Bellevue, Washington, United States
I’m not exactly a “machine learning person”, but I know how to hang out with them. I’ve led applied machine learning projects in conservation technology, gesture recognition, brain-computer interfaces, and computer music. A wise AI guru once told me that “machine learning is easy, feature selection is hard”. Words to live by; many of my contributions in this space have focused on problem formulation and feature exploration for applying ML to interactive systems. I’m not exactly an “environmental scientist“, but I know how to hang out with them. I am researcher in the AI for Nature and Society program at Google, where I use computer vision to accelerate biodiversity surveys (i.e., to save ecologists time). Sometimes I move lots of remote sensing bits around. I’m not exactly an “electrical engineer” (the “building stuff” kind or the “signal processing” kind), but I know how to hang out with them (both kinds). I’ve led hardware prototyping and signal processing projects in natural input, mobile computing, and computer music. I get sad if I go more than a few weeks without soldering anything. I’m not exactly a “doctor”, but I know how to hang out with them. My undergraduate degree was in neurobiology, and since then I’ve worked closely with clinicians, leading projects in surgical simulation, neural interfaces, patient-friendly medical informatics, and mobile health sensing. Home page: http://dmorris.net CV: http://dmorris.net/cv
I build AI tools that help conservation scientists spend less time doing boring things. About 50% of my universe is focused on wildlife conservation, the other 50% is focused on remote sensing for forest monitoring, particularly urban forestry.
For about the first 33.3% of my time at Microsoft, I worked on gesture-y, sensor-y, signal-processing-y stuff for user interfaces and creativity support, then the next ~33.3% of my time at MSFT was on health technology (particularly cardiovascular sensing), then I had a mid-life crisis and decided it was sustainability or bust, so the last ~33.3% of my time at Microsoft was spent on remote sensing infrastructure and AI tools for wildlife conservation.
PhD research on haptics, physical simulation, and virtual environments for medical training.
Consulting engineer; built a hardware and software experimental platform for embedded neural prosthetic devices.
Worked on an infrastructure for haptic rendering and haptic device interaction; developed computer vision prototypes for real-time processing of medical images.