Michael Hirsch Ph.D.

You’ve probably used projects I’ve contributed code to, or transacted (at least indirectly) with companies that use my IP. I consult for companies, institutions and organizations of all sizes in complete full-stack system design including:

Remote sensing: radar / optical

  • Precision / passive indoor radar / optical remote sensing
  • Broadband wireless systems including: broadcast, public safety, two-way voice/data radio, UAS, satellite

Performance & schedule oriented Software Engineering

We focus on scientific computing for:

  • endpoint / edge computing: reduce data at the sensor
  • scalable HPC algorithms

Code contributions

I have contributed code to:

I have published over 110 geoscience and aerospace programs, including 28 packages listed at http://heliopython.org/. My work blends data science with full-stack hardware development, using data science with radar, GNSS, optical and other remote sensing techniques.

  • 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

Professor Hirsch uses comprehensive model-based engineering frameworks to 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)

As a governmental example, 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, Michael helps 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 work with agricultural operations from farmers to companies working with and for agricultural advancement as humankind struggles to feed more with less.


Mathematics Genealogy Project entry

PhD in Electrical Engineering

Michael developed novel ionospheric remote sensing system techniques via optical tomography, radar, and radio instruments. The kickoff to Michael’s doctoral research was an AFOSR-funded deployment to Greenland on multiscale (temporal and spatial) features in the aurora. The lessons learned from this system built confidence in the field deployment of a multi-site auroral tomography system to the Poker Flat Research Range near Fairbanks, Alaska.


Michael earned the Master of Science in Electrical Engineering degree from Boston University in the Space Physics: Remote Sensing & Instrumentation track.

BSEE (High Honors)

My undergrad ECE accomplishments include: