About Me

beach

  • I’m a researcher, aspiring boffin, mango and cocoa picker. Creative and analytical thinker; I ran away from Hollywood (working for R&D facilities that facilitated technical innovation for the movie industry) after a little more than a decade of working in that industry, and into science research; research seems to be a great blend of creativity, intellectual and analytical thinking, which suits me! Also note: my background before heading to the United States was in Physics, Maths and Art, and so, I had to learn everything about filmmaking from the ground up upon arriving in the United States, had never developed a single black and white roll of film before, in a class full of students who had since high school (1a) spent my last semester as an extramural student at Cornell (1b), and graduated at the top of my class in Undergrad.
  • Here is my CV for linear thinkers or here and you can see what I’m up to here i.e. “News”.
  • 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 (QC) community, which involves anything from working with post-quantum cryptography, quantum computational complexity, or general topics in arithmetic geometry / algebraic graph theory . Currently I am working on mathematical cryptography as it relates to quantum computing, co-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 classical error-correcting codes, quantum algorithms, and more broadly, computational arithmetic geometry / number theory and some graph theory projects relating to quantum (2), and in my spare time, I continue a budding love interest in building SAT solvers in Lean.
  • You may have noticed that I have some history in AI. “An AI person!”, you might say (“Isn’t everyone these days?”). Until I publish in Mathematics (soon!), I am aware that this is what my profile shows because the cycle for publishing in AI is much shorter then my current area of research. I’d like to say that it would have been very easy (and quite lucrative; I could have had a glossy photo of myself with a link to my Ted Talk instead of that beach photo from Marin County!) for me to continue on a path with Generative AI, GPT, Transformers, etc, but I am more passionate about Pure Mathematics research, and its intersection with QC. I also really love the communities within Pure Mathematics and Quantum Computing and have felt that they invested in my success and in my being a good researcher in a way that I didn’t think I was receiving via the AI community, which has issues with “researcher tokenism”, as I like to call it (i.e. all researchers are not equal but also hey, we need “someone like you” today for our brochure / panel. In short, many aspects felt pretty exploitive (e.g. having a first-time submitter review papers with little to no mentorship because of the large number of submissions to conferences, so you want the labour of junior researchers without giving them much in return; in some cases not even acknowledging their work!), which is not surprising, given the complaints of the effects of these technologies by people who do not make them). So I seriously stopped coding any AI models around 2020, and I can hack things together, but I am really rusty. In 2021 and 2022, I cut my teeth learning Pure Mathematics grad school foundational classes (e.g. I took Abstract Algebra I, III in the same semester and it kicked my butt, as well as Graph Theory and Spectral Graph Theory at the same time another semester!), and around that time, I started working on some projects, only seriously digging in around Fall 2022 (Pure Maths research can be very intidimidating because in comparison to AI, you’re not “starting with a dataset” typically. And it is a slower, iterative process!). All is not lost; my background in AI has served me well in the Pure Maths community, too, but I enjoy problems at the intersection of Pure Maths and QC primarily very much! I work mainly with Sage these days, LaTeX, and mechanical pencils on paper and most recently, Lean. That being said, I’ve been flooded with kindness by the QC and Pure Maths communities, and so I am really very busy working with several groups on several projects (about 8-10 in 2023 alone which are wip)! So much so that I’ve missed recruitment emails that were sent nine months ago in 2023!
  • You will find me mostly in the Pure Maths lab; I was given a desk since I am working with professors in Graph Theory and Number Theory. I’m working with several mathematicians on projects at the moment (and most recently, some physicists!), as well as learning Lean 3 (Summer 23) with a logician and making SAT solvers (a recent fascination of mine that stemmed from a research internship I did in 2022!). I’ve really enjoyed the jump into Quantum, but I do realize that I also have a lot to learn (and that I have to work my way up, while say, continuing in AI would mean that I would have had my pick in opportunities to some extent, and certainly would have been finished with grad school by now!). I don’t see this as a disadvantage (see (1) and (2) about my background), as if you’ve been reading this far, you know that by definition one of my strengths is working my way up to the top of any discipline / area of interest I set my mind towards, and it is, in fact, expected of many long-term career researchers (the criteria is often “is the question interesting” rather than “this is a thing in my field”, and one learns to learn in research). Meanwhile, my appetite for learning more Pure Mathematics and my core community in general is that of the Pure Mathematics community (in particular, the Number Theory community), and I would say at this point I think more like a Mathematician, but I was told this in past internships (even before grad school!), and have a tendency to get hired by Mathematicians (so if that mindset is what your team might enjoy, it’s something to consider!). What this means is also that I find the kinds of problems that mathematicians would enjoy to be enjoyable, too (that’s generally a good metric to also figure out where one “belongs” in research). I invest a lot of time and share resources within any community that is my core, as I think it’s an important part of sustaining its longevity.
  • 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 2018. I am going to become an computational 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.
  • When I (sigh) have to code, my current tools are anything from Python, Matlab, SageMaths, Lean3, Haskell, Rust, LaTeX, a calculator, mechanical pencils, paper, and most recently, chalk. I am a Systems thinker. It would be amazing to defend my thesis by iPad but I may end up having to TeX it.
  • My grad school Pure Maths peers have described me as having “Hermione energy”, which I’ll gladly accept.
  • I also recently joined Mastodon and BlueSky. You can find me on Mathstodon at: kammitama@mathstodon.xyz. I joined the Maths one because that’s mostly what I’ve been hanging out around these days. Also, I found this particular one while looking up something in Combinatorics, and figured it would be a good fit for me. I probably won’t use it much, except to read, as I’m pretty busy.
  • I’ve been (i) an extramural undergraduate student at Cornell University, (ii) a visiting PhD student at UC Berkeley, and (iii) a faculty member (through a PhD Teaching programme for two weeks) at UT Austin!
  • I have also audited graduate classes at Stanford University (Information Theory and Scalability of Blockchain in 2021), UC Berkeley (Coding Theory 2024) and have taken a graduate class (for transfer credit) at the University of Waterloo (Algebraic Graph Theory and Quantum Computing (2024)).
  • Also a book junkie. Love Haskell, Hackerspaces, puzzles, making and sailing.

What’s Unique about me

  • I have the unique perspective of being an immigrant (and green card holder), having been through many pipelines of school, having work experience and having lived in locations and groups where my representation was quite scarce (both in terms of knowledge, having work experience and demographics). My career has been in a breadth of typically niche, proprietary knowledge/ technologies (which is a nice way of saying I know a lot about things that are absolutely useless but I have great stories!). My first job out of undergrad involved working with high-speed cameras used for crash-testing (think automotive, electrical, and aerospace industries), defense and movies, and my job after that involved working with (testing, troubleshooting) high-speed lights which used long-arc xenon / plasma technology (my job involved using welder’s glasses, screwdrivers and an ohmmeter, as well as working with high voltage systems (240V, 480V) daily), both of which are fairly esoteric. This second job was at an R&D facility where manufacturing was done in-house (I worked next to and with a machine shop daily). This means I understand manufacturing, risk and critical industries. (I was also educated with a British-colonial science curriculum meant to prepare engineers for the petro-chemical industry in my home country and studied 18 years of Physics, Art and Mathematics before undergrad.)
  • Also fun fact: my second job shared a space with an exoskeleton startup that was later sold, started by an innovation from the film / camera industry that was adapted for oil rigging and other industries where workers spend long hours in one position in cramped spaces, and each unit was assembled in-house.
  • I would describe myself as intellectually curious. I’ve taken classes in sculpting, drafting, 3D modelling (I did hand-drafting on vellum, know how to draw in 2D-CAD and love Rhino hobby modelling), woodworking, electronics (low voltage/high-voltage/PCB-milling), welding, machining, and robotics (I also taught a robotics class weekly for about a year). I’ve sailed from MDR to Catalina Island, and to Newport beach. I like Haskell and programming languages in general, which I did not learn formally in school. I also worked in manufacturing for a couple startups, and understand the process of manufacturing real-world products (generating a BOM, 3-d modelling, ordering parts, bidding with client, etc). I’ve been told recently by a mentor that I may, in fact, actually be a theoretician, so take that as you will. I love lectures with chalk on blackboards. I believe that life experience/learning from failure is important.
  • I see programming as a tool, but these days, I spend a lot more time writing (badly-written, but improving and learning!) proofs, improving my mathematical clarity in writing in general, and learning Lean. I believe that coming from a different perspective is important in solving new problems in research, and I enjoy collaborating with people who are from various backgounds in research.

2024

  • I will be a visiting PhD scholar at the Simons Institute for the Theory of Computing in UC Berkeley, California!
  • I will be there for the “Quantum Algorithms, Complexity and Fault Tolerance” workshop via:
    • the Quantum Coding workshop
    • the Error-Correcting Codes Bootcamp, for the duration of a month, courtesy of the Institute!

Update (as of 2019)

  • I began focusing on Supersingular Isogeny-based Cryptography research in Winter 2020. I absolutely love it, and I am working on progress with my two advisors (I also attended a summer workshop on Isogeny Based Cryptography in 2020, and another affiliated workshop on post-quantum networks, which focused on implementation into current non-post-quantum secure protocols). In the past, I have done research on Provable Fairness and Differential Privacy, too. I have also TA-ed for Data Privacy coursework (Python), a Programming for Engineers Matlab course (Matlab), a Compilers course in Haskell and another CS course. For my oral quals, the agenda is: Quantum Computing and Mathematical Cryptography, Elliptic Curves (passed!) and Graph Theory (yes, I convinced the department to let me take all Maths topics!)!
  • I do not work directly with Quantum Computers; post-quantum means “we assume that we have quantum computers; will this cryptography be subject to attacks where a quantum computer can break it?”. The cryptography with respect to this should have hardness properties to prevent this. This meant that I had to know just enough about Quantum Computing (algorithms, how it works, what it can and cannot do) to write a dissertation with a solid introduction on Quantum Computing in general, and how it relates to (post-quantum) isogeny-based cryptography (and this is still my primary goal). However, I got sucked into learning more about Quantum Computing because of (1) the Quantum Computing community (2) I noticed that there were not a lot of people with my academic background / interests at all at communal events …and now I have been working on things directly related to understanding how quantum computing works, specifically with intersections that use my backgrounds in Pure Mathematics, and I believe that this has enriched understanding of my interests (cryptography, Pure Maths) in this space. This has taken me into working on projects that have been on quantum algorithmic complexity, in particular, relating to work at the intersection of Algebraic / Spectral Graph Theory and Quantum Computing Complexity, and how that affects things like our assumptions on post-quantum cryptography. In short, I’m learning a lot in both Pure Mathematics and Quantum.
  • I have been forbidden from taking any more classes (for now) by “some professor(s)” who do Algebraic Graph Theory research :) In terms of coursework, I’ve taken Post-Quantum Mathematical Cryptography (Maths department), Data Privacy (CS), Secure and Distributed Computation (CS), Machine Learning (CS), Abstract Algebra I: Group Theory (Maths) and Abstract Algebra III : Groups, Fields, some Ring and Galois Theory (Maths: focused on preparing Maths PhD students for Quals), Abstract Algebra IV A: Ring and Module Theory (Maths), along with a Random Probabilistic Graphs class (Maths), Algebra IV C: Elliptic Curves and Modular Forms (Maths), and sat in on an Elementary Number Theory course (Maths). I also have taken Combinatorical Graph Theory (Maths), Spectral Graph Theory (Maths), Category Theory, and self-learning (Set Point) Topology (Maths), Matroids (Maths), while sitting in on the Theory of Algebraic Differential Equations and a Matroids and Polytopes class because why not. I’m also learning a bit of Model Theory, too, because sometimes Pure Maths professors reach out to me to learn things because of my enthusiasm and passion for the subject! Basically, if there is “Abstract anything”, you will find me there.
  • Some other things along the way I am learning (not for research) are Real Analysis, Ramsey Theory, HDX and Expander Graphs, and Extremal Graph Theory, through my awesome professors in my Pure Maths department who have been quite patient with me!
  • I have also participated in Qiskit summer workshop (2021), two Quantum Computing book clubs (2022 and 2023), a Quantum Field Theory book club (2023), and in 2023 participated in two quantum computing summer schools (PCMI and SoQ) and a Quantum hackathon. The summer schools focused on (i) quantum information theory, quantum algorithms and complexity (and the quantum advantage), quantum learning theory, and cryptography and error-correcting codes. I also participated in 2 quantum formalism courses (one of which involved theorem proving in Lean, and the second which is about mathematician foundation for quantum hardware formalism), and joined a group working on community in quantum resource estimation (something I’m newly learning about in 2023) I’m also taking a class in Algebraic Graph Theory and Quantum (2024) at another institution that has a stronger Quantum Computing programme (my institution currently offers no such classes in their Physics department, so I’ve been doing much of this legwork externally) and visiting the Simons Institute to learn more about Quantum Coding and Error-Correcting Codes (2024).
  • Breakthroughs: After attending summer schools and receiving my first Fellowship for (and attending) SQuInT 2023, we had our first abstract accepted at QIP 2024, and I was invited as a visiting researcher to the Simons Institute in Berkeley (with funding) for their Quantum Fault Tolerance workshop and Error-Correcting Codes bootcamp! I’m very thankful for all the people who have supported my journey in this space.
  • Q: I am a recruiter / person (??) and I have an opportunity.
    • A: I’m a bit crestfallen by my time in industry during my PhD, and exhausted (but I don’t regret it; I also wish that companies would rethink the three months to four months model for hiring students specifically in research, as projects are often rushed to facilitate this time frame, when in academic labs something like a semester in length is the minimum time one would expect to complete a project). Specifically, my experiences weren’t really great, particularly the capacity and degree of mentorship and imaginative scope of projects; coincidentally, I decided to pursue grad school because I found a lack of quality mentorship in the direction I was headed before grad school, too (in industry), and have strong thoughts on this topic wrt the tech industry, hierarchy and promotion aka “levels”; IMO in industry very “technical” people who are weak on leadership skills can be promoted based on seniority, fumbling along as they go. This can happen in Academia, too, but the structure of the PhD journey means that you are by definition learning to lead and mentor others, on some level, very early on (either by TA-ing, mentoring undergrads, and there is more incentive for doing this properly i.e. it is rewarded). At this time, I am punting to just do a postdoc somehow after I complete my PhD or become a cab driver and continue to work on research (as someone who spent a fair amount of time in a high-risk, high reward space, interesting problems and good collaborators motivate me most), but maybe there is a research opportunity or collaboration that might bring us both joy; I’m open to that.
  • Things that will make me run screaming from most internships: arrogance (why am I here if you know everything?), top-down hierarchy, exclusion (I could be in a Maths or Quantum summer camp instead, or working on research). I generally prefer to work in “no-jerks” or “minimal jerks” environments.

How Pure Maths research can be different from Computer Science aka where are your ten papers?

  • In my experience, compared to my previous research focus, this topic takes a bit more time to produce a paper. I am okay with that; I like how papers in my present discipline are written. I am still a Computer Science PhD student…I think…(for now). Please stop asking me if “I’m sure”. You’re not helping :)

More Updates…

  • You can see a bit of my so far (quite busy) life in a blog post here. There is still much time in the year to go! I love working hard and pushing myself, while helping others to reach their fullest potential!

More Information

Ravenclaw. Started out in New York, mostly in California, but get around to the other states, too.

Trinidad -> New York -> California -> Vermont -> ?

Other

Groups I’m in

Open Source

  • I’ve worked quite a bit on open source via programmes:
    • Haskell.org for Google Summer of Code (GSOC) (2018)
    • Mozilla’s Rust Reach (2018)
    • SageMaths (104: Arithmetic Dynamics library) (2019)
    • Microsoft Reinforcement Learning Open Source Fest (RLOS) (2021)
    • Summer of Bitcoin (2022)
    • LMFDB (via LUCANT) (2023) (just 1 pull-request fixing some LaTeX!)
  • I’m currently very interested in contributing to the Quantum Open Source eco-system and the Pure Maths open source eco-systems, so if you’re in these communities, you’ll probably find me there!

Books I’m currently reading

  • What I’m reading: Books, papers in the future (currently on a GH repo)
  • Current favourite shows: Silent Witness, Poirot, Industry, Suits, Billions (I’m seeing a trend), 48 hours.
  • Thanks to my parents: Poirot, Silent Witness, Inspector Morse, Midsomer Murders, Wycliffe, New Tricks, Vera, Miss Marple…(basically any British (Medical) Detective show) etc.

Awesome other things I used to enjoy!

Contact me