(rot13 "qhapnaajvyxvr@tznvy.pbz")
(rot13 "synzvajnyehf@zngevk.bet")
(rot13 "SynzvaJnyehf@yvoren.pung")
My name is Duncan. I am 22, and have lived most of my life in rural Arkansas. I graduated in 2023 from LSU, cum laude, with dual degrees in math and physics, and have at various times been employed as a dishwasher, maintainence guy, tutor, data science intern, embedded developer, and research scientist. I am currently an algorithm and model development, design, and optimization specialist in an engineering test team under Northrop-Grumman's naval aviation divison.
I've planned on studying physics since I was 5. I enjoy studying almost anything that's natural and not alive, and all my other interests are largely subsidiary to this. I like the areas where physics intersects with math, particularly when it does so in mathematically-exciting ways. I also loved my classes about emergent phenomena: thermodynamic, statistical, and condensed-matter physics. I spent the latter half of my time working under Jeff Chancellor's Space Radiation Transport and Applied Nuclear Physics (SpaRTAN Physics) research group, doing embedded design of radiation detectors and writing improvements for Monte Carlo transport codes.
I view math primarily as a tool for physical science and inquiry in general. Accordingly, I want to get to the frontier of the discipline as fast as possible: I probably will need to make new tools. The only domain that seems not to have borne much practical fruit, except as a target for developing "real" tools, is number theory. I particularly like topology/geometry and algebra, and would much prefer if analysis and discrete math borrowed as many of its tools and methods as possible.
Fundamentally, computer science is a branch of mathematics. I am interested in ways to compute as abstractly, efficiently, securely, and correctly as possible. As such, I enjoy functional and logic programming languages which succeed by representing computation in maximally mathematical form, using the abstractions that have been most useful. I like writing things in Haskell, Lisp, and Coq. I've done extensive work with Python, C, and Fortran. I didn't enjoy those (although Fortran was much better than expected—prefered to C). Software that is not Free might as well not be software at all. I use GNU Emacs for almost everything.
For all of the above, you have to build real, material things. Physical science requires the construction of detectors, accelerators, and whatnot; mathematics needs blackboards, chalk, printing presses, and a society to ignore; and computation needs computers and network technology. This is predominantly electrical work—designing silicon, circuits, wire protocols, radios, and so on. I've done fair bit of this. However, that electrical work is predicated on things like power generation, structures to protect the electronics, etc. So, I aspire to learn "real" CAD at some point, and understand these things too.
There simply is not enough time in a person's life for autarkic, first-principles generation of every part of every thing one's primary interests depend on. Nevertheless, understanding of those parts is important, even critical. A general understanding of human action, particularly of catallactic action, is understanding how to outsource this task to broader society. Austrian economics helps one act in the world—explicating the function of social institutions in a way no other approach even approximates. The critical error of conventional economics, as with many social- and life-science disciplines, is thoughtless application of methods of physical science, through the positivist telephone, without careful consideration of whether the philosophical conditions on which the correctness of those methods depend are present. These fail spectacularly in analysis of action: the wants and desires of humans are not immutable, intersubjective quantities. However, Austrian economists tend to thoughtlessly reject methodological precision due to superficial association with unrelated fallacy. I have a longstanding pet project to ground mathematically, in the truest sense, the reasoning of Mises, Rothbard, and Long.
All of this again rests on some foundational definitions and propositions about the nature of truth, reason, mind, beauty, and morality. Very recently, I've become acutely interested in these foundations, particularly the philosophy of mathematics and science. I am currently most convinced by the American pragmatists and their post-positivist heirs: empiricist, fallibilist, phenomenalist anti-skeptics. I see no essential distinction between practice, philosophy, teaching, and history of science (and mathematics). Anything can be questioned at any time for any reason. And many scientific revolutions are the spoils of such foundational assaults.
I don't know much about linguistics, aesthetics/art, or psychology. These are similarly foundational, as philosophy can only be communicated through language, must be boostrapped by the beautiful, and must be done by the human mind. I would like to learn these things, but am not taking active measures in any capacity to do so at the moment.
I dislike: OOP, Javascript, the Intel Management Engine, almost all TV and movies, number theory, drugs, the War on Drugs, rhetorical appeal to authority, the Federal Reserve System, occupational licensure, and collectivism.
I listen to (.*?)core, rock and metal from the 60s-80s, microtonal and avant-garde jazz and classical, and old standards. I all-too-seldom go outside: when I remember I enjoy it, I resistance train, hike (spin|fly) fish, (show|water) ski, climb, and mountaineer. I read high fantasy and sci-fi obsessively for about 10 yeasr, and occasionally go back through th Tolkein, Jordan, and Sanderson novels I love. I watch a lot of football and baseball; my Tigers picked up a ring in each while I was there.