Using Machine Leaning and Math in LiDAR 3D point clouds


Dr. Francis Patricia Medina

On Thursday, October 13th, 2022 Virtually via Zoom FROM 1:00-2:00 PM.

Meeting ID: 586 526 2264 and Passcode: SIAM2022
The talk is on
Using Machine Leaning and Math in LiDAR 3D point clouds

LiDAR point clouds contain measurements of complicated natural scenes and the classes are comprised of natural features. We present a preliminary comparison study for the classification of 3D point cloud LiDAR data that includes several types of feature engineering. We also include experiments with several dimension reduction strategies and introduce the product coefficients which might have different patterns for different classes. We’ll compute the product coefficients on a simple example to get further understanding of how they can represent a measure. The idea is that we can see the connections between mathematical tools from areas on mathematics such as measure theory and machine learning in the sciences.

Dr. F. Patricia Medina is an assistant professor at the Department of Mathematics at City Tech. Dr. Medina holds a PhD in Mathematics from Oregon State University, two masters in Mathematics and a postdoc in machine learning at Worcester Polytechnic Institute. She also was visiting postdoctoral scholar in ICERM, Brown University. Before coming to City Tech, Dr. Medina was an assistant professor in Computer Science at Yeshiva University. Dr. Medina’s background includes Banach space theory, measure theory, machine learning, numerical analysis and applied functional analysis. She has several publications on machine learning and the mathematical analysis of methane models and has made several presentations on her research. Her grants include Azure computing from Microsoft and Google Explore.
She co-organized the AMS-AWM Session on Mathematical and Computational Research in Data Science (AWM Sponsored) at the Join Mathematics Meeting (the largest mathematics meeting in the world). She was also part of the 2017 and 2019 ICERM research collaboration workshops at Brown University, launching the Women in Data Science and Mathematics (WiSDM) Research Network.

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