Prasad joined the DART group as a Postdoctoral Fellow in February 2025. His research interests span agro-hydrology and hydro-meteorology. During his PhD in Civil Engineering at the Indian Institute of Technology Kanpur, he developed real-time fog prediction methods using uncertainty-aware Bayesian Neural Networks (https://fog.iitk.ac.in). Prasad is passionate about leveraging advancements in data science to tackle critical challenges in environmental modeling, with focus on remote sensing and citizen-science methods. His cocurricular activities include volunteering for scientific events and attending guest lectures.

Wri has recently joined DART after completing his Ph.D. at Presidency University, India and brings a strong background in precision weed management using remote sensing technologies. He will now be working on multidisciplinary research projects in our team with emphasis on integrating AI and multispectral technologies in understanding weed management in spatial and temporal scales to reduce the herbicide resistance. Wri is a wanderlust who also has a fascination for shooting (photography and rifle). When Wri is not researching, he likes walking, travelling to new places, trailing amidst nature, and collecting magnets. Check his website! https://wridutta.wixsite.com/environment-research

Dr. Kim’s is a recently minted doctorate from Kangwon National University in South Korea with his expertise on Alfalfa (Medicago Sativa L.) yield prediction and water stress. At DART, Jiyung diligently assesses factors using machine learning models, particularly those related to water, that impact alfalfa yield in Southern Great Plains . With expertise in constructing alfalfa yield predictions using statistical models, Jiyung has conducted extensive research on various production and management variables, including cultivar selection, harvest methods, and fertilizer application. As a dedicated researcher, Jiyung Kim contributes valuable insights to the realm of precision agriculture and its applications in optimizing alfalfa production for the region.

Farshina is currently pursuing her Ph.D. in Electrical Engineering and her research focuses on the application of Machine Learning for resource optimization. Her recent work addresses the critical issue of irrigation water optimization in drought-prone regions like states of Montana, California and Kansas, employing innovative statistical and machine-learning techniques. Farshina’s solutions effectively bridge gaps in data frequency challenges, providing informed irrigation decisions for farmers. During her master’s program from 2018-2020, her focus was on automated power management in smart grids, emphasizing the enhancement of microgrid resiliency to prevent blackouts. Beyond her academic pursuits, Farshina actively engages in community services, advocating for underprivileged groups. Driven by a passion for solving complex problems, she aspires to make a meaningful societal impact through her ongoing research endeavors.

Sindhu is researching early water and nutrient stress detection through the application of Hyperspectral Imaging techniques for row crops. Her previous expertise at Texas A&M AgriLife Corpus Christi is in multi-temporal canopy features of cotton using diverse regression models. Sindhu recently earned her master’s degree from Texas A&M University Kingsville and is driven by a passion for advancing her knowledge in Precision Agriculture to contribute to sustainable and efficient farming practices. Outside research, Sindhu could be found watching anime or being creative with her culinary skills.

Sourajit Dey, is originally from West Bengal, India, and is currently pursuing his Ph.D. at Kansas State University as a Graduate Research Assistant. With a focus on forage agronomy, he aims to enhance drought resilience in alfalfa, and his project is funded by USDA to monitor impacts of drought on forage production in Southern Great Plains. Dey holds a M.S. degree from Bidhan Chandra Krishi Viswavidyalaya, India. He excels in statistical programming and is enthusiastic about exploring coding for agriculture datasets. Beyond academia, he enjoys travel, music, and guitar, embracing exploration and creativity.

Nishadini is originally from Sri Lanka and earned her Bachelor’s degree in Agricultural Technology and Management in 2019, followed by a Master’s degree in Agricultural and Biosystems Engineering in 2022, both from the University of Peradeniya, Sri Lanka. Additionally, she completed her second Master’s degree in Agronomy at K-State in December 2023. She is excited to work as a PhD student with Dr. Gaurav Jha on the soil microbial innovations project funded by National Science Foundation (https://www.k-state.edu/micra/). In her free time, she enjoys traveling to appreciate nature, as well as indulging in her passion for cooking and baking.

Udit Debangshi, is a Graduate Research Assistant pursuing his M.S. at Kansas State University, focusing on understanding how different climates and soil types affect crop management and yield predictions in various agricultural regions. He has a B.S. in Agriculture from Visva-Bharati University in India. He is passionate about crops and soils and draws inspiration from Rabindranath Tagore (a renowned Indian philosopher and poet, particularly his ideas about education). He has authored and co-authored scientific articles on topics related precision farming technologies, Additionally, he has initiated a group called ‘The Indian Society of Sustainability’. He aspires to make a positive impact in agriculture, guided by Tagore’s words: “The roots below the earth claim no rewards for making the branches fruitful.”

Akshay Kumar Kona, originally from Hyderabad, India, is a Master’s student in Data Analytics at Kansas State University. He holds a Bachelor’s degree in Artificial Intelligence & Machine Learning (AIML). Previously, he worked as an AI Engineer, developing AI-driven automation, product recommendation systems, and optimizing prompts with LangChain, Retrieval-Augmented Generation (RAG), and Prompt Engineering. As a Data Scientist Intern, he developed GenAI-powered chatbots and fine-tuned speech recognition models. In his role as a Web Developer Intern, he designed front-end interfaces and integrated backend services to streamline data processing. With expertise in Generative AI (GenAI), Natural Language Processing (NLP), Machine Learning (ML), and cloud-based automation, he is passionate about leveraging AI to drive innovation and solve real-world challenges across industries.

Douglas is an undergraduate student at Kansas State majoring in Agronomy with a specialty in Precision Agriculture and minoring in Animal Science. He has industry experience with agronomic use of UAVs, artificial intelligence, and crop yield prediction models. Additionally, he has experience in production of major row crops from his family farm. Douglas assists in data acquisition, processing, and analysis for various projects of the DART lab.

Lawrence is an undergraduate student at Kansas State University, majoring in Agricultural Technology Management with a focus on Precision Agriculture, and minoring in Agronomy. He has hands-on experience from an internship at an agricultural cooperative, where he learned about the agriculture industry firsthand. Lawrence is interested in using precision farming technology and agronomy techniques to boost crop yields and improve farming practices. Outside of his studies, he enjoys being a part of the K-State Marching Band, playing different instruments, and listening to all kinds of music.