I am a computer scientist with a passion for using computational methods in addressing urban and environmental problems. My research focus is on the design of algorithms for extracting patterns from spatio-temporal data. The knowledge acquired from such data can be used to create a data-driven and system-level view of an urban/environmental phenomenon. This knowledge can lead to better decisions for addressing these problems. One of my goals is to make these algorithms more accessible to domain users by automating low-level tasks in the machine learning pipeline that are often time-consuming and tedious.
I am currently working as assistant professor at Leiden University. I had an amazing time as a Φ-lab visiting scholar for a month in October 2019, focusing on the design of new algorithms for enhancing physical spatio-temporal models using AI and machine learning. I received my PhD degree in computer science from the University of Twente in 2015, followed by a post-doc research period on spatio-temporal data analysis from 2015–2017. I joined Leiden University, respectively, in 2017. Currently, I am also affiliated with the Leiden Centre of Data Science (LCDS), where I collaborate with researchers in other disciplines (e.g., environmental scientist) with interest in spatio-temporal data modelling.
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