Overview
I work with domain experts across different fields to solve challenging real-world problems through the application or development of advanced signal processing, computer vision, machine learning (especially deep learning) methods to real-world problems. Recently, my work has spanned topics such as remote sensing, energy systems, and materials science. My work has recently been featured in premiere machine learning conferences (e.g., NeurIps, ICLR) and computer vision conferences (e.g., WACV).
Current Duke Appointments & Affiliations
Adjunct Assistant Professor in the Department of Electrical and Computer Engineering
·
2022 - Present
Pierre R. Lamond Department of Electrical and Computer Engineering,
Pratt School of Engineering
Recent Scholarly Works
When Centroids Mislead: Quantifying the Consequences of Sub-Optimally Aggregating Gridded Raster Data to Polygons
Journal article ISPRS International Journal of Geo Information · June 1, 2026 Point data, such as population, disease incidence, and greenhouse gas emissions, are commonly aggregated to a uniform grid of raster data for storage and representation. In many remote sensing applications, polygons are instead used to describe regions of ... Full text CiteAre deep learning models robust to partial object occlusion in visual recognition tasks?
Journal article Pattern Recognition · March 1, 2026 Image classification models, including convolutional neural networks (CNNs), perform well on a variety of classification tasks but struggle under conditions of partial occlusion of relevant objects. Methods to improve performance under occlusion, including ... Full text CitePhysics-informed learning in artificial electromagnetic materials
Journal article Applied Physics Reviews · March 1, 2025 The advent of artificial intelligence—deep neural networks (DNNs) in particular—has transformed traditional research methods across many disciplines. DNNs are data driven systems that use large quantities of data to learn patterns that are fundamental to a ... Full text CiteRecent Grants
Estimating Onsite Building Emissions
ResearchCo Investigator · Awarded by WattTime · 2022 - 2024Deep Context-aware Discriminative Learning for Buried Threat Detection: single sensor processing and multi-sensor fusion
ResearchCo-Principal Investigator · Awarded by Army Research Office · 2017 - 2022Estimating solar PV locations and capacity in San Diego, CA
ResearchCo-Principal Investigator · Awarded by Ernest Orlando Lawrence Berkeley National Laboratory · 2019 - 2021View All Grants
Education
Duke University ·
2015
Ph.D.