I develop performant solutions to complex scientific and industrial problems. I am currently a product engineer at Radar, where I work on search systems, geocoding, machine learning, and some mathematical work to better interface between the digital and physical worlds.

I recently graduated from the University of Waterloo with a BMath in Computer Science and Computational Mathematics.

My previous experience has largely revolved around data-intensive embedded systems, like software-defined radios for wireless communication. I also have a number of projects where I worked with digital signal processing, such as a low-cost solution for performing turbulent flow analysis using ultrasonic sensors, and a binaural audio localizer.

I am also interested in applied research, both in academia:

• I studied the efficacy of large language models (LLMs) in performing graph clustering tasks at OpAL Lab.
• I worked in David Del Rey Fernandez’s group, where I investigated the possibility of solving certain classes of PDEs using spiking neural networks.
• I worked with Sri Namachchivaya to investigate non-parametric methods for performing quickest change detection on high-dimensional datasets with unknown pre- and post-change distributions.

and in industry:

• I iterated on existing algorithms capable of locating an RF-emitting device using TDoA with statistical methods, and
• I implemented novel methods for performing low-cost BLE emitter localization using machine learning methods.