Michael is experienced with working with international teams of geoscientists as well as collaborations in the medical and transportation fields, on topic areas including embedded vision and radiolocation systems.
Michael’s geoscience research interests include studying microscale ionospheric turbulence using radio science, radar, and optical methods including:
To this end, Michael applies big data processing techniques from the machine learning and machine vision world to large geoscience datasets from instruments Michael sometimes develops himself. Michael is also a patron of the geosciences.
Michael works as a trailblazer in the open-science / open-data movement, having founded the Zenodo Space Physics and Aeronomy section. Michael endeavors to set a new normal in refereed publication with open-source code and open-data available for download a prerequisite for manuscripts to enter the review process.
Applications including challenging and novel remote sensing and medical imaging problems. Embedded/single board computers including
Remote Sensing and Wireless Networks
- unpowered quantitative sensor tags to be sensed from many meters away allowing precise location of particular devices in a cluttered environment or quantitative reading of unpowered sensors from several meters away.
- Raspberry Pi- and Red Pitaya-based software defined radar where the radar waveforms also transmit processed data products.