Debjani Sihi
Bio
Debjani Sihi joined the College of Agriculture and Life Sciences AI cluster in the fall of 2024. She has joint appointment with the Department of Plant and Microbial Biology and the Department of Crop and Soil Sciences. Prior to joining NC State, she was a faculty member at Emory University. Her doctoral research was completed at the University of Florida, and she held postdoctoral appointments at the University of Maryland Center for Environmental Sciences (Appalachian Laboratory) and Oak Ridge National Laboratory.
Her research program focuses on the plant-soil-microbe-atmosphere continuum. Sihi is a biogeochemist by training, and her work involves integrating field and laboratory data with machine learning (AI) and process-based (mechanistic) models. Her specialization lies in soil (and ecosystem) carbon (and nutrient) cycle processes and greenhouse gas emissions from managed (agricultural) and natural (forest, wetland, grassland) ecosystems. As part of the N.C. Plant Sciences Initiative, she is interested in building an interdisciplinary program that leverages cutting-edge technologies (e.g., sensors, imaging, molecular technologies) to address grand challenges of our era (climate change, food security, and environmental sustainability) using multi-scale modeling and big data analytics approaches. Research projects in Sihi Lab are funded by federal agencies (USDA, NSF, DOE) and industry (Valent Biosciences) partners.
Publications
- Barley, corn, and wheat residue decomposition as affected by tillage and nitrogen rate in semi‐arid conditions , (2025)
- Decoding the hidden mechanisms of soil carbon cycling in response to climate change in a substrate-limited forested ecosystem , BIOGEOCHEMISTRY (2025)
- Management alternatives for climate‐smart agriculture at two long‐term agricultural research sites in the United States: A model ensemble case study , Agronomy Journal (2025)
- Regenerative agriculture's effects on soils and greenhouse gas emissions , Reference Module in Food Science (2025)
- Using probability distribution function as a scaling approach to incorporate soil heterogeneity into biogeochemical models for greenhouse gas predictions (Final Technical Report) , (2025)
- A New Coupled Biogeochemical Modeling Approach Provides Accurate Predictions of Methane and Carbon Dioxide Fluxes Across Diverse Tidal Wetlands , JOURNAL OF GEOPHYSICAL RESEARCH-BIOGEOSCIENCES (2024)
- Biochar applications and enzyme activity, carbon dioxide emission, and carbon sequestration in a calcareous soil , Journal of Plant Nutrition (2024)
- Reconciling Top-Down and Bottom-Up Estimates of Ecosystem Respiration in a Mature Eucalypt Forest , JOURNAL OF GEOPHYSICAL RESEARCH-BIOGEOSCIENCES (2024)
- Upscaling Soil Organic Carbon Measurements at the Continental Scale Using Multivariate Clustering Analysis and Machine Learning , Journal of Geophysical Research: Biogeosciences (2024)
- A Continental‐Scale Estimate of Soil Organic Carbon Change at NEON Sites and Their Environmental and Edaphic Controls , Journal of Geophysical Research: Biogeosciences (2023)