Jonathan Jones
Senior Applied Scientist at Amazon
Virginia, United States
Summary
👤
Senior🎓
Top SchoolJonathan Jones is a Senior Applied Scientist with 11 years of experience applying structured prediction and machine learning to real-world perception problems, now leading applied research at Amazon. He specializes in time-series and multi-modal signal processing, with deep expertise in fine-grained activity recognition and automatic speech recognition developed through a Ph.D. in electrical engineering from Johns Hopkins. Jonathan has a strong track record of building experimental engineering stacks and data-collection platforms—having led multi-modal studies that produced and labeled hundreds of videos combining RGB-D, IMU, and gaze signals. His work spans probabilistic and neural methods, sim-to-real transfer, and zero-shot temporally-structured action recognition, translating research into production-focused solutions. Based in Virginia, he blends rigorous academic research with hands-on implementation skills in signal-processing applications across healthcare, surgery, and human spatial cognition domains.
11 years of coding experience
13 years of employment as a software developer
Johns Hopkins UniversityBachelor's Degree, Engineering Physics, Bachelor's Degree, Engineering Physics at Eastern Illinois UniversityUniversity of Illinois Urbana-Champaign
English
Github Skills (3)
prediction3
struct2
pytorch1
Programming languages (3)
Github contributions (5)
jd-jones/kinemparse
May 2020 - Jul 2021
Parsing kinematic structures using action recognition
Contributions:2 PRs, 153 pushes, 3 branches in 1 year 2 months
recognitionaction-recognitionparsing
SecondPlain/misc
Nov 2014 - Jun 2017
Contributions:17 commits, 13 pushes in 2 years 7 months
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