An IoT-enabled, fire detection and response system that reduces fire detection and emergency response times to stove/cooking fires by 17%, drastically cutting down on ~$3B in property damages. Stakeholders include multifamily housing companies (primary customers), smart home security companies, insurance companies, senior living communities, and fire departments (state governments).

Developed signal processing algorithms in C and in VHDL for FPGAs as part of a project exploring research problems in reconfigurable computing. In particular, I investigated alternative designs for implementing a neural network based image classifier; this included evaluating multiple ways of configuring the FPGA to perform per-pixel classification using both bit-serial and parallel adders and multipliers. This work sparked my interest in efficient parallel computing.

My responsibilities include developing and researching new ideas in computer architecture and code optimization, teaching and developing undergraduate and graduate courses, curriculum planning and innovation, advising graduate and undergraduate students, and supporting the research community and the public through volunteer service and outreach.

My responsibilities include developing and researching new ideas in computer architecture and code optimization, teaching and developing undergraduate and graduate courses, curriculum planning and innovation, advising graduate and undergraduate students, and supporting the research community and the public through volunteer service and outreach.

My responsibilities include developing and researching new ideas in computer architecture and code optimization, teaching and developing undergraduate and graduate courses, curriculum planning and innovation, advising graduate and undergraduate students, and supporting the research community and the public through volunteer service and outreach.