Zachary Sickmann

Zachary Sickmann is an Assistant Professor in the School of Natural Sciences and Mathematics at the University of Texas at Dallas. His research focuses on sedimentology, stratigraphy, and sediment provenance, with applications in environmental monitoring, construction materials, and climate change studies.

His research interests include:

• Sediment transport in coastal and estuarine systems
• Detrital records of glaciation and sea-level change
• Fingerprinting sand sources for traceable construction material sourcing
• Machine learning applications in geological image analysis
• Tectonic controls on deep-water sediment dispersal

His recent publications highlight a strong trend in integrating traditional geological field and laboratory methods with data science and machine learning, particularly through the development of the sandID project, which aims to create a global database for sand provenance using image-based classification. This work bridges academic research with practical applications in sustainability and resource management.

Scientific contributions and projects:

• sandID: A machine learning–driven tool for identifying sand composition and provenance via image analysis
• Citizen science initiative for global sand sample imaging
• Collaborative research on sediment supply networks and environmental change

Dr. Sickmann actively seeks contributions from citizen scientists and researchers to expand the sandID dataset. He is involved in advising and mentoring through research participation, though no formal students are listed. His work has implications for sustainable construction, coastal management, and paleoenvironmental reconstruction.