Machine vision is reshaping modern agriculture by integrating imaging, sensing, and automation to improve how crops are monitored and managed. This panel, Agriculture Machine Vision Applications in Farm Automation and Precision Agriculture, will explore how imaging and artificial intelligence technologies are being used for crop and weed detection, disease monitoring, yield estimation, precision spraying, and robotic harvesting. Panelists from research and industry will discuss challenges in scaling these technologies, including field variability, changing environmental conditions, and hardware integration. The session will also highlight advances in spectral imaging and AI that are enabling more precise, data-driven farm operations. By connecting perspectives from robotics, agronomy, and imaging science, this discussion aims to provide practical insights into how machine vision and automation are driving the next generation of sustainable and efficient farming systems.

Moderator

Fartash Vasefi Chief Technology Officer SafetySpect, Inc. (United States)

Dr. Fartash Vasefi is the Co-founder and CTO of SafetySpect and a biophotonic scientist with 20+ years of experience in multimode spectroscopy and medical imaging. He has served as technical lead and principal investigator on $30M+ in federally funded programs across the U.S. Army, ARPA-H, USDA, NOAA, NIH, EPA, and NASA. His expertise spans optical hardware design, AI-driven analytics, and translational product development—capabilities that underpin SafetySpect’s platform and its expansion into food safety, medical diagnostics, and defense. Dr. Vasefi’s experience covers the full stack from foundational electrical/optical engineering through clinical validation and commercialization. He has authored 100+ peer-reviewed publications (cited 2000+ times) and is focused on turning innovative optical imaging, spectroscopy, and algorithms into commercially adoptable, regulatory-ready systems.

Panelists

Diganta D. Adhikari Global Head of On-farm IoT & Agronomic Data Platforms Syngenta Group (United States)

Diganta Adhikari is the Global Head of On-farm IoT & Agronomic Data Platforms at Syngenta Group-Computational Agronomy. He leads the integration of IoT-based sensors and agronomic data sources, building platforms that enable advanced analytics and AI-driven solutions in agriculture. With the rapid evolution of AI and large language models, Adhikari underscores the critical role of high-quality, well-structured data in delivering effective and precise outcomes. As Head of Agronomic Data Platforms, he ensures all data assets are FAIR, rigorously quality-controlled, and enriched with appropriate metadata to maximize their value for AI applications.

Adhikari’s career spans over 25 years in IoT, sensor development, and data-driven agronomy, including roles at Irrometer Co Inc. and the Center for Irrigation Technology at Fresno State. He is an active member of organizations such as ASABE, AgGateway, and the American Society of Agronomy, ISO/TC, IoT4Ag and serves on several standards committees focused on data standards, irrigation, IoT and precision agriculture. Throughout his career, Adhikari has demonstrated a deep commitment to advancing IoT and data platforms that optimize water efficiency, productivity, and sustainability—driving the digital transformation of agriculture through data and AI. He is recognized for his ability to shape long-term technology vision, lead enterprise innovation, and partner with executive teams to maximize technology’s strategic and operational impact.

Sambandh Bhusan Dhal Post-Doctoral Associate, Department of Analytical Chemistry and Characterization, Directorate of Energy, Environment, Science and Technology Idaho National Laboratory (United States)

Dr. Sambandh Bhusan Dhal is a Postdoctoral Associate at Idaho National Laboratory (INL) specializing in uncertainty-aware machine learning for data-scarce sensing at the intersection of AI, hyperspectral imaging, and sustainable material systems. His work applies semi-supervised, transfer, and deep learning to precision agriculture, bioenergy, e-waste classification, and circular-economy problems. He earned his Ph.D. (2024) and M.S. (2019) in Electrical and Computer Engineering from Texas A&M University, where his research spanned data-driven modeling for sparse agricultural systems, IoT-enabled decision support for soilless cultivation, UAV hyperspectral plant-disease detection, and statistical resource optimization under limited data.

Patrick De Guelle Sales Manager US – South / East Konica Minolta Sensing Americas, Inc. (Specim) (United States)

Patrick De Guelle is Sales Manager for the US – South and East with Konica Minolta Sensing Americas, Inc., where he is responsible for Specim hyperspectral imaging solutions. With more than 20 years of experience in technical and industrial markets, he focuses on connecting advanced imaging technologies with real-world challenges in agriculture, food safety, recycling, and process monitoring.

With a master’s degree in molecular biology, he brings a perspective that spans from microscopy to remote sensing—linking micro-scale observations to macro-scale applications. Drawing on this background, he is passionate about advancing the adoption of imaging technologies and supporting organizations in applying them to improve efficiency, accuracy, and sustainability.

He sees artificial intelligence and machine learning as essential tools for maximizing value of hyperspectral data in agriculture enabling faster, more precise and scalable solutions for growers, producers, and researchers. At KMSA, he collaborates closely with engineers, researchers, and industry leaders to advance the adoption of hyperspectral imaging.

Nathan Dorn Director Agricultural Industry Relations F3 Innovate (United States)

Nathan Dorn is Director of Industry Relations at F3 Innovate, where he helps accelerate the adoption of agricultural technologies through education, competition, training, funding, and partnerships between farmers and technologists. In this role, he contributes to advancing the $30 billion agricultural economy of California’s Central Valley, supporting the people who provide America’s fruits, vegetables, wines, nuts, fiber, dairy, and beef. Previously, Nathan served as Business Development Lead at Farm-ng, taking the company from zero to 200 robotic systems in market during its first two years, and as CEO of Food Origins, a data science and capture startup in specialty crops. Earlier roles include Director of Knowledge and Innovation at Reiter Berry Farms, Technical Manager for Gallo Coastal Vineyards and Wineries, engineering positions at Pepsi Cola Bottling and Etamic Movomatic, and five years of service in the U.S. Navy as a Nuclear Machinist Mate aboard the USS Omaha (SSN 692). Raised on a Nebraska farm, he also spent his early years as a custom wheat harvest crewmember. He is active in the agtech community through IoT4Ag, ASABE, the Monterey County Farm Bureau, and California Ag Leadership, and has represented U.S. agriculture in delegations to the Netherlands, Japan, and Argentina. Nathan has also spoken at leading forums including the World Ag Expo, EcoFarm, the Forbes AgTech Summit, RoboUniverse, and the Unified Winegrape Symposium.

Chris Padwick Director of Computer Vision Machine Learning Blue River Technology (United States)

Chris Padwick joined Blue River Technology in 2016 as the first machine learning engineer for the See and Spray product. He led the machine learning team to develop See and Spray which was released to customers in 2022.  This year over 5 million acres have been treated using See and Spray, resulting in herbicide savings of 50% and over 32M gallons of herbicide tank mix not sprayed. Chris has received numerous awards and 13 patents related to the See and Spray product. Before Blue River, he worked in the remote sensing industry for 12 years at Maxar, MDA, and ITT VIS, holding various roles. Chris has an M.Sc. degree in Physics and Astronomy from the University of British Columbia.

Mitchell Sueker Research Assistant Professor in Biomedical Engineering, University of North Dakota (United States) Product Manager, SafetySpect, Inc. (United States)

Dr. Mitchell Sueker is a Research Assistant Professor in Biomedical Engineering at the University of North Dakota and a Product Manager at SafetySpect. His research and professional work center on multimodal spectroscopy, optical imaging, and machine learning for biomedical and food safety applications.

Dr. Sueker has contributed to the development and validation of several multimodal spectroscopic systems, including the Pressure Injury Prevention Assessment (PIPA) device for early tissue damage detection and handheld platforms for seafood quality assessment supported by NOAA and USDA collaborations. His experience spans prototype development, embedded software integration, optical characterization, and algorithm design.

Working at the intersection of academia and industry, Dr. Sueker focuses on translating spectroscopy-based research into practical, data-driven diagnostic tools through close collaboration with engineers, clinicians, and commercial partners.

 

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Event Details

FORMAT: Panel discussion followed by audience Q&A.
MENU: Coffee, decaf, tea and water will be available nearby.
SETUP: Theater seating