Machine Learning & Sensing Lab

The Machine Learning and Sensing Laboratory develops machine learning methods for autonomously analyzing and understanding sensor data.

We investigate and develop 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

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 – Current
Related Links: UF|IFAS Article

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 – Current
Related Links: UF|IFAS Article

Rays for Roots: Integrating Backscatter X-Ray Phenotyping, Modeling, and Genetics to Increase Carbon Sequestration and Resource Use Efficiency
Funding Agency:ARPA-E
PI: A. Zare
Dates: May 2017 – Current
Related Links: ARPA-E ROOTS Project Descriptions | ARPA-E Announced $70M in Funding | UF HWCOE Article

CAREER: Supervised Learning for Incomplete and Uncertain Data
Funding Agency: National Science Foundation
PI: A. Zare
Dates: May 6, 2014 – Current
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 at Univ. of Texas at Austin
Dates: August 2015 – Current
Related Links: UT Austin Article | UF HWCOE Article

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 at Univ. of Missouri
Dates: May 2016 – Current

Multi-Sensor Fusion for Buried Object Detection
Funding Agency: Army Research Office
PI: A. Zare
Dates: April 2017 – Current

Multi-Aspect Underwater Scene Understanding
Funding Agency: Office of Naval Research
PI: A. Zare
Dates: April 1, 2014 – Current
Related Links: MU Article 2015 | MU Article 2016

Completed Projects

Algorithm and Decision Support for Buried Object Detection
Funding Agency: Army Research Office
PI: A. Zare
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
PI: A. Zare
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
PI: A. Zare
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
PI: A. Zare
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
PI: A. Zare
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
PI: A. Zare
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
PI: A. Zare
Dates: September 2010 – October 2011
Note: Research conducted at Dr. Zare’s prior appointment at the Univ. of Missouri