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My main research interest is around predictive modeling using big data from scale as micro as plant functional traits to the broader scale of global climate change. Applications of remote sensing, machine learning, and Bayesian statistics are used to study ecosystem functions in urban environment.  

Having led unique tech industry experiences in relating various different industries into development of convergence models, I am particularly keen in the interdisciplinary research development and open for collaborations with researchers in wider areas. And, this is why I was attracted to the domain of landscape architecture at its core.  While it is firmly grounded on our everyday earth, its potential of versatility is maximized through connecting with various different domains in academia from history to bioscience.