significant spatio-temporal and inter-vegetation type variabilities of solar-induced fluorescence yield in the U.S. Midwest. Remote Sensing of Environment. 241, 111728.
  38. Jiang, C., Guan, K., Pan, M., Ryu, Y., Peng, B., Wang, S. (2020). BESS-STAIR: a framework to estimate daily, 30-meter, and all weather crop evapotranspiration using multi-source satellite data for the U.S. Corn Belt. Hydrology Earth System Science. 24, 1251–1273.
  39. Benes, B.†, Guan, K.†, Lang, M.†, Long, S.†, Lynch, J.†, Marshall-Colón, C.†, Peng, B.†, Schnable, J.†, Sweetlove, L.†, Turk, M.† (2020). Multiscale computational models can guide experimentation and targeted measurements for crop improvement. The Plant Journal. (All authors contributed equally to the conception of the presented idea and the writing of the manuscript. Authors are listed alphabetically of their last names)
  40. Wu, G., Guan, K., Jiang, C., Peng, B., Kimm, H., Chen, M., Yang, X., Wang, S., Suyker, A., Bernacchi, C., Moore, C., Zeng, Y., Berry, J., Cendrero-Mateo, M. P. (2020). Radiance-based NIRv as a proxy for GPP of corn and soybean. Environmental Research Letters. 15, 034009.
  41. Li, Y., Guan, K., Peng, B., Franz, T., Wardlow, B., Pan, M. (2020). Quantifying irrigation cooling benefits to maize yield in the US Midwest. Global Change Biology, 26(5): 3065-3078.
  42. Cheng, Y., Huang, M., Chen, M., Guan, K., Bernacchi, C., Peng, B., Tan, Z. (2020). Parameterizing perennial bioenergy crops in Version 5 of the Community Land Model based on site-level observations in the Central Midwestern United States. Journal of Advances in Modeling Earth Systems. 12: e2019MS001719.
  43. Kimm, H., Guan, K., Jiang, C., Peng, B., Gentry, L., Wilkin, S., Wang, S., Cai, Y., Bernacchi, C., Peng, J., Luo, Y. (2020). Deriving high-spatiotemporal-resolution leaf area index for agroecosystems in the U.S. Corn Belt using Planet’s CubeSAT and STAIR fusion data. Remote Sensing of Environment. 239: 111615.
  44. Cai, Y., Guan, K., Nafziger, E., Chowdhary, G., Peng, B., Jin, Z., Wang, S., Wang, S. (2019). Detecting in-season crop nitrogen stress of corn for field trials using UAV- and CubeSat-based multispectral sensing. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 12(12): 5153-5166.
  45. Zhou, W., Shi, J., Wang, T., Peng, B., Yu, Y., Zhao, R., Yao, R. (2019). New methods for deriving clear-sky surface longwave downward radiation based on remotely sensed data and ground measurements. Earth and Space Science. 6, 2071-2086.
  46. DeLucia, E., Chen, S., Guan, K., Peng, B., Li, Y., Gomez-Casanovas, N., Kantola, I., Bernacchi, C., Long, S., Ort, D. (2019). Are We Approaching a Water Ceiling to Maize Yields in the United States? Ecosphere. 10(6):02773.
  47. Zhu, P., Zhuang, Q., Welp, L., Ciais, P., Heimann, M., Peng, B., Li, W., Bernacchi, C., Rodenbeck, C., Keenan, T. (2019). Recent warming has resulted in smaller gains in net carbon uptake in northern high latitudes. Journal of Climate. 32, 5849-5863.
  48. Li, Y., Guan, K., Schnitkey, G.D., DeLucia, E., Peng, B. (2019). Excessive rainfall leads to maize yield loss of a comparable magnitude to extreme drought in the United States. Global Change Biology, 25, 2325-2337.
  49. Cai, Y., Guan, K., Lobell, D., Potgieter, A., Wang, S., Peng, J., Xu, T., Asseng, S., Zhang, Y., You, L., and Peng, B. (2019). Integrating satellite and climate data to predict wheat yield in Australia using machine learning approaches. Agricultural and Forest Meteorology. 274: 144-159. (ESI Highly Cited Paper)
  50. Li, Y., Guan, K., Yu, A., Peng, B., Zhao, L., Li, B., & Peng, J. (2019). Toward building a transparent statistical model for improving crop yield prediction: Modeling rainfed corn in the U.S. Field Crops Research, 234, 55-65.
  51. Peng, B.*, Guan, K.*, Pan, M., Li, Y. (2018). Benefits of seasonal climate prediction and satellite data for forecasting US maize yield. Geophysical Research Letters, 45, 9662-9671.
  52. Peng, B.*, Guan, K.*, Chen, M., Lawrence, D.M., Pokhrel, Y., Suyker, A., Arkebauer, T., Lu, Y. (2018). Improving maize growth processes in the community land model: Implementation and evaluation. Agricultural and forest meteorology, 250–251, 64-89.
  53. Zhou, W., Shi, J., Wang, T., Peng, B., Zhao, R., Yu, Y. (2018). Clear-Sky Longwave Downward Radiation Estimation by Integrating MODIS Data and Ground-Based Measurements. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 12(2), 450-459.
  54. Xu, Z., Guan, K., Casler, N., Peng, B., Wang, S. (2018). A 3D convolutional neural network method for land cover classification using LiDAR and multi-temporal Landsat imagery. ISPRS Journal of Photogrammetry and Remote Sensing, 144, 423-434.
  55. Miao, G., Guan, K., Yang, X., Bernacchi, C., Berry, J., DeLucia, E., Wu, J., Moore, C., Meacham, K., Cai, Y., Peng, B., Kimm, H., Masters, M. (2018). Sun-Induced Chlorophyll Fluorescence, Photosynthesis, and Light Use Efficiency of a Soybean Field . Journal of Geophysical ResearchBiogeosciences, 123, 610–623. (ESI Highly Cited Paper)
  56. Peng, B.*, Zhao, T.*, Shi, J., Lu, H., Mialon, A., Kerr, Y.H., Liang, X., Guan, K. (2017). Reappraisal of the roughness effect parameterization schemes for L-band radiometry over bare soil. Remote Sensing of Environment, 199, 63-77.
  57. Zhou, W., Peng, B.*, Shi, J.* (2017). Reconstructing spatial-temporal continuous MODIS land surface temperature using the DINEOF method. Journal of Applied Remote Sensing, 11(4), 046016.
  58. Zhou, W.†, Peng, B.†*, Shi, J.*, Wang, T., Dhital, Y.P., Yao, R., Yu, Y., Lei, Z., Zhao, R. (2017). Estimating high resolution daily air temperature based on remote sensing products and climate reanalysis datasets over glacierized basins: a case study in the Langtang Valley, Nepal. Remote Sensing, 9, 959.
  59. Xiong, C., Shi, J., Cui, Y., Peng, B. (2017). Snowmelt Pattern Over High-Mountain Asia Detected From Active and Passive Microwave Remote Sensing. IEEE Geoscience and Remote Sensing Letters, 14, 1096-1100.
  60. McColl, K.A., Wang, W., Peng, B., Akbar, R., Short Gianotti, D.J., Lu, H., Pan, M., Entekhabi, D. (2017). Global characterization of surface soil moisture drydowns. Geophysical Research Letters, 44, 3682-3690.
  61. Cui, Y., Xiong, C., Lemmetyinen, J., Shi, J., Jiang, L., Peng, B., Li, H., Zhao, T., Ji, D., Hu, T. (2016). Estimating Snow Water Equivalent with Backscattering at X and Ku Band Based on Absorption Loss. Remote Sensing, 8, 505-522.
  62. Wang, S., Liu, S., Mo, X., Peng, B., Qiu, J., Li, M., Liu, C., Wang, Z., Bauer-Gottwein, P. (2015). Evaluation of Remotely Sensed Precipitation and its Performance for Streamflow Simulations in Basins of the Southeast Tibetan Plateau. Journal of Hydrometeorology, 16, 2577-2594.
  63. Li, D., Zhao, T., Shi, J., Bindlish, R., Jackson, T.J., Peng, B., An, M., Han, B. (2015). First Evaluation of Aquarius Soil Moisture Products Using In Situ Observations and GLDAS Model Simulations. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 8, 5511-5525.
  64. Peng, B., Shi, J., Ni-Meister, W., Zhao, T., Ji, D. (2014). Evaluation of TRMM Multi-satellite Precipitation Analysis (TMPA) Products and Their Potential Hydrological Application at an Arid and Semiarid Basin in China. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 7, 3915-3930.
  65. Peng, B., Tian, J., Tian, Q. (2012). Preliminary Simulation Study of Lake Water Color Monitoring Oriented Satellite Remote Sensing System: Based on Hyperion Scene. Journal of Remote Sensing Information, 27, 91-98. (Full paper in Chinese and abstract in English).
  66. Peng, B., Zhou, Y., Gao, P., Ju, W. (2011). Suitability Assessment of Different Interpolation Methods in the Gridding Process of Station Collected Air Temperature: a Case Study in Jiangsu Province, China. Journal of Geo-information Science, 13, 539-548. (Full paper in Chinese and abstract in English).

Community Engagement

  • Editorship

  • Grant Review Panelist

    • Panelist for NASA Soil Moisture Active-Passive (SMAP) Mission Science Team (2020)
    • Panelist for NASA Deep Space Climate Observatory (DSCOVR) Science Team (2021)
    • Proposal review for the Foundation for Food and Agriculture Research (FFAR) (2021)
  • Service to Disciplinary and Professional Societies or Associations

    • NASA Science Team: Carbon Monitoring System Science Team, 2017-present.
    • Judge for AGU Fall Meeting Outstanding Student Paper Award (OSPA), 2017-2019.
    • Founding President of IEEE GRSS Student Branch Chapter at University of Chinese Academy of Sciences, 2013-2015.
    • Vice President of IEEE Student Branch at University of Chinese Academy of Sciences, 2013-2014
  • Conference Session Organizer

    • Primary Convener and Session Chair of “Sustainable Agriculture and Climate Change: Monitoring and Modeling Soil Organic Carbon Dynamics and Greenhouse Gas Emissions of Agroecosystems”, AGU Fall Meeting in 2020 (2 online oral sessions, 1 online poster discussion session), 2021 (2 online oral sessions, and 1 online poster discussion session), 2022 (3 oral sessions, 1 poster session, and 1 online poster discussion session).
    • Primary Convener and Session Chair of “Carbon, Water, and Society: Adapting to Changes on Multiple Scales” (Oral and postal sessions), AGU Fall Meeting, 2019.
  • Journal Peer Reviewer (>100 manuscripts for over 35 domain leading journals. Publons Top Reviewers for Geoscience awardee)

    • Nature Communications (1/2019; 1/2020; 1/2022), Nature Food (2/2019, 1/2021), Global Change Biology (1/2019, 2/2020, 1/2021), Global Change Biology-Bioenergy (1/2020), Earth-Science Reviews (1/2019), Remote Sensing of Environment (2/2017, 7/2018, 8/2019, 3/2020, 3/2021, 3/2022), ISPRS Journal of Photogrammetry and Remote Sensing (1/2019), Remote Sensing (3/2017, 6/2018, 5/2019, 2/2020), IEEE Trans. on Geoscience and Remote Sensing (2/2020), Agricultural and Forest Meteorology (7/2018, 3/2019, 3/2020, 1/2021), Geophysical Research Letters (1/2017, 2/2019), Water Resource Research (1/2019, 1/2020, 1/2021), Journal of Hydrometeorology (1/2016, 2/2017), Journal of Climate (2/2020), Climate Dynamics (1/2021), Hydrology and Earth System Sciences (2/2018, 1/2020), Geoscientific Model Development (1/2019, 1/2020), Journal of Geophysical Research-Atmospheres (1/2017, 2/2018), Journal of Geophysical Research-Biogeoscience (5/2018, 2/2020, 1/2021), Environmental Research Letters (2/2018, 3/2020), Earth’s Future (1/2018, 1/2019, 2/2022), Environmental Modelling and Software (1/2018), Advances in Atmospheric Sciences (1/2018, 2/2020), Frontiers in Plant Science (1/2019), Frontiers in Big Data (1/2020), Monthly Weather Review (2/2015), Journal of Atmospheric and Oceanic Technology (1/2014), Hydrological Processes (1/2019, 1/2020), Remote Sensing Applications: Society and Environment (1/2017), Water (1/2018), Regional Studies (1/2019), Communications Earth and Environment (1/2020), One Earth (2/2020, 1/2021), Computers and Electronics in Agriculture (2/2021), Agronomy Journal (1/2022), Geomatics, Natural Hazards and Risk (1/2020).
  • Professional Membership

Teaching & Mentoring

  • Class Teaching

    • UIUC NRES 512: Ecosystem Biogeochemistry (Fall of 2022, Instructor for selected chapters)
    • UIUC NRES 598: Terrestrial Remote Sensing Applications (Spring of 2017, 2018, and 2019, Instructor for selected chapters and TA)
    • UIUC NRES 512: Biometeorology (Spring of 2022, Instructor for selected chapters)
    • UIUC NRES 499: Ecohydrology and Water Management (Fall of 2017, Instructor for selected chapters and TA)
  • Student Mentoring

    • Graduate interns: Nimisha Jasuja (Informatics, 2022)
    • Undergraduate interns: Bowen Song (2018, SPIN), Brain Yan (2019, SPIN), Junrui Ni (2019, SPIN), Yihong Jian (2021, SPIN), Chen Song (2021, SPIN), Isabelle Wagenvoord (2022, REU)

We are hiring

The Agroecosystem Sustainability Center (ASC) at Institute for Sustainability, Energy, and Environment (ISEE), University of Illinois at Urbana-Champaign (UIUC) has multiple opening positions for postdoctoral researchers and Ph.D. students working on modeling and remote sensing over the agroecosystems.

  • Area 1: Agroecosystem modeling. Expertise/interest in soil biogeochemistry, ecosystem modeling, and advanced data-model integration. We will recruit both postdoctoral researcher / Ph.D. student. Targeted ecosystem models in our group include: (1) ecosys, an advanced ecosystem model with full representation of soil C-N-P cycles; and (2) CLM, the land component of U.S. flagship earth system model CESM.

  • Area 2: Water Quality and Hydrological Modeling. Expertise/interest in watershed hydrology, hydrodynamics, groundwater, flow in porous medium and mathematics. We will recruit both postdoctoral researcher / Ph.D. student.

  • Area 3: IoT and Vehicle Sensing of Agroecosystem. Expertise/interest in remote sensing, electronics, field work, and computer vision. We will recruit both postdoctoral researcher / Ph.D. student.

Candidates with strong backgrounds in programming, process-based modeling and remote sensing would be highly preferred. Please send a cover letter, CV, and contact information of three references via email to Dr. Xiang Zhu (

UIUC ranks top worldwide in Agricultural Science, Computer Science & Engineering, and Environmental Science. The University of Illinois administration, faculty, and staff embrace diversity and are committed to attracting qualified candidates who also embrace and value diversity and inclusivity. International students have the flexibility to study remotely considering the COVID-19 situation.