hafez ahmad

Graduate Teaching Assistant

Mississippi State University

United States

Research Interests

Explore related searches

Professors in United States

Contact this professor

Get a free first email built on one of their papers, ready for you to edit and send yourself.

About

Hafez Ahmad is a Graduate Teaching Assistant at Mississippi State University in the United States. His research focuses on hydrologic connectivity, land use and land cover dynamics, and the application of remote sensing and machine learning techniques in environmental studies. Recent publications include works on the dynamics of particulate organic carbon and cyanobacterial blooms, as well as the use of GIS for ecological assessment.

Articles (10)

Year:

2025

Year:

2025

Year:

2025

Year:

2025

Year:

2025

Year:

2025

Year:

2025

Year:

2025

Year:

2025

Year:

2025

Collaborators (2)

M M Nabi

Assistant Professor

Western Kentucky University

UNITED STATES

View details

Felix Jose

Professor

Florida Gulf Coast University

UNITED STATES

View details

ApplyKite TwinLearns as you apply

Make your next move.

Prepare your application

Review drafts before you send them.

hafez ahmad

Research Interests

Explore related searches

Contact this professor

About

Articles (10)

Land use and land cover dynamics in the Irrawaddy Delta: Remote sensing analysis and projections for the future

Hydrologic Connectivity in Floodplain Systems: A Multiscale Review of Concepts, Metrics and Management

Confluence of Time and Space: An Innovation for Quantifying Dynamics of Hydrologic Floodplain Connectivity With Remote Sensing and GIS

Confluence of Time and Space: An Innovation for Quantifying Dynamics of Hydrologic Floodplain Connectivity With Remote Sensing and GIS

Mapping the Dynamics of Particulate Organic Carbon: Satellite Observations of Coastal to Shelf Variability in the Northeastern Gulf of Mexico

Estimation of chlorophyll-a in uncrewed aircraft systems imagery using autonomous surface vessel data with machine learning algorithms and feature selection techniques

Machine learning-based estimation of chlorophyll-a in the Mississippi Sound using Landsat and ocean optics data

Spatiotemporal dynamics of cyanobacterial blooms: Integrating machine learning and feature selection techniques with uncrewed aircraft systems and autonomous surface vessel data

Spatiotemporal dynamics of cyanobacterial blooms: Integrating machine learning and feature selection techniques with uncrewed aircraft systems and autonomous surface vessel data

Using geographic information systems and remote sensing technique to classify land cover types and predict grassland bird abundance and distribution in Nairobi National Park, Kenya

Collaborators (2)

M M Nabi

Felix Jose

Make your next move.