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Welcome to my homepage! I'm Shardul Chiplunkar (shardulc), an MIT '22 undergrad from Pune, India, but also from the Bay Area, California.

My academic interests are somewhere in the neighborhood of math, computer science, linguistics, and cognitive science, somewhere that I don't yet have a good word for! My favorite description so far is that I want to study how intelligence arises and functions, whether it be physically in a human brain, virtually in an artificial intelligence, or formally in a mathematical system. In reality this has to somehow manifest in the form of coursework, about which I've written a little under the 'coursework' tab.

Apart from that, I enjoy Hindustani classical music, typesetting with LaTeX, teaching, thoughtful discussions, playing table tennis, science fiction, and spinning fire. I'm usually busy with one of the following variety of things (the 'activities' tab has more):

Finally, the 'links' tab is a list of pages I find interesting on the Internet. On the other hand, in the unlikely event that you find me interesting, you can email me at shardulc AT mit DOT edu, or ping me @shardulc on Telegram. (I don't use Facebook or Messenger anymore!)

A list of the subjects I've taken at MIT, annotated with my thoughts about them (click to view).

Spring 2020 (expected)

18.702 Algebra II
(not completed yet)
21M.710 Script Analysis
(not completed yet)
6.006 Introduction to Algorithms
(not completed yet)
6.009 Fundamentals of Programming
(not completed yet)
24.904 Language Acquisition
(not completed yet)

Fall 2019

18.701 Algebra I
I enjoyed this subject and it was more challenging than I thought it would be. Prof. Artin has helpful insights in class to accompany his 'textbook' of notes—while I hear that lectures used to be better in the past, I still gained a lot from going to them. If you are considering this course, please note that if you haven't seen proof-based math before or taken a math course that involves significant problem solving beyong formula plug-and-chug, this class will be very difficult. This fact is in unfortunate contrast to the fact that the class is effectively an entry point for most pure math majors.
18.404 Theory of Computation
This is a great class! Prof. Sipser is a very good lecturer and the class is generally well-structured. The problem sets have a good range of difficulty. Honestly this was probably the most well-organized and well-taught class I've ever taken and I can only think of minor negatives. 10/10 would recommend.
9.66 Computational Cognitive Science
This subject started out very exciting, as Prof. Tenenbaum introduced the fundamental concepts of his field—probabilistic programming and Bayesian inference—and demonstrates their successes over current statistical approaches to modeling cognitive functions in interesting and engaging demos. Once the groundwork was laid, however, the middle of the semester was just an extensive literature review of various applications of the techniques explained earlier in the semester. This is good as a general overview (and for inspiration for the final project) but can be repetitive. Personally for me the class picked back up in excitement at the end when Porf. Tenenbaum talked about program induction and the broader context of learning systems. A bonus to this class is that the professor's CoCoSci lab is very open to UROPs in fields branching off what's covered in class.
24.215 Topics in Philosophy of Science
An interesting subject, presenting its content in ways/frames that I hadn't considered before, albeit a tad slow-paced. There are four units: thermodynamics (focusing on entropy, the second law, and various associated philosophical considerations), causation, evolution (a discussion of what the theory of evolution actually means, evolutionary mechanisms, whether biological artifacts have a "purpose", etc.), and a general conclusion talking about what Science aims to achieve and can actually achieve. Informative on the whole. One major negative is that Prof. Skow completely avoided discussing Bayes' Theorem and its applications to what we were looking at in class, because it was "too much math" (very relevant math though!), but it turned out okay.

Spring 2019

2.110/6.050 Information, Entropy, and Computation
The facts about this class are simultaneously positive and negative, much as the qubits that are Prof. Lloyd's lifeblood are a superposition of on and off. The class covers a wide range of related topics in information theory, coding theory, thermodynamics, quantum computation, etc. but assumes that you have an inkling of the topic already (you've been in the same room as someone talking about it, for example). Also, Prof. Lloyd spends a significant amount of class time in stories (mostly related to the subject matter, often personal). These two things together mean that the class conveys a lot of culture about the topics, i.e. an attitude towards thinking about them, along with the actual content.
18.783 Elliptic Curves
I took this class without any previous classes in algebra or number theory and oh boy, was that a struggle. Don't do that unless you're looking for a struggle (which I'll admit I was). It was a fun time learning to swim in the deep end of the pool for me, a Sahara desert tribesman, and the content is actually very interesting.
9.13 The Human Brain
  • The weekly readings are recent cognitive science publications that are pretty interesting and relevant to the week's topics. The reading response assignments helped me feel more confident about reading scientific literature in general.
  • The class presents a nice range of content, and it's all a functional-level study of the brain rather than anatomy or psychology, both of which are interesting but not what I'm interested in. (To be clear, by 'psychology' I mean the behavioral study of humans that attempts to build models of our social and personal states of being, whereas functional-level cognitive science attempts to explain how exactly the brain performs the computations that let us see, hear, move, reason, etc.)
  • The class gives an overview of physical methods of data collection and experimentation, like fMRI and intracranial stimulation, and also an overview of what sorts of statistical analyses produce the results presented in class. I liked the focus on experimental design that encouraged critical thinking about competing hypotheses for the same data—I think this is a nice scientific way of teaching in general and I suspect that these skills are more broadly applicable.
  • Prof. Kanwisher was often both a little repetitive and unable to actually go through all the content planned for a lecture. It wasn't too bad though.
  • There is nothing about memory or conscious thought (possibly because we don't understand it too well yet?) and little about language, which are topics I'm now even more interested in. I believe emotions are outside the scope of the class anyway.
21M.080 Introduction to Music Technology
This class was a lot of fun! Lectures were for the most part informative and engaging, and the assignments and the final project were enjoyable and really helped me understand hands-on the stuff we talked about in class. I was a little annoyed that I had to run a Windows VM for a lot of classwork and buy more than $100 of software+hardware but I think it was worth it. In my opinion, the topics of this class—acoustics, audio production, electronic synthesis, etc.—fit very well into the "essential MIT attitude" of connecting practical engineering to the humanities.
8.022 Physics II
Did a much better job of explaining div, curl, grad than 18.022 because of the physical context of electric and magnetic fields. This is my first class on P/NR that I actually treated like P/NR, so I don't think I'm in a position to say much else.

Fall 2018

18.022 Calculus
Not much to say, except that although the math was at a good level of rigor, the explanation of div, curl, grad from a 'theoretical point of view' was unsatisfactory. 8.022 did it much better! Prof. Borodin did an intriguing optional introduction to differential forms in the last week of class.
18.03 Differential Equations
  • The last third of the class had a good amount of new (for me) material about linear algebra, enough that I felt confident learning more on my own.
  • I think I learned a lot of core concepts from this class such as what a vectorspace is (yay Fourier series!), how to reason about the general behavior of a dynamic system, and the relationship between differential equations, recurrence relations, and their solutions.
  • Lectures were slow, especially in the first half of the class, with maybe 15 minutes of valuable content in 50 minutes of lecture.
7.012 Introductory Biology
I'm very glad I took this class! I'd never liked (or understood the point of) biology in high school, and I took this just because it was a requirement and I might as well be done with it, but now I really appreciate how interesting biology is and am not averse to taking more course 7 subjects in the future (maybe 6.049/7.33 Evolutionary Biology?). Prof. Lander is one of the best lecturers I've even seen: he's compelling and approachable and clearly extremely good at what he does. 10/10 would strongly recommend.
24.900 Introduction to Linguistics
  • The class covered the basics of phonetics and phonology pretty well, as expected given that it's Prof. Albright's area of research.
  • The main writing assignment of the class (it's a CI-H) was fun. It involved interviewing a native speaker of a language you don't know and writing an essay describing the important structural features as discovered by you.
  • The syntax formalism of choice was the 'X-bar schema' which I thought was taught decently but without much justification for why it represents linguistic structure better than anything else. In my opinion, it was heavily English-centric, and I wasn't satisfied with how we attempted to apply the same formalism as a 'universal' to other languages; again in the morphology section, the examples (necessarily from languages other than English) were sparse, and as a speaker of a morphologically rich language (Marathi) many claims did not seem to me to apply generally.
  • I thought the entire class was slow and lectures were often repetitive. This may have been because I came in with some previous linguistics experience from the IOL.

The MIT Educational Studies Program (ESP) is a student group that aims to spread the joy of learning and teaching by running a variety of educational programs for middle- and high-school students throughout the year, drawing teachers mostly from the MIT community. ESP values freedom in what students choose to learn and teachers choose to teach; ESP also values opportunities for the growth of its programs and its members (admins) through experimentation and leadership in a very healthy work environment. You're welcome to talk to me if you're interested in teaching a class or helping run a program!

The MIT-Wellesley Toons is MIT's (and Wellesley's) only cross-campus a cappella group ("only, and therefore the best", as the old lame joke goes). The Toons aren't competitive or solely performance-focused, but rather choose to have some wholesome fun with kind of obscure and experimental indie music; I sing tenor with this wonderful group of people. Come audition at the start of the next semester!

The Panini Linguistics Olympiad (PLO) is the Indian national Olympiad in linguistics that feeds into the International Linguistics Olympiad (IOL), one of the 12 international science Olympiads for talented school-aged students (its better-known siblings include the IMO and IOI). The main component of a linguistics Olympiad is puzzles based on linguistic phenomena of the world's languages and on how humans and machines work with the many forms of language. After being on Team India at the IOL for a couple years, I now help with making and testing problems for PLO and training the Indian team.

My current UROP with the Programming Languages and Verification lab (PLV) in CSAIL, led by Dr. Adam Chlipala, involves using formal software verification and synthesis tools to build a useable prototype of a network firewall. At a high level, I use the automated theorem-proving assistant Coq and a software library called Fiat developed by the PLV group to write a 'mathematical' specification of a computer program, and then to incrementally refine it into something that a computer can actually execute. This is very much a work in progress.

The MIT Spinning Arts Club is a student group that is perhaps best known for the fire shows it organizes during REX and CPW. Spinning Arts also organizes weekly fire and non-fire spinning practices and has occasional workshops to make your own spinning props.

aca-sound is a student group that runs the sound equipment for most of MIT's numerous a cappella concerts. aca-sound owns and manages its own equipment and everything at a concert from physical setup to live audio mixing is done by students, who are often also members of a cappella groups.