People

abe Dr. Sushant Mehan
 I work at water resources engineering and hydro-informatics interface. My research agenda includes advancing the understanding and physical representation of nutrients' fate and transport to manage water resources using the computing infrastructure. I am also interested in exploring how interactions between climate and land management operations impact water quantity and quality. My passion for working on water resources, precisely water quality, is driven by the idea that resolving water problems can solve much unseen unpredicted chaos in the ecosystem. I love to work as a problem solver on issues related to water sustainability.

Graduate Students and Postdocs

abe ABE Graduate Student 1
I am a Graduate Research Assistant at South Dakota State University (SDSU), where I am pursuing my Ph.D. in the Department of Agricultural and Biosystem Engineering with a specialization in hydrological modeling under the mentorship of Dr. Sushant Mehan. My academic journey began before my time at SDSU, as I completed my Bachelor of Engineering (BE) and Master of Science (MS) degrees at the Institute of Engineering in Nepal. Currently, my research encompasses a diverse range of topics, including remote sensing, Machine Learning, evapotranspiration (ET), soil moisture, and hydrological modeling. These areas of study are of utmost importance as they play a pivotal role in shaping the future of agriculture and water resource management. My research extends geographically to the states of Colorado and South Dakota. The primary focus is on generating innovative ideas to improve the accuracy and spatiotemporal resolution of ET and soil moisture data and effectively integrating them into hydrological modeling. This work holds significant promise for facilitating agricultural water management and expediting decision-making processes in this critical domain.
abe ABE Graduate Student 2
Kayode Adebayo is a Ph.D. student/a Graduate Research Assistant in the HydroSolve Lab. He holds a background in Mechanical Engineering from the University of Hull, where he conducted his thesis on "Utilization of Artificial Intelligence Approaches for Online Control Systems Tuning". His academic journey has equipped him with a strong foundation in engineering principles, data science, and artificial intelligence skills, all of which play a crucial role in his current research. In his present research work, Kayode focuses on water footprints, seamlessly combining his engineering knowledge with data-driven insights to address critical water resources challenges. Kayode envisions the successful completion of his Ph.D. and a continued journey of making meaningful contributions to the fields of agricultural engineering and hydrology.
abe ABE Undergraduate Research Student
Kyle is an organized and proactive individual currently pursuing a double major in mathematics and data science at South Dakota State University. He enjoys working with data but is still deciding in which area to specialize. As Spike Club President, he actively engages with campus personnel to facilitate event logistics, reserve practice times, and promote spikeball tournaments. Additionally, he serves as the Treasurer for the Data Science Club, regularly participates in Ultimate Club activities, and continually develops his musical technique on the Alto Saxophone by playing in Jazz 1. His current favorite fantasy author is Brandon Sanderson.
abe ABE Graduate Student 3
Tulsi graduated as an Agricultural Engineer from the Institute of Engineering, Purwanchal Campus, Tribhuvan University, Nepal, in 2021. He served as an assistant lecturer with the Civil Engineering Department at Himalaya College of Engineering from 2021 (December) to 2024 (July), where he was responsible for teaching various subjects related to water resources engineering. He also served as a part-time lecturer at the Cosmos College of Management and Technology in the Civil Engineering Department in 2023. His research is focused on understanding and employing hydrology and water quality models to predict and assess water quality, utilizing machine learning techniques to analyze vast soil and water dynamics datasets, and implementing precision agriculture and sustainable water resource management techniques.