// From the Lab
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NDSU hosted a two-day Polytec-led training on its new PSV QTec 3D Scanning Vibrometer, acquired through an NSF-MRI award (No. 2510004) led by Dr. Eshkabilov. Faculty and students from six departments covered 1D/3D measurement, modal analysis and MEMS — highlighted by a live 3D vibration measurement of an observation honey bee colony with high-speed video.
Our paper "Site-specific mechanical weeding robot with automatic self-adjustable individually controlled cultivator" (Istiak, Talami, Kim, Eshkabilov) is now published open access in Springer's Precision Agriculture journal.
Lab students — Mohammad Aftabi Talami, Shoaib Ahmmad, Shafi Istiak, Farhin Neha, Bakht Alam Khan, Mahmud Alam Pranto, Brady Lindsey and Jewel Woodcock — presented their research and development results at the Big Iron Show, Autonomous Nation Conference 2026, and the 3rd CEA Conference at NDSU.
Graduate students Mahmud Alam Pranto, Farhin Faiza Neha and Shafi Md. Istiak presented key findings on lettuce growth dynamics and monitoring using true-color and spectral imaging, and an Edge AI-enabled smart sensing system for hydroponic lettuce.
A team led by Dr. Frank Casey — with Aaron Reinholz, Dr. Eshkabilov and Md. Ibne Joha — presented collaborative precision-agriculture R&D at John Deere TechCon, built connections with Deere R&D groups, and exhibited NDSU research and academic programs.
Dr. Eshkabilov met Dr. Stavros Vougioukas and Dr. Shamim Ahamed of UC Davis Biological and Agricultural Engineering to discuss robotics in agriculture and apiculture, phenotyping and fertilizers for specialty crops grown in CEA, and potential collaborative research.
During a visit to USDA-ARS in Salinas, Dr. Eshkabilov and host Dr. Ivan Simko discussed the current USDA-AMS project, lettuce phenotyping and genetics research, and future research collaborations.
The AgriMechatronics team brought its site-specific mechanical weeding robot to Autonomous Nation 2026 at Grand Farm, demonstrating targeted tillage to growers, engineers, and industry partners and connecting with the wider autonomous-agriculture community.
Lab members drove the field UGV down the NDSU Homecoming (Bison) parade route alongside full-size tractors, then hosted an open-house demo where families and alumni explored the robot's controls and live telemetry.
Dr. Eshkabilov visited outstanding researchers and graduate assistants at Cornell University in the U.S. and at Nanzan University, University of Tsukuba, and Nagoya University in Japan. At Cornell he met Prof. Neil Mattson, Dr. Lirong Xiang, Prof. Sunny Jung, and Prof. Bryan Danforth, with further discussions at Cornell AgriTech in Geneva. The trip opened new collaborations across controlled environment agriculture, robotics, automation, precision agriculture, and apiculture. He also presented a paper on robot navigation and control modeling and chaired a session at ICRAS 2026 in Kyoto.
Three NDSU professors — Drs. Xinhua Jia, Paulo Flores, and Sulaymon Eshkabilov — visited CANON Virginia Inc. in Newport News, VA to establish a research collaboration with its R&D Group. CANON Virginia specializes in product design & development, testing & certification, precision model making, plastic injection molding, and custom manufacturing. The team toured six laboratories, including Materials & Material Processing, Spectroscopy, Imaging Technology, and the Controlled Environment Agriculture Imaging Technology Lab, holding discussions with CANON researchers and engineers.
Researchers and leaders from North Dakota State University — including Sulaymon Eshkabilov, Heidi Grunwald, Alexey Leontyev, and Trung Le — joined peers from across the country at the 2026 NSF EPSCoR Annual Summit in New Orleans, Louisiana. Hosted by the American Association for the Advancement of Science, the summit brought together researchers, educators, and jurisdiction leaders to discuss collaboration, professional development, NSF engagement, and networking, and to explore ways to strengthen STEM research and education.
The NDSU Farm Robotics Challenge student team was selected as one of the Top Five Finalists in the International Farm Robotics Challenge with their custom-built SoilXplorer Robot — GPS-guided mechanical soil sampling for lab-ready analysis. Go Bison! The team thanks its members for their hard work and dedication, and extends special thanks to industry partner Mr. Michael Anderson and farmer collaborator Mrs. Noreen Thomas for their invaluable support and practical insights.
Part of our research group participated in the 5th Interdisciplinary Conference on Electronics and Computer (INTCEC), held September 15–16, 2025 in Chicago, IL. The team delivered four papers and one keynote speech, sharing latest developments on honey bee monitoring, sugar-beet decomposition sensing, and site-specific weed control technologies.
Spanning three colleges and eight university departments, NDSU secured a $625,244 NSF Major Research Instrumentation (MRI) award (No. 2510004) to acquire a PSV QTEC 3D Laser Scanning Vibrometer. Led by Dr. Sulaymon Eshkabilov, this tool captures true 3D non-contact vibratory signals — measuring frequencies non-invasively so the team can analyze structural and biological movements, such as determining whether a honey bee hive is calm or under stress. The award was recognized in a letter from the office of Congresswoman Julie Fedorchak.
Dr. Sulaymon Eshkabilov, Assistant Professor of Agricultural and Biosystems Engineering, has earned the highly selective National Science Foundation (NSF) Faculty Early Career Development Program award. This grant supports his pioneering study on modeling and predicting how honey bees respond to environmental fluctuations. By deploying wireless sensor network systems equipped with Edge AI capabilities, the project aims to non-invasively decode natural hive signals to protect pollinator health and global ecosystems.
Launched in September 2024, this project focuses on automating drip irrigation systems for lettuce production by leveraging advanced soil sensors and machine learning algorithms. The project aims to accurately quantify water and nutrient balances to maximize environmental conservation while maintaining optimal plant health. Additionally, the team is designing innovative greenhouse solar modules to maximize solar radiation and generate clean farm electricity.
Initiated in August 2024, this proposal aims to apply machine learning algorithms to develop robust classification, estimation, and prediction models for lettuce crops. Key objectives include developing mathematical models to assess plant nutritional and water status from spectral data, alongside evaluating the challenges and sustainable opportunities of utilizing egg-washing wastewater as a natural fertilizer and irrigation source.
This multi-year collaborative initiative brings together personnel from the USDA and NDSU to develop novel, field-ready "DC-to-Light" electromagnetic sensors. By fusing these advanced hardware platforms with specialized Edge AI machine learning theory and secure Information Technology (IT) platforms, the project delivers real-time, data-driven local decisions directly to growers in the field.
Established in May 2024, this project implements a comprehensive methodology to assess the cultural, social, legal, and economic implications of introducing clean energy tractors to the farming industry. By actively engaging all potential stakeholders—including agricultural producers, engineers, educators, policymakers, and consumers—the strategy aims to smooth the market adoption and structural transition to eco-friendly fleet machinery.
Kicking off in March 2024, this precision agriculture project combats weed control by dramatically reducing chemical herbicide usage. An interdisciplinary team of weed scientists, autonomous vehicle engineers, and AI engineers is designing a cooperative Unmanned Ground Vehicle (UGV) system. Using onboard computer vision systems powered by Edge-AI technology, the vehicle precisely identifies and target-sprays weeds locally, maximizing environmental friendliness across North Dakota farming operations.
