I teach and conduct research in the area of artificial intelligence and machine learning as a Professor in the Electrical and Computer Engineering Department at the University of Florida and lead the Machine Learning and Sensing Laboratory, in addition to being an Associate Dean for Research and Facilities. My research has focused primarily on developing machine learning algorithms to autonomously understand and process non-visual imagery. My research work has included automated plant root phenotyping using visual and X-ray imagery, 3D reconstruction and analysis of X-ray micro-CT imagery, sub-pixel hyperspectral image analysis, target detection and underwater scene understanding using synthetic aperture sonar, LIDAR data analysis, Ground Penetrating Radar analysis, and buried landmine and explosive hazard detection.

I am an Assistant Professor in the Department of Geographical and Sustainability Sciences at the University of Iowa. I work at the intersection of machine learning, remote sensing, and ecology to understand our functioning natural environment. The ability to capture high temporal, spatial, and spectral resolution imagery has advanced much more rapidly than algorithms for processing, visualizing, and interpreting these images. In my work, I aim to develop algorithms and methodologies for image processing that transform the data into manageable and applicable information for future applications. I use computational spatial methods to overcome these challenges, primarily with airborne hyperspectral, thermal, and LiDAR data.

I am an Assistant Member and Principal Investigator at the Donald Danforth Plant Science Center. The Gehan lab develops high-throughput phenotyping approaches to study mechanisms of crop resilience under temperature stress.

I am the Director of the Data Science group at the Donald Danforth Plant Science Center. The Data Science group works at the intersection of plant science and computational sciences. In particular, the group develops data management and analysis software and approaches for proximal and remote sensing of plants. These tools are used to quantitatively measure plant phenotypes and responses to the environment for applications in foundational research, breeding, and precision agriculture.

I am a Data Scientist working in the Data Science and Gehan lab teams at the Donald Danforth Plant Science Center. I work mainly on software development and user support for the PlantCV project. Outside of work, I enjoy taking yoga and dance classes, indoor rock climbing, and taking my dog for weekend camping trips.

I am a Data Scientist in the Data Science and Gehan groups at the Donald Danforth Plant Science Center, and am the lead of the Above-Ground Phenotyping Expertise Core for the New Roots for Restoration Biological Integration Institute. I develop computer vision and machine learning tools for plant phenotyping.

I am a Master’s student in Computer Science at the University of Florida and am a member of the Machine Learning and Sensing Lab. For one of my projects, I am developing annotation tools for hyperspectral image data.