Marika Schubert

Marika Schubert is a research scientist in the Advanced Computing Lab in the AI Division at CMU SEI. Schubert's research and engineering activities have focused on implementing and benchmarking AI algorithms on various types and scales of hardware. She is currently the PI of Stereo Radar Imaging for Dusty and Foggy Environments (STRIDE) and is supporting DARPA Scalable Analog Neural-networks (ScAN). Her graduate research explored deep-learning benchmarks for embedded systems. 

Before joining SEI, Schubert worked in a variety of engineering roles at NASA Johnson Space Center (JSC), primarily in audio systems (hardware and software) for crewed vehicles. Her prior experience additionally spans several different engineering teams at NASA JSC, writing software for long-duration weather balloons, and performing fluid properties research in a lab studying solitary traveling waves.

Schubert received her bachelor's degrees in electrical engineering and applied mathematics from University of Colorado Boulder and her master's and Ph.D. in electrical and computer engineering from University of Pittsburgh as part of the Space, High-Performance, and Resilient Computing (SHREC) lab.