A little more about me

After getting my PhD in mathematics (specializing in numerical optimization) in 2011, I started down the machine learning/data science career path. I had just started working for a small engineering company in San Diego, Elintrix, and my first project involved developing support vector machine (SVM) powered chemical sensing systems. Before deep learning and large language models took over the AI world, SVMs were considered pretty cutting-edge.

Once that project ended, we started taking on more work in digital communications. Made sense; that is one of Elintrix’s core areas of expertise. At the time, I knew next to nothing about any of that. My knowlege didn’t extend beyond what you’d learn in a first-year physics course. Fortunately, I must have given off a tenaciousness vibe, because over the course of several years, my boss trained me to be a design engineer.

It’s been a completely unexpected, and fascinating, journey. Over the course of my career, I’ve had the privilege of working on nearly every aspect of the electrical engineering workflow: analog circuit design, PCB schematic capture and layout, embedded platform development, FPGA design, RF simulations, board rework, etc. Heck, I’ve even gotten to install gear in an electrical substation.

Working on a small development team, in a technically demanding area has taught me how to effectively manage complexity. The amount of competing interests, constraints, and technical challenges tied to a communications design can be overwhelming. Navigating the solution space, on a tight budget, requires clever problem solving strategies based on the simple principles of staying nimble and being well-prepared. The more time invested in understanding the intricacies of your craft, the more options available when you hit the inevitable snag.