Carola Wenk is a Professor of Computer Science at Tulane University, with an adjunct appointment in Mathematics. Her research develops algorithms for interpretable spatial, geometric, visual, and mobility data analysis. Across domains ranging from geospatial systems and intelligent transportation to biomedical imaging and digital pathology, her work aims to reveal meaningful structure in complex data and to provide principled explanations for where patterns occur, how they relate, and why they matter.
A central foundation of Dr. Wenk’s research is computational geometry, with particular expertise in shape matching, trajectory analysis, graph comparison, and topological data analysis. She is an expert on the Fréchet distance and related distance measures for curves, trajectories, and geometric graphs. Her work on map matching, road map construction, and road map comparison has established algorithmic foundations for movement and transportation network analysis.
Her research also connects these foundations to AI-relevant problems in interpretable data analysis, topological machine learning, anomaly detection, biomedical image analysis, and large-scale agent-based simulation. Through DARPA- and IARPA-supported work, she has contributed to geosocial simulations of urban populations in which individual behaviors, constraints, and mobility decisions give rise to emergent patterns of life. This work supports the development and evaluation of methods for modeling human mobility, detecting behavioral anomalies, and understanding deviations from expected spatial and temporal patterns.
Dr. Wenk has received research, teaching, and service awards, including an NSF CAREER Award, multiple best paper awards, a 10-year impact award from ACM SIGSPATIAL GIS, and university-level teaching and service honors. She previously served as chair of Tulane’s Department of Computer Science. Her research has been supported by NSF, NIH, DARPA, IARPA, ARPA-H, and other funding agencies.