Alexie Pogue

Independent researcher developing a framework to understand how universities respond to critical incidents.

My Education

Education: San Diego Mesa Community College 2008-2010 (Associate’s degrees), University of California San Diego 2010-2013 (B.S. Chemical Engineering), University of California Los Angeles 2014 – 2024 (M.S. Mechanical Engineering 2016, Ph.D. Candidate 2018, Ph.D. conferred 2024).

The Basics

My writing is “homegrown” but I do use chatbots for formatting and some editing.

I’m a “first principles” thinker; likely because I’m a product of simple values, (statistically) zero indoctrination, and a lot of listening before forming an opinion.

The Turning Point

Engineering was the real turning point for me in critical thinking. I wasn’t a typical engineer growing up — simple mechanisms I saw every day were mysteries I assumed I’d never understand. But a course in digital control changed everything. It was hands-on and required me to implement theory on a robot I built myself. That was my first real introduction to robotics — I was amazed by how much I could do with so little background. I considered seriously pursuing the field so I joined a robotics lab, but it wasn’t smooth sailing from there.

Certain principles in engineering were lost on me. Mechanisms looked crude in form — the details and nuances of how they worked remained a mystery. I was frustrated, but I kept looking, hoping to see beyond the surface. The experience was like learning a foreign language — over time words that were just sounds began to have meaning and they held incredible power when they came together. This was just the beginning, but I learned more than I expected. I learned that by careful inspection, there is no element to a mechanism’s function that is mundane or can be taken for granted. Every component plays an important role, even if it’s small or seemingly simple (months on frictionless bearings or shoulder bolts at the behest of a more experienced human really drives that message home).

Later on in my education I learned that in the face of physics, intuition never meant much. To get anywhere with my work I had to abandon all previous assumptions and use only the tools allowed by physics. If I failed, which I often did, I couldn’t get mad (at physics?), and I couldn’t argue or manipulate. I had to persevere, and steadfastly try again all while listening and observing. I did not tell physics what to do and physics was never going to tell me what to do. I had to be patient, and listen. There were times when I would get frustrated, all my energy spent, ready to hammer the square peg into the round hole. Even then I learned I had to compose myself and go back to the fundamentals to overhaul my entire approach rather than exhaustively search for a solution using the same incorrect methods simply because I felt I was close to a solution.

The fundamentals (or first principles) were the only thing that mattered. They were objective truths. And while I built a method to obtain a solution based on assumptions I made from collecting data, none of the process beyond the fundamentals proved anything until the evidence presented itself. At the end of it all, I learned to be comfortable saying, this is what the data may be saying or this is what could be happening, but without x or y or z, I really can’t know. Because any time I’d forget that, physics would prove me wrong. I became comfortable knowing I might always be wrong, until the evidence presented itself. I knew I was “right” when the solution was reached — all the data from input to output followed mathematical theory. In robotics you would know, because the robot would actually do what you expected it to do rather than “blow up” (figuratively that is, a little controls lingo).

It was all really tough but it was worth it because looking back, robotics gave me a way of understanding the world I never thought possible. First I had to be able to see it, then I had to appreciate all its components; to interact with it I had to listen and be receptive to change, and to obtain what I wanted I had to always be learning and getting smarter; through it all and perhaps most importantly, I had to persevere.

The Takeaway

My graduate major field was called Systems and Controls. In essence it’s about:

  • Mapping how subsystems interact — modeling dependencies and interfaces so the whole system behaves predictably

  • Theorizing input–output behavior — what signals go in, how the system transforms or reacts to those signals, and what signals come out

  • Empirical testing — ensuring proper engagement with the environment under observation such that all inputs are correctly mapped to the proper outputs in practice

  • Closing the loop — sensing deviations and ensuring feedback control mechanisms keep the system within a desired range of behavior

In short: it’s the discipline of understanding how complex systems behave — whether those systems function by the rules of physics or the law, and creating control algorithms — often called “policies” — for making them behave desirably, even under uncertainty. If the system deviates due to a changing environment or disturbance such that it cannot achieve this behavior predictably, the control policy is incomplete.

The Future

I’m interested in data-driven policy. My research and publications will mainly focus on demonstrating how responsible data practices can improve our world.

My Interests

I love comedy, spy thrillers, poetry, and basketball. Would also love to get into some DIY projects if I ever have time.