Knowledge discovery and data mining to understand large-scale dynamics, extract multi-dimensional spatiotemporal correlations, predict future behaviors, and make intelligent decisions in complex heterogeneous networks applied to active sensing (US Patent 10,743,198) and transfer learning (US Patent 11,046,247). 

Data and Physics Driven Active Sensing
Heterogeneous Pedestrians Deep Q Learning & Social Force Dynamics
Part of NASA JPL ”MAARS” project led by Dr. Ono

Research Highlights

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Publications

A full list of published work.

If you are interested in joining us, read my CV, send an email to hpark1@ncat.edu or fill below with your CV, and address a specific contribution to the projects listed on this webpage.