Update about.md

about.md

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 <!-- - [Here is my CV for linear thinkers: available upon request or see what I'm up to here](https://kammitama5.github.io/Tuesday-October-8th/). -->
 - [Here is my CV for linear thinkers](https://github.com/kammitama5/kammitama5.github.io/blob/master/images1/Reeee_Krystal_Maughan_CV_20_2023.pdf) and you can see what I'm up to [here i.e. "News"](https://kammitama5.github.io/Tuesday-October-8th/).
 - I am currently working on mathematical cryptography research, often as it relates to quantum computing. I regularly work at the intersection of the Number Theory community and the Quantum Computing community. Currently I am working on [post-quantum supersingular isogeny-based cryptography](https://en.wikipedia.org/wiki/Supersingular_isogeny_graph), advised by two professors; one in Pure Mathematics and the other in Computer Science (while being held hostage by the Pure Maths department at my University, much to my delight!). I am also working on other adjacent topics, too, such as error-correcting codes, or more broadly, computational arithmetic geometry / number theory.
-- You will find me mostly in the Pure Maths lab. I'm working with several mathematicians on projects at the moment, as well as learning Lean 3 (Summer 23). In the past, I've also done research at the intersection of Provable Fairness, Differential Privacy / Trustworthy AI (having produced 4 papers, 2 of which we presented at peer-reviewed workshops), but I am not an expert in state-of-the-art AI technologies involving LLMs or Transformers (Sorry!). I do occasional DEI things for the AI community, but I am not really affiliated with them in terms of serious research (sometimes someone will ask me to collaborate, but it's not my main area of research), and will fall asleep in most AI lectures. You can say my interest in Machine Learning was because, in general, I care about critical, trusted systems moreso than aiming for tell-tale signs of improved iterative accuracy.
+- You will find me mostly in the Pure Maths lab. I'm working with several mathematicians on projects at the moment, as well as learning Lean 3 (Summer 23). In the past, I've also done research at the intersection of Provable Fairness, Differential Privacy / Trustworthy AI (having produced 4 papers, 2 of which we presented at peer-reviewed workshops), but I am not an expert in state-of-the-art AI technologies involving LLMs or Transformers (Sorry!). I do occasional DEI things for the AI community, but I am not really affiliated with them in terms of serious research (sometimes someone will ask me to collaborate, but it's not my main area of research), and will fall asleep in most AI lectures. You can say my interest in Machine Learning in general intersects with critical, trusted systems moreso than aiming for tell-tale signs of improved iterative accuracy or data-crunching.
 <!-- - [Here is my (longer and more realistic) CV / Curriculum Vitae](https://github.com/kammitama5/kammitama5.github.io/blob/master/images1/Krystal_Maughan_CV_4_11_2023a.pdf).  -->
 <!-- - I've done some Machine Learning in the past, and it's cool, but I honestly enjoy Computational Pure Mathematics research more (and there are lots of students who do a rather great job at this AI / Deep Learning stuff i.e. it's their passion. I didn't like the "hand-waviness" and "one-notey" aspects of the field, although learning about data is a good abstraction for learning about noise, patterns, entropy and probabilistic methods). I discovered this a year or two into my PhD (i.e. that super duper applied stuff was not really my thing) and switched (it happens), although I'm always happy to give a very "high-level" overview of past work (based on memory or a quick review). Actually, I've [spoken about how I feel about data science things before](https://kammitama5.github.io/Tuesday-February-27th/) (circa 2018). I will talk your ears off about what I'm into now, though, and I want to stress that this is totally a normal thing in a PhD (when not under duress; the goal of a PhD is to learn how to be a researcher and find your research peer community), and you do your best work in the [things you love](https://www.youtube.com/watch?v=5dXulZVstbY) working on, with proper [support](https://www.youtube.com/watch?v=KQTqbNB7Xb0) and room to grow! For me, it was 100% the Pure Mathematics community! -->
 - I am not taking any more coursework (unless it's a sit-in occasionally type-class / seminar). I did take a 1.5-ish year-long mini-Master's type format of Pure Maths classes, for a solid foundation on Elliptic Curves, Abstract Algebra, Graph Theory and Isogenies once I settled on what I wanted to do. However, I have been a part of the Number Theory community [since](https://kammitama5.github.io/images/msrismall/msri.png) [2018](https://www.msri.org/ckeditor_assets/pictures/1197/content_IMG_2239-edited.jpg). I am going to become an computational pure mathematics researcher and to continue research in this direction after my PhD, wherever there are opportunities to do so. I love everything about the Pure Mathematics Community! (specifically in Arithmetic Geometry / Number Theory and Algebraic Graph Theory) and I love mathematical cryptography. I also really like the quantum community (so far), which is newer for me.