Our focus is on scientific computing and HPC modeling of the geospace environment, from the thermosphere through the ionosphere and out to the magnetosphere and beyond. In particular:
- endpoint computing and edge computing: reduce data at the sensor
- scalable OS-agnostic HPC algorithms
- precision radar and passive indoor radar / optical remote sensing
- broadband wireless systems including: broadcast, public safety, two-way voice/data radio, UAS, satellite
Applied mathematics stats:
- Erdős number == 5
- Mathematics Genealogy Project record
If you have an issue or suggestion with software we’ve written, it’s greatly preferred to raise a GitHub Issue for that package, as due to the large volume of email received, the emailed issue may be lost or handled much later.
The order of preferred (fastest to slowest) contact is:
- GitHub: scivision
- Keybase: michaelhirsch
- Twitter: sci_vision
email@example.com(consulting inquiries welcome)
- AFOSR-funded deployment to Greenland on multiscale (temporal and spatial) features in the aurora.
- multi-site auroral tomography system on the Poker Flat Research Range near Fairbanks, Alaska.
Code contributions to widely used projects include:
- Python type hinting subsystem
- Meson: core developer focusing on HPC and Fortran applications
- Ninja build
- GNU Octave
We have published over 110 geoscience and aerospace programs, including 28 HelioPython packages. Our work blends data science with full-stack hardware development, using data science with radar, GNSS, optical and other remote sensing techniques.
- developed harmonic radar and antennas at half the size and 85% less cost v. US Patent # 7,145,453
- designed and demonstrated the first coffee-can radar costing $35 to build
- Research and development in applied scientific computing, particularly for aerospace and geospace remote sensing
- geoscientist with expertise in RF systems
- expertise in remote sensing (multiple patents) using computer vision and machine learning
- solved the century-old problem of auroral discrimination based on physical driving mechanism via machine learning and computer vision techniques
- technology rights and geoscience outreach
- award-winning STEM educator
Growing engineering endeavors
We use comprehensive model-based engineering frameworks to first check feasbility and then turn an idea into a product. Broad engineering expertise combined with years of experience bring quick resolve to vexing system issues for geospace/geoscience research as well as corporate and government entities.
- comprehensive practical and theoretical design experience with RF systems from antenna to CPU and detailed propagation modeling
- remote sensing: radar & radio science–from microwatt to megawatt with EMC mitigation
- remote sensing: optical–terabytes/day reduced 1000x by machine learning/machine vision algorithms using edge computing
- model-based design reduces iterations and speeds path from concept → bench prototype → fielded system
- serves as outside expert for design review, expert witness or pre-money planning and prototyping (whether research grants or startups)
We work with public safety and transportation entities on their wireless infrastructure, whether in modeling upgrades, solving coverage problems or helping write RFPs and reviewing responses. As an independent voice of experience, we help police, fire, EMS, transit and other public agencies as they maintain and transition from legacy analog radio and data systems to broadband digital networks, including FirstNet. We help support agricultural operations from farmers to companies working with and for agricultural advancement as humankind struggles to feed more with less.