I am a Ph.D. candidate (ABD) in Electrical Engineering at Boston University, where I also earned a Master of Science in Electrical Engineering (MSEE).
My primary research interests are in synthesizing developments from the image/signal processing and computer vision worlds with plasma physics / electromagnetic principles for exploration of natural phenomena in space and the near Earth environment.

I mentor and advise teams with interest in humanitarian projects using low energy wireless and computer vision technologies to open new educational, health, and general quality-of-life improvements to disadvantages populations around the world.

Going forward, I am interested in using my generalized technology expertise as a consultant for charitable foundations, government and public safety agencies, as well as startups and established corporations. That is, helping guide stakeholders to make better informed choices to improve public and charitable services through more efficient and effective use of technology, ranging from hardware efforts including embedded systems to software efforts including real-time machine vision and inverse theory algorithm implementation.

my Github:

Programming proficiency — defined as ability to architect cycle-efficient solutions using from-scratch and toolbox modules:

  • Python (Numpy, Scipy, Astropy, h5py, oct2py, etc.)
  • LabVIEW (Real-Time, FPGA)
  • MATLAB / Octave

Programming working knowledge — defined as ability to read/understand other’s code and make minor to moderate modifications:

  • IDL / GDL
  • Fortran
  • C++

Operating system proficiency — defined as ability to install/compile programs, add/remove kernel modules/drivers, fix minor to moderate system failures and deploy multi-year stable remote systems

  • Linux — Debian/Ubuntu and CentOS families of distros
  • Windows — 3.0 through 8.1
  • MS-DOS/FreeDOS

Operating system working knowledge — defined as ability to setup software, resolve minor problems

  • Mac OS
  • FreeBSD
  • AIX

I have substantial experience with the Raspberry Pi and BeagleBone Black singleboard ARM computers.
Previously, I had worked on developing a curriculum for junior-high school teachers to introduce their students to signal processing concepts. The tools I’m using for this include:

Hardware: The ubiquitous $20 RTL2832 USB 50MHz-2GHz receivers
Software: Python, Octave, GNU Radio

In July 2012 I did two sessions with sixth graders from Boston area schools. I demonstrated an RTL2832 receiver in GNU Radio with broadcast FM stations (88-108MHz) and NOAA weather broadcasts on 162.55MHz. We discussed how humans transmit and receive mechanical sound waves (vocal tract –> auditory system).
Next, we discussed how sounds are converted from mechanical waves to electrical waves and vice versa — simple telephone circuit.
Finally, I described at a very high level how voice is upconverted to RF and downconverted to send information across town or the solar system and beyond.


I also enjoy Amateur Radio, I hold the Extra Class license. I enjoy FM repeaters on the 33cm (900MHz) band, as well as voice/digital/CW for all lower frequencies, especially JT65 and WSPR. I have 2m/70cm satellite equipment as well as receivers covering DC through 18GHz. ADS-B listening via the ubiquitous $20 USB receivers. When operating digital modes I exclusively upload to LoTW, so if there is a missing QSL you are needing let me know, maybe I missed an upload.