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  • šŸ‘‹ Hi, Iā€™m Ekin Ugurel.
  • šŸ‘€ Iā€™m interested in mobile sensor data for human mobility modeling.
  • šŸŒ± Iā€™m currently learning about Gaussian Processes, kernel methods, and statistical modeling of spatiotemporal data.
  • šŸ’žļø Looking to collaborate? Reach out!
  • šŸ“« You can email me at ugurel [at] uw [dot] edu

Ekin's Projects

cse547 icon cse547

Class files for CSE 547: Machine Learning for Big Data

ekinugurel.github.io icon ekinugurel.github.io

Github Pages template for academic personal websites, forked from mmistakes/minimal-mistakes

evclom icon evclom

A Python-based optimization model framework for minimizing daily charging load variation from electric vehicle charging events with respect to user-defined target charging loads.

geolife-mobility-data-app icon geolife-mobility-data-app

A Python-based application utilizing Streamlit to provide structured, interactive visualizations on the GeoLife GPS Trajectories dataset.

gpsimpute icon gpsimpute

Includes codes for "Correcting Missingness in Passively-Generated Mobile Data with Multi-task Gaussian Processes"

physics-regularized-mtgp icon physics-regularized-mtgp

Includes codes for the forthcoming paper, "Learning to generate synthetic human mobility data: A physics-regularized Gaussian process approach based on multiple kernel learning"

satmobfusion icon satmobfusion

A novel real-time event-identification framework fusing satellite imagery with mobile sensor data

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