About

Sam Stone
^{BS Electrical Engineering, Binghamton University 2019}

I am an Electrical Engineer interested in applying signal processing and machine learning to solve problems in embedded systems.

As an engineer, I work on systems engineering/architecture, signal processing, and machine learning (mainly deep learning) at SRC. As an intern, I worked in product design, specifically with injection molded products, at Tessy Plastics and aerospace-grade electronics at Collins Aerospace. I have filed for a number of patent-pending inventions related specifically to solving problems for various customers. My coursework at Binghamton University was focused on signal processing, including some Master’s classes.

Recently, I’ve been working more and more on Radar Signal Processing and Machine learning. I’ve published several papers on Radar Signal Processing at Tri-Service Radar Symposium. I presented a paper on Deep Learning and published an article on connected, autonomous cars.

• Stone, S., Zhang, A., Hartle, J., Aklian, A. (2022). Extending the Range of micro-Doppler Rotor Paramter Estimation. In Proceedings of the 68th MSS Tri-Service Radar Symposium.
• Stone, S., & Spector, E. (2021, October). Deep Neural Network for Multi-Pitch Estimation Using Weighted Cross Entropy Loss. In 2021 IEEE Western New York Image and Signal Processing Workshop (WNYISPW) (pp. 1-3). IEEE.
• Stone, S., Davis, E., Nashed, K., (2021). UAS Rotor Length and Multiple Rotor RPM Estimation. In Proceedings of the 67th MSS Tri-Service Radar Symposium.
• Stone, S. (2019). Connected, Autonomous Cars: Passive Pothole Patrollers. IEEE Potentials, 39(1), 52-58.

I am very involved in the IEEE and I am currently the Treasurer and Young Professionals Chair for the Syracuse IEEE Section.