Emma Bennett
Cohort 2025 · Computer Science
Emma Bennett develops graph-based solutions to computer vision applications in fields such as materials science, sensing, and precision agriculture. This includes problems like carbon nanotube segmentation and tracing, aerial localization, and crop yield prediction. Her research also explores quantum-classical learning and computing for large-scale experiments using the NSF Nautilus cluster.
Advisor · Filiz Bunyak
Emma Bennett is a PhD student in Computer Science at the University of Missouri. She received her undergraduate degree also at the University of Missouri in Chemical Engineering, and prior to graduate school worked in engineering consulting designing industrial wastewater treatment systems. She currently does computer vision research under Dr. Filiz Bunyak. She is also an NSF NRT trainee, undergraduate research mentor, and graduate teaching assistant.
Publications
- Graph attribute encoding and sparse graph integral histograms for efficient aerial localization (2026) · Journal of Applied Remote Sensing
- Quantum-Enhanced Similarity Measures for Polarimetric Materials Classification (2026) · arXiv (Cornell University)
- Aerial visual localization through novel applications of Weisfeiler-Lehman graph embeddings (2025) · Geospatial Informatics XV
- Bag-of-graph-attributes and sparse graph structures for efficient UAV localization in complex environments (2025) · Geospatial Informatics XV
Leadership history
- Officer of Public Engagement · 2026–present