Technology Innovation Showcase
Featured Technologies
The showcase will highlight cutting-edge technologies and research concepts. Below are additional details of each innovation that will be a the showcase.
Innovation Spotlight Presentations
Inventors: Dr. Daran Rudnik, Dr. Josefina Lacasa, Rayhaan Kabenge, Tumwesige Kabateraine
Technology Domain(s): Data Analytics & Visualization, Precision Agriculture
Description: Many farms already collect irrigation-use data through flow meters or electric meters, but the information is usually reported only as a cumulative total. This dashboard converts those existing measurements into a simple, in-season irrigation requirement window that shows whether a field is trending below, within, or above an appropriate range, helping producers manage water without surrendering control to an automated prescription.
Inventors: Dr. Hande McGinty, Yinglung Zhang, Aryan Singh Dalal, Srikar Reddy Gadusu
Technology Domain(s): Artificial Intelligence / Machine Learning
Description: OLIVE helps experts build and update ontologies using large language models through a simple interface. It converts user prompts and research text into structured knowledge graphs stored in Neo4j. Experts can review, visualize, merge, and refine results while checking errors and inconsistencies.
Inventors: Dr. Ajay Sharda, Aashvi Dua
Technology Domain(s): Artificial Intelligence / Machine Learning, Data Analytics & Visualization, Precision Agriculture
Description: A functional cloud and web - based minimum viable product has been developed and tested using agricultural spatial and tabular datasets, including UAV multispectral imagery, geospatial field boundaries, breeding plot shapefiles, vegetation indices, and tabular field measurements.
Innovation Alley
Inventors: Dr. Laura Miller, Dr. Doina Caragea
Technology Domain(s): Artificial Intelligence / Machine Learning, Biosecurity & Animal Health
Description: This new tool that uses artificial intelligence (AI) to read veterinary test results from simple paper-based strips (similar to a COVID-19 rapid test). Currently, these tests are sometimes hard to read by eye. This AI tool acts like a digital assistant, analyzing photos of the test strips to provide more accurate and sensitive results. This technology is designed to work on basic smartphones, making it especially useful for veterinarians and clinics in areas that lack expensive laboratory equipment.
Inventor: Dr. Rahul Harsha Cheppally
Technology Domain(s): Robotics and Automation, Computer Vision and Image Analysis
Description: An autonomous system that detects and sprays.
Inventors: Dr. Charles Carlson, Dr. Carle Ade, Dr. Dave Thompson
Technology Domain(s): Sensors and IoT, Artificial Intelligence / Machine Learning
Description: Every time your heart beats, it pushes blood through your circulatory system, and that movement of blood causes your entire body to shift ever so slightly which is too subtle to feel, but detectable with modern sensors. The ballistocardiogram (BCG) represents these tiny movements, and the technology we’ve developed shows that characteristics of the waveform are closely tied to blood pressure and related cardiovascular parameters and potentially body composition (e.g., body fat). Thus, simple sensors can be integrated into furniture (e.g., a bathroom scale, a bed, or a wearable device) and could one day give doctors a continuous, effortless window into your cardiovascular health or body composition without any cuffs, needles, or clinic visits.
Inventors: Dr. Todd Gunderson, Dr. Brad White, Dr. Robert Larson, Dr. Brian Vander Ley
Technology Domain(s): Computer Vision and Image Analysis, Artificial Intelligence / Machine Learning, Data Analytics & Visualization
Description: We are developing computer models that can take data collected as part of a routine bull breeding soundness examination and use it to make better predictions of bull fertility. This will directly benefit producers, who will be able to use these predictions to be more efficient and profitable with how they procure and use bulls. This in turn will benefit veterinarians, who will be able to use the computer models to add value to their services.
Inventors: Dr. Hande McGinty, Mikel Ridgeway
Technology Domain(s): Artificial Intelligence / Machine Learning
Description: A system that utilizes knowledge graphs and machine learning in order to predict the effects, mechanism, and other traits of chemicals based on structure. Is able to intake a chemical structure, identify if the uploaded chemical is a threat, and display any similar chemicals, allowing the user the ability to quickly classify drugs that have not been seen before.
Inventors: Araya Berhe, Dr. Gaurav Jha, Prasad Jayant Deshpande, Udit Debanshi
Technology Domain(s): Data Analytics and Visualization, Precision Agriculture, Crop Modeling and Decision Support System
Description: Precision agriculture, DSSAT-Pythia (python powered spatially gridded crop simulation modeling) and data analytics and visualization. Data driven, field specific management technology to make better crop and water use decisions. Computer models were used to estimate crop growth, yield, irrigation water needs and to support management decisions Data analytics: Spatial crops, and water data were generated and turned into interactive maps and graphs.
Inventors: Dr. Suprem Das, Aarthi Kannan, Shreyansh Mishra
Technology Domain(s): Sensors and IoT, Precision Agriculture
Description: NitroSense aims to explore the research and product development, market opportunity, growth projections, and validation plan for printed nitrogen-based nanosensors. The technology leverages in-house proprietary two-dimensional nanomaterials development and printed sensor fabrication made for low-cost, room-temperature, and conformal deployments.
Inventors: Dr. Ajay Sharda, Benjamin Vail, Dr. Rahul Harsha Cheppally, Sidharth Ra
Technology Domain(s): Computer Vision and Image Analysis, Artificial Intelligence / Machine Learning, Precision Agriculture
Description: A small grain row-unit integrated, multi-view image, GNSS, and IMU data collection platform. The system records synchronized data and provides real-time, in-cab feedback to operators.
Inventors: Dr. Ajay Sharda, Dr. Brian McCornack, Dr. Rahul Harsha Cheppally, Sidharth Ra, Sudan Baral
Technology Domain(s): Computer Vision and Image Analysis, Artificial Intelligence / Machine Learning, Data Analytics & Visualization
Description: A handheld and ATV-mountable edge perception device capable of performing real-time computer-vision inference and producing actionable insights and diagnostics for crop characteristics and health metrics.
Inventors: Prasad Jayant Deshpande, Dr. Gaurav Jha, Victor Braga Antiquera
Technology Domain(s): Data Analytics & Visualization, Precision Agriculture
Description: This project would help farmers see how well modern weather forecasts match real conditions at or near their fields. By letting users compare their own weather data or nearby Mesonet data with GenCast, i.e., AI-based weather forecast model by Google, the dashboard can make forecast accuracy more transparent and easier to trust.