The Machine Learning and Sensing Laboratory develops machine learning methods for autonomously analyzing and understanding sensor data.
We investigate and develop artificial intelligence, machine learning, pattern recognition, computational intelligence, signal processing, and information fusion methods for application to sensing. Applications we have studied include landmine and explosive object detection, automated plant phenotyping, sub-pixel target detection, and underwater scene understanding. We have developed algorithms for ground-penetrating radar, hyperspectral imagery, electromagnetic induction data, synthetic aperture SONAR, and minirhizotron imagery.
Current Projects
Center for Multiscale Modeling of Multiphase Combustion (CM3C)
Funding Agency: DOE
Role: Co-PI; PI: S. Balachandar
Dates: August 2025 – Current
Related Links: News Stories
Paving the Way for Adoption of New Technologies
Funding Agency: University of Florida Strategic Funds
Role: Co-PI; PI: S. Thornsbury
Dates: January 2025 – Current
DSFAS: Getting to the Core of Roots: Model-Informed Machine Learning for Phenotyping and Mapping
Funding Agency: USDA NIFA
Role: PI
Students: Aditya Dutt, Juan Diaz
Dates: August 2024 – Current
Using Machine Learning to Uncover the Role of Tortoises in Shaping Freshwater Ponds in the Galápagos
Funding Agency: UF Biodiversity Institute
Role: Co-PI; PI: A. Subalusky, UF Biology
Dates: July 2024 – Current
HCC: Medium: Optimizing Interactive Machine Learning Tools to Support Plant Science
Funding Agency: NSF
Role: Co-PI; PI: L. Anthony, UF CISE
Students: Diandra Ojo, Ayesha Naikodi
Dates: October 2023 – Current
Equipment: MRI: Track 2 Acquisition of a Novel Performance-Driven 3D Imaging System for Extremely Noisy Objects (NPIX)
Funding Agency: NSF
Role: Co-PI; PI: N. Asadi, UF ECE
Dates: October 2023 – Current
Domain Transfer for Continuity of Performance Across Synthetic Aperture Sonar Systems
Investigate domain transfer approaches to translate data and algorithms across SAS sensing systems.
Funding Agency: ONR
Role: Co-PI; PI: J. Fairbanks, UF CISE
Students: Sam Gallic, Luke Saleh
Dates: August 2023 – Current
Research into aflatoxin mitigation that is ongoing and proposed by the University of Florida and Mississippi State University in partnership with Premium Peanut
Funding Agency: USDA/ARS National Peanut Research Laboratory
Role: Co-PI; PI: B. Tillman, UF Agronomy
Students: Khaled Hamad
Dates: January 2023 – Current
MCA: Improving understanding of controls over spatial heterogeneity in dryland soil carbon pools in the age of ‘big data’
Machine learning techniques related to detecting surface features from imagery in dryland ecosystems.
Funding Agency: NSF
Role: Senior Personnel; PI: H. Throop, Arizona State University
Students: Clinton Jules
Dates: August 2022 – Current
DSFAS-CIN: Alliance of Plant Phenotyping Software (APPS) Developers: Integration and Interoperability of Open-Source Tools to Support Plant Phenotyping for Agriculture
This effort is to create an open source plant phenotyping software package and platform.
Funding Agency: USDA NIFA
Role: Co-PI; PI: M. Gehan
Students: Ayesha Naikodi
Dates: January 2022 – Current
AI-HARVEST: Artificial Intelligence Hub for Agricultural Reporting and Verification of Ecosystem Services through Sensing Technologies
In this effort, we are developing hybrid- deep learning and crop modeling tools to measure and quantify ecosystem services provided by an agricultural system.
Funding Agency: FDACS
Role: Co-PI; PI: M. Dukes
Students: Satya Krishna Pothapragada
Dates: February 2021 – Current
Related Links: Smarter Agriculture Takes Root
SiTS: Hyperspectral Signals in the Soil
In this effort, we will build hyperspectral cameras (which also collect information outside of the visible range collected by standard color cameras) that will be inexpensive, have an automated mechanism to move up and down minirhizotron tubes, and are paired with automated algorithms to process and understand the collected data.
Funding Agency: USDA NIFA
Role: PI
Students: Ritesh Chowdhry
Dates: January 2021 – Current
Related Links: UF Article 2020 | Horti Daily Article 2021 | WCJB News Story and Video #1 2021 | WCJB News Story and Video #2 2021 | Villages Daily Sun 2021 | Fox 13 Tampa Bay 2021 | Florida Insider 2021 | Independent 2021 | Reuters 2021 | Smarter Agriculture Takes Root
Testing predictions of plant-microbe-environment interactions to optimize climate adaptation and improve sustainability in switchgrass feedstocks
This work will leverage a field-established genetic resource network (S-GENE) to deepen understanding of local adaptation and to identify beneficial traits, genes, and microbial associates that contribute to switchgrass productivity.
Funding Agency: DOE
Role: Co-PI; PI: T. Juenger, UT Austin
Dates: September 2020 – Current
Students: Diandra Ojo, Bakari Kerr
Related Links: UF Article 2020 | UT Article 2020 | Smarter Agriculture Takes Root
NSF Engineering Research Center for Internet of Things for Precision Agriculture
This effort is an NSF ERC focused on the development of Internet of Things (IoT) for Precision Agriculture and the infrastructure (including algorithm development) needed to effectively deploy IoT devices for precision agriculture.
Funding Agency: NSF
Role: Co-PI; PI: C. Kagan, UPenn
Dates: September 2020 – Current
Students: Anna Hampton, Khaled Hamad, Chloe Nolan
Related Links: UF Article #1 2020 | UF Article #2 2020 | UF Article #3 2020 | UF Article #4 2021 | IoT4Ag Homepage| NSF Award Article 2020 | Purdue Article 2020 | UC Merced Article 2020 | WCJB News Story and Video 2020 | Smarter Agriculture Takes Root
Completed Projects
Identifying drought-resistance traits and drought stress limits of southeastern peanuts
Developing plant phenotypic approaches to identify drought-resistance and drought stress in peanuts.
Funding Agency: NPB
Role: Co-PI; PI: W. Hammond, UF Agronomy; Co-PI: B. Tillman, UF Agronomy
Dates: January 2023 – June 2024
FreshID: Fruits and Vegetables Quality Evaluation Using Hyperspectral Imaging System
In this effort, we are developing AI-based approaches to detect and predict vegetable “freshness” levels.
Funding Agency: USDA NIFA and UF Research
Role: Co-PI; PI: T. Liu, UF Horticulture
Dates: June 2021 – April 2025
Related Links: UF Article 01 2021 | UF Article 02 2021 | WCJB News Story and Video 2021 | Gainesville Sun Article 2021
Adaptive Manifold Learning for Multi-Sensor Translation & Fusion given Missing Data
Funding Agency: Center for Big Learning
Role: PI
Dates: May 2018 – December 2024
AI for Climate Smart Florida Agriculture
These funds are to support students interested in exploring the use of artificial intelligence for climate smart agriculture. The funds are dedicated to provide student scholarships to support data collection activities at producer locations throughout the state of Florida.
Funding Agency: Solutions from the Land
Role: PI; Co-PI: J. Dubeux
Dates: November 2021 – December 2024
HYPERspectral Plant HYdration Status (HYPER-PHYS): a novel and scalable method for sensing plant function, dysfunction, and failure on a warming planet
Develop HYPERspectral Plant HYdration Status (HYPER-PHYS), a novel and scalable method for sensing plant function, dysfunction, and mortality. Developing HYPER-PHYS will allow monitoring of plant water status in high-throughput agricultural plant breeding programs, while also enabling ecosystem-scale monitoring of plant water status in biodiverse natural systems.
Funding Agency: UF Research
Role: Co-PI; PI: W. Hammond; Co-PI: G. John
Dates: June 2022 – December 2024
Countermine Division’s Electro-Optical and Infrared Detection Algorithms
Develop and validate target detection algorithms.
Funding Agency: DoD
Role: PI; Co-PI: J. Fairbanks; J. Wilson
Dates: August 2022 – December 2024
MRA: Disentangling Cross-scale Influences on Tree Species, Traits, and Diversity from Individual Trees to Continental Scales
Trees are essential to ecosystems. They store carbon, reduce erosion, and serve as habitat for other species. The factors influencing trees, and the spatial scales at which they are managed, range from an individual tree to entire continents. Since there are approximately three trillion trees in the world collecting data on every tree over large areas is impossible using traditional methods. Therefore, it is necessary to use new technology to measure and describe individual trees over large geographic areas. This research will address this fundamental challenge by combining high resolution remote sensing data with field data on trees.
Funding Agency: NSF
Role: Co-PI; PI: E. White, Univ. Florida
Dates: August 2019 – August 2024
Related Links: Project Website
Robust and Reversible Deep Nets for Synthetic Aperture Sonar Analysis
This project is developed automated outlier detection and competency awareness techniques for deep learning architectures with specific application to synthetic aperture sonar image analysis.
Funding Agency: Naval Surface Warfare Center
Role: PI
Dates: August 2020 – July 2024
Superpixel Segmentation and Texture Feature Learning for Multi-Aspect Underwater Scene Understanding
In this project, we are developing segmentation and texture feature analysis methods for automated underwater scene understanding using synthetic aperture sonar.
Funding Agency: DOD
Role: PI
Dates: May 2020 – April 2024
Understanding pre-harvest and post-harvest factors that can help to mitigate aflatoxin in peanut
This project is investigating and working to identify both pre- and post-harvest risk factors for Aflatoxin develop in peanut production. The effort involves imaging to directly detect evidence of aflatoxins as well as advancing models to combine environmental and management factors to predict aflatoxin risk.
Funding Agency: Industry Sponsors
Role: Co-PI; PI: B. Tillman, Univ. Florida
Dates: February 2021 – December 2023
Hurricane effects on the distribution and management of plant invasions in coastal habitats
In this effort, we are using on-the-ground plant measurements and aerial hyperspectral sensing to evaluate the effects of hurricanes on Brazilian peppertree.
Funding Agency: Everglades National Park
Role: Co-PI; PI: L. Flory, UF Agronomy
Dates: September 2020 – December 2023
Related Links: UF Article 2021
SENTINEL: SENsing Threats In Natural Environments using Ligand-receptor modules
Funding Agency: DARPA
Role: Co-PI; PI: D. Nusinow, Danforth Plant Science Center
Dates: September 2018 – September 2023
Improved system assessment of aflatoxin risk utilizing novel data and sensing
Funding Agency: USDA NIFA
Role: Co-PI; PI: D. Rowland at Univ. Florida
Dates: May 2018 – January 2023
Related Links: UF|IFAS Article
Coordinated Adaptive Phenotyping (CAPs) for Improving Soil Water Acquisition
Funding Agency: USDA NIFA
Role: Co-PI; PI: B. Tillman at Univ. Florida
Dates: June 2018 – December 2022 Related Links: UF|IFAS Article
Satellite estimation of Bahiagrass yield and crude protein
In this effort, satellite remote sensing imagery is being used to estimate parameters of interest in pasture used for cattle ranching.
Funding Agency: Industry Partners
Role: Co-PI; PI: C. Wilson, UF Agronomy
Dates: May 2020 – August 2022
Related Links: UF Article 2021 | Gainesville Sun News Story 2021
AEROFUSION-MLUQ: Mars Lander Aerodynamic Model Data Fusion using Machine Learning
In this effort, the team is developing machine learning tools to quantify uncertainty in planetary landing systems. The effort will advance sensitivity analysis, outlier identification, multi-sensor fusion, and associated uncertainty quantification on sensor analysis performed.
Funding Agency: NASA
Role: Co-PI; PI: M. Lee, NASA
Dates: August 2020 – July 2022
Environmentally-aware Feature Extraction/Selection and Classification of Underwater Objects in Synthetic Aperture Sonar Imagery for Mine Countermeasures
Funding Agency: Office of Naval Research
Role: Co-PI; PI: J. Keller, Univ. of Missouri
Dates: May 2016 – Dec. 2021
What mind matters? Machine learning approaches to linking structural variation in the brain to individual differences in spatial behavior
Funding Agency: UF Research, AI Catalyst Funds
Role: Co-PI; PI: S. Weisberg, UF Psychology
Dates: Nov. 2020 – Dec. 2021
Related Links: UF Article 2021
Parasitic Nematode Identification with Deep Learning
Funding Agency: UF Research, AI Catalyst Funds
Role: PI
Dates: Nov. 2020 – Nov. 2021
Related Links: UF Article 2020 | UF IFAS Article 2021 | UF Explore Article 2021 | Growing Produce Article 2021
Rays for Roots: Integrating Backscatter X-Ray Phenotyping, Modeling, and Genetics to Increase Carbon Sequestration and Resource Use Efficiency
Funding Agency: ARPA-E
Role: PI
Dates: May 2017 – Aug 2021
Related Links: ARPA-E ROOTS Project Descriptions | ARPA-E Announced $70M in Funding | UF HWCOE Article | UF Research Awards
Cyber-Physical Systems Security through Robust Adaptive Possibilitistic Algorithms: a Cross Layered Framework
Funding Agency: NSF
Role: Co-PI; PI: A. Bretas, Univ. Florida
Dates: August 2018 – July 2021
Multi-Sensor Data Fusion for Buried Target Detection
Funding Agency: Army Research Office
Role: PI
Dates: April 2017 – May 2021
CAREER: Supervised Learning for Incomplete and Uncertain Data
Funding Agency: National Science Foundation
Role: PI
Dates: May 2014 – Apr. 2021
Related Links: Project Website | NSF Award Abstract | MU Article| MIZZOU Magazine Article
Climate Adaptation and Sustainability in Switchgrass: Exploring Plant-Microbe-Soil Interactions across Continental Scale Environmental Gradients
Funding Agency: Department of Energy
Role: Co-PI; PI: T. Juenger, Univ. of Texas at Austin
Dates: August 2015 – March 2021
Related Links: UT Austin Article | UF HWCOE Article | Smarter Agriculture Takes Root
Development of Competitive Analytic Research Methodologies with Universities, Volunteer Geospatial Information Methodologies GEOINT Curriculum Development and Scientific Exchange
Funding Agency: NGA
Role: Co-PI; PI: P. Gader, Univ. Florida
Dates: March 2018 – March 2021
Multi-Aspect Underwater Scene Understanding
Funding Agency: Office of Naval Research
Role: PI
Dates: Apr. 2014 – Dec. 2020
Related Links: MU Article 2015 | MU Article 2016
Taking the next steps towards making drone data applicable: novel approaches for directly relating UAV images to peanut maturity, disease, and drought
Funding Agency: National Peanut Board
Role: PI
Dates: Jan. 2019 – June 2020
Peanut Volatile Organic Compounds Analysis
Funding Agency: National Peanut Board
Role: PI
Dates: Jan. 2019 – June 2020
Related Links: Georgia Tech Article
Biodiversity Data from Insect Songs: New hardware and software for monitoring insect bioacoustics, and new opportunities for public outreach
Funding Agency: UFII & UFBI
Role: Co-PI; PI: B. Stucky, Univ. Florida
Dates: Nov. 2018 – May 2020
Peanut seed quality research
Funding Agency: APSA
Role: Co-PI; PI: D. Rowland, Univ. Florida
Dates: Aug. 2018 – July 2019
Robust Hyperspectral Image Analysis via Computational Topology
Funding Agency: UFII
Role: Co-PI; PI: P. Bubenik, Univ. Florida
Dates: Aug. 2017 – Aug. 2018
Algorithm and Decision Support for Buried Object Detection
Funding Agency: Army Research Office
Role: PI
Dates: October 2016 – April 2017
New Investigator Program Award: Functions of Multiple Instances for Hyperspectral Analysis
Funding Agency: National Geospatial-Intelligence Agency
Dates: September 30, 2014 – October 2017
Role: PI
Note: Research conducted at Dr. Zare’s prior appointment at the Univ. of Missouri
Machine Learning Techniques for Handheld Subsurface Object Detection
Funding Agency: Army Research Office
Role: PI
Dates: November 1, 2013 – October 2016
Note: Research conducted at Dr. Zare’s prior appointment at the Univ. of Missouri
Understanding root growth using X-ray CT Imaging to increase crop yields
Funding Agency: Mizzou Advantage
Role: Co-PI; PI: S. Kovaleski
Dates: June 2014 – September 2016
Note: Research conducted at Dr. Zare’s prior appointment at the Univ. of Missouri
Adaptive Underwater Target Detection
Funding Agency: MU Research Board
Role: PI
Dates: January 1, 2014 – May 2015
Note: Research conducted at Dr. Zare’s prior appointment at the Univ. of Missouri
Environmentally-Adaptive Target Recognition Systems
Funding Agency: Naval Surface Warfare Center
Role: PI
Dates: April 2014 – May 2015
Note: Research conducted at Dr. Zare’s prior appointment at the Univ. of Missouri
Mathematical Models for Describing and Reasoning with Geographic and Human Cultural Features
Funding Agency: DOD
Role: Co-PI; PI: J. Keller
Dates: October 2010 – December 2014
Note: Research conducted at Dr. Zare’s prior appointment at the Univ. of Missouri
Explosive Object Detection with Electromagnetic Induction Sensors
Funding Agency: DOD
Role: PI
Dates: September 2011 – May 2014
Note: Research conducted at Dr. Zare’s prior appointment at the Univ. of Missouri
Probabilistic Hyperspectral and LIDAR Fusion
Funding Agency: DOD
Dates: October 1, 2010 – October 31, 2013
Note: Research conducted at Dr. Zare’s prior appointment at the Univ. of Missouri
Airborne Multispectral Imagery (MSI) and ground-based Ground Penetrating Radar (GPR) Fusion
Funding Agency: DOD
Role: PI
Dates: September 2010 – October 2011
Note: Research conducted at Dr. Zare’s prior appointment at the Univ. of Missouri