Licheng Liu
Environmental Science · Purdue University West Lafayette
Publications
119
Citations
4,448
Est. group size
~1
Recurring co-author estimate
Active years
45
Publishing since 1982
Licheng Liu's work focuses on tracking and predicting greenhouse gas emissions—especially methane and nitrous oxide—from wetlands, soils, and agricultural land, often by combining computer simulation models with machine learning ('knowledge-guided machine learning'). This research aims to better understand how carbon and nitrogen cycle through ecosystems and how these processes are changing over time and across the globe.
Publication output has grown substantially over the last decade, rising from a few papers per year in 2017 to a sustained pace of roughly 13-16 papers per year in recent years.
Generated by claude-sonnet-5 from public bibliographic data · Jul 20, 2026
- Knowledge‐Guided Machine Learning for Global Change Ecology Research
Global Change Biology · 2026
- Photothermal CO <sub>2</sub> Reduction to CO with Ultrahigh Selectivity Enhanced by Au–O–Ce Bond in Au–CeO <sub>2</sub>
Energy Material Advances · 2026
- Global compilation of soil methane uptake measurements from 1984 to 2018
DOE Lawrence Berkeley National Laboratory (LBNL) Repository · 2026
- Retraction notice to “Knowledge-guided machine learning captures key mechanistic pathways for better predicting spatio-temporal patterns of growing season N2O emissions in the U.S. Midwest” [Agricultural and Forest Meteorology 373 (2025) 110750]
Agricultural and Forest Meteorology · 2026
- Design and Test of a Lower-Cost Water-Quality Sensor for Nitrate
ACS ES&T Water · 2026
- AgroFlux: A Spatial-Temporal Benchmark for Carbon and Nitrogen Flux Prediction in Agricultural Ecosystems
Open MIND · 2026
- AgroFlux: A Spatial-Temporal Benchmark for Carbon and Nitrogen Flux Prediction in Agricultural Ecosystems
arXiv (Cornell University) · 2026
- Dual-functional basic microenvironment in Sr-doped La2CuO4 for selective CO2 electroreduction to CH4 via cooperatively promoting CO2 adsorption and H2O dissociation
Journal of Rare Earths · 2026
- Multi‐Decadal Dynamics of Wetland Methane Emissions Revealed by Knowledge‐Guided Machine Learning
Global Change Biology · 2026
- Integrating machine learning with a process-based model for estimating global wetland methane emissions
2026
- CHAM-net: A Contrastive Hierarchical Adaptive Meta-network for Robust Global Methane Flux Prediction
arXiv (Cornell University) · 2026
- CHAM-net: A Contrastive Hierarchical Adaptive Meta-network for Robust Global Methane Flux Prediction
arXiv (Cornell University) · 2026
- Isotopic constraints in methane inversions reveal larger trends in wetland emissions with improved linkage to terrestrial water storage
Nature Communications · 2026
- Revising the Magnitude and Trends of the Global Methane Soil Sink With Process‐Based, Machine‐Learning, and Atmospheric Inversion Modeling Approaches
Journal of Geophysical Research Biogeosciences · 2026
- DAUNet: A deformable aggregation UNet for multi-organ 3D medical image segmentation
Pattern Recognition Letters · 2025
- arXiv (Cornell University)×7
- Agricultural and Forest Meteorology×5
- Journal of Geophysical Research Biogeosciences×4
- Zenodo (CERN European Organization for Nuclear Research)×4
- SSRN Electronic Journal×4
- Qianlai Zhuang
Environmental Science · Purdue University West Lafayette
- Patrick Crill
Environmental Science · The Ohio State University
- Brian H. Stirm
Environmental Science · Purdue University West Lafayette
- Kristian D. Hajny
Environmental Science · Purdue University West Lafayette
- Robert Kaeser
Environmental Science · Purdue University West Lafayette
This profile was generated automatically from public scholarly data (OpenAlex). Group size and activity levels are estimates derived from co-authorship patterns.
Last updated Jul 20, 2026.
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