Graduate Research Assistants

Name: Anish K C
Degree Seeking: M.S in Environmental Science concentration in Natural Resources.
Advisor: Dr. Bharat Pokharel
Project Title: Predictive Model Mapping of Aboveground Biomass of Mixed-Hardwood Forests using Multisource Remotely Sensed Data.

Project Description:
This thesis research project aims to improve forest aboveground biomass (AGB) estimation by integrating LiDAR,  Sentinel, and NAIP remote sensing data. It addresses the limitations of single-sensor approaches, such as signal saturation and species variation, by combining LiDAR’s structural metrics with Sentinel’s spectral and NAIP’s texture information. Focusing on the Land Between the Lakes Recreation Area, the study conducts a systematic review of LiDAR-based biomass modeling, develops and integrates multisensor models, and compares traditional regression with machine learning techniques. The goal is to identify the most accurate and efficient method for large-scale forest biomass mapping and carbon assessment.

Name: Abishek Gupta
Degree Seeking: M.S in Environmental Science concentration in Natural Resources.
Advisor: Dr. Behnaz Molaei
Project Title: Machine Learning Based Hot and Cold Anchor Pixel Prediction for Improving Satellite-Based METRIC Development and Validation in Humid Climates of Tennessee

Project Description:
This thesis research aims to improve evapotranspiration (ET) estimation in humid climates by enhancing the METRIC (Mapping EvapoTranspiration at high Resolution with Internalized Calibration) energy balance model through machine learning. METRIC relies on manually selecting hot and cold anchor pixels representing extreme ET conditions, a process that is subjective, time-intensive, and prone to error, particularly challenging in Tennessee's humid, vegetated landscape where identifying appropriate pixels is difficult.
This study addresses these limitations by developing machine learning models to automate anchor pixel selection using Landsat and Sentinel satellite imagery. The research involves processing multispectral satellite data through Google Earth Engine to extract vegetation indices, land surface temperature, and surface energy balance parameters. Ground-truth validation is conducted using meteorological station data and soil moisture measurements across Tennessee study sites.
By integrating remote sensing data with machine learning algorithms, this work seeks to reduce subjectivity in METRIC calibration, improve ET estimation accuracy in humid regions, and enable more efficient large-scale water resource monitoring. The automated approach has potential applications in agricultural water management, drought monitoring, and hydrological modeling across similar humid climates where traditional METRIC implementation faces challenges.

Name: Bikalpa Lamichhane
Degree Seeking: M.S in Environmental Science concentration in Natural Resources.
Advisor: Dr. Behnaz Molaei
Project Title: Improving the Accuracy of UAS-Based Crop Evapotranspiration Estimation for Different Climates

Project Description:
This thesis aims to achieve enhanced accuracy in estimating crop evapotranspiration (ET) using Unmanned Aerial Systems (UAS) across diverse climatic conditions by integrating high-resolution multispectral and thermal imagery with advanced machine learning algorithms. Current ET estimation methods often lack the spatial resolution and adaptability needed for precision agriculture in varying environments. The research develops climate-adaptive predictive models trained on ground-truth measurements from eddy covariance systems and lysimeters across multiple climate zones—ranging from arid to humid regions while accounting for climate-specific variables including temperature regimes, humidity levels, solar radiation, and wind patterns. By evaluating model performance under different crop types, growth stages, and environmental conditions, this study identifies optimal sensor configurations and flight parameters for each climatic scenario. The outcomes address limitations of one-size-fits-all approaches and provide stakeholders with reliable, scalable tools for precision irrigation scheduling and sustainable water resource management, ultimately bridging remote sensing technology with practical agricultural applications to enhance water use efficiency in water-limited regions facing climate variability.

Name: Maheen Mehnaz
Degree Seeking: M.S. in Environmental Science
Advisor: Dr. Sudipta Rakshit
Project Title: Macroscopic and in-situ ATR-FTIR Spectroscopic Studies of Metformin Adsorption on Soil

Project Description:
Emerging contaminants might pose serious threats to the soil and water environment. Metformin, an emerging micropollutant, is one of the most widely used drugs for type-2 diabetes treatment. However, its waste disposal through human excretion is causing environmental concern to the soil and water environment. Yet, knowledge about the interaction mechanism of metformin with soil remains very limited. In this study, we evaluated metformin adsorption mechanisms on model oxide minerals (gibbsite, hematite) and two Tennessee soils (Milan Loring soil and Cheatham County soil) and in the presence of soil micronutrient (molybdenum) using in situ attenuated total reflectance Fourier transform infrared (ATR-FTIR) spectroscopy and macroscopic adsorption experiments under environmentally relevant solution properties.

Name: Donna Blankenship
Degree Seeking: M.S. in Environmental Science
Advisor: Dr. Sudipta Rakshit
Project Title: Evaluating Tennessee Soil as a Sink for PFOS and PFOA-The Implications for Soil Health

Project Description:
TThis thesis investigates the sorption and retention behavior of PFAS in soils to assess their function as environmental sinks. This research examines the influence of soil mineralogy, pH, and redox-sensitive components on PFAS binding and evaluates implications for soil health and contaminant mobility.

Name: Monika Gaire
Degree Seeking: M.S. in Environmental Science
Advisor: Dr. Jianwei Li
Project Title: Temperature Rise Impact on Patterns and Drivers of Soil Respiration in Switchgrass Croplands

Project Description:
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Name: Himani Singh Gautam
Degree Seeking: M.S in Environmental Science
Advisor: Dr. Huseyin Tecimen
Project Title: Effect of soil tretaments on rhizospheric microbial community, soil nutrient dynamics and plant nutritional status for selected forest farming species.

Project Description:
This research investigates the effects of applying different types of biofertilizers on the rhizospheric microbial community and examines how these microbial responses influence soil nutrient status. Furthermore, the study evaluates the subsequent impacts on the growth and development of forest farming species such as black cohosh, ginseng, goldenseal, and ramps.

Name: Xiaoyue Li
Degree Seeking: Ph.D. in Agricultural Science 
Advisor: Dr. Yujuan Chen
Project Title: Quantifying the Ecosystem Services of Urban Forests in the Southeastern United States

Project Description:
Urban forests provide critical ecosystem services that enhance environmental quality, human well-being, and climate resilience, particularly in rapidly urbanizing regions. The project integrates field-based measurements of air temperature, relative humidity, and heat index with spatial analysis of tree canopy structure and land cover characteristics. Measurements are conducted across multiple urban environments, such as parking lots and green spaces, to capture ecosystem service variation at both site and tree-proximity scales. By combining in-situ observations with geospatial and statistical analyses, the study assesses how tree canopy cover, spatial configuration, and proximity influence the magnitude of ecosystem services provided by urban forests.

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Name: Diptesh Banerjee
Degree Seeking: Ph.D. in Agricultural Science 
Advisor: Dr. Sudipta Rakshit
Project Title: Nucleic acid based organic phosphorus cycling

Project Description:
Adsorption mechanism of nucleotides on soil in presence of redox materials.