About me
I have been working as a Research Data Scientist through most of my career so far with most of my work involving data science and decision support software tool development in the energy and technology field.
I got my PhD at the University of California, Berkeley in December 2017 in Civil and Environmental Engineering and for the last 4 years I was working as a senior Research Engineer at the Computer Science and AI Lab of a large global energy company, ENGIE. My research interests revolve around spatial analysis, geospatial data science, energy modeling, databases and visualization. My passions and research revolve around data science, geospatial data science, statistics, algorithms, databases, visualization, energy and climate resiliency. From my Ph.D. career, postdoctoral research and work experience, I have gained experience in programming, data science, modeling, machine learning, working with databases and efficient pipelines, vector and raster data particularly in integrating these tools with engineering analysis and optimal design. My previous professional experience and academic work allow me to have a deep understanding of working with data, creating efficient pipelines for software development and code management, applying algorithms and creating models and tools for understanding data and creating informative visualizations for solving environmental engineering problems.
My main research area during my PhD was using spatial data and systems-level modeling techniques develop software tools to assist the engineering decision making process. My research interests include modeling decentralized water reuse infrastructure to improve the usage of energy and resources under the constraints of climate change.