01 / Connected Radar
Connected Radar — MAAS meets machine learning.
Our flagship research direction. Real-time, fine-grained, coordinated control of multiple connected radar systems through the MAAS cyberinfrastructure, fused with machine-learning-driven adaptive scanning. Enables agile sampling of fast-evolving atmospheric phenomena that conventional fixed-scan radars cannot capture.
MAASMachine learningAdaptive sensingMulti-radar
02 / MAAS
Multisensor Agile Adaptive Sampling.
The cyberinfrastructure backbone of Connected Radar. NSF-CISE-funded framework providing real-time, fine-grained, coordinated control across connected radar systems with feature detection, tracking, and integration of drones and phased-array radars.
NSF CISEReal-timeCyberinfrastructure
03 / Radar remote sensing
Millimeter-wavelength & phased-array systems.
Development and deployment of multi-frequency radar systems for high-resolution observation of clouds and precipitation. Doppler-spectra analysis, polarimetric retrievals, and dual-wavelength techniques.
Ka · X · KuPolarimetry
04 / Cloud microphysics
Ice nucleation, droplets, entrainment.
Ice nucleation, precipitation formation, aerosol-cloud interactions, entrainment, and droplet activation. In-situ + remote sensing + simulations.
In-situMixed-phase
05 / Spaceborne missions
EarthCARE, WIVERN, INCUS.
Forward modeling tools and retrieval algorithms for spaceborne radar observations of clouds and precipitation.