I am Rushil Shah, a senior at MIT passionate about the intersection of physics, computer science, and mathematics.
I'm pursuing my bachelor's degree in physics and computer science as well as a master's degree in computer science.
My primary interest is in quantum computation which is the field of my current research. Currently, I am
working on simulating readout for superconducting qubits to achieve higher fidelity while maintaining fast readout.
For a more complete list of my research and projects, please refer to my CV.
Beyond academics, I also enjoy playing squash and other racket sports, reading fantasy novels, and speedrunning minecraft.
In this personal website, I have shared a few of my project, paper, and handouts which I have developed over the past few years.
Papers
A collection of academic papers and talks from my coursework and research at MIT.
2025 • IEEE High Performance Extreme Computing Conference • Rushil Shah, Emmanuel Lujan, Rabab Alomairy, Alan Edelman
We introduce a large language model (LLM)-driven
approach for generating dynamic algorithmic dispatch heuristics
in high-performance linear algebra.
We introduce a large language model (LLM)-driven
approach for generating dynamic algorithmic dispatch heuristics
in high-performance linear algebra. By combining prompt engineering with LLaMA 3 and a curated performance database,
the model learns to synthesize selection heuristics that exploit
structural patterns to identify fast algorithmic choices. A case
study on LU factorization demonstrates the model's ability to
replicate expert-designed strategies. This work, developed as part
of the DARPA-MIT SmartSolve project, highlights the promise
of LLMs for algorithmic discovery and the development of more
adaptive, fast linear algebra software.
The DARPA-MIT SmartSolve project tackles the challenge of dynamically selecting optimal algorithms and architectures through an automated discovery framework.
As part of this effort, we present advances on optimizing algorithm and data structure choices tailored to linear algebra.
The DARPA-MIT SmartSolve project tackles the challenge of dynamically selecting optimal algorithms and architectures through an automated discovery framework.
As part of this effort, we present advances on optimizing algorithm and data structure choices tailored to linear algebra.
Contributions include automated benchmarking across diverse matrix patterns, database-driven selection via Pareto analysis, and exploring large language models for automatic heuristic generation.
Quantum optimization algorithms attempt to prove quantum supremacy over classical computation. Many of these algorithms solve certain instances of a general class of problems called constraint satisfication problems (CSPs).
Quantum optimization algorithms attempt to prove quantum supremacy over classical computation. Many of these algorithms solve certain instances of a general class of problems called constraint satisfication problems (CSPs).
These problems are fundamental, so demonstrating an exponential speedup is necessary for the viability of quantum computation. Recently, a paper proposed an algorithm called DQI which prepares a state that generates a polynomial of a CSP objective function.
They provide an application to the max-XORSAT problem where they notice speedups in special cases. In this paper, we introduce the shortest codeword problem and demonstrate an equality with the max-XORSAT problem. We also take a look at some key features of the DQI algorithm which provide its functionality, specifically the usage of elementary symmetric polynomials.
Using these features, we apply the DQI algorithm to the spiked shortest codeword problem and analyze the results with a simulated annealing approach. We notice that DQI performs slightly worse than the classical simulated annealing algorithm on 10 random 6 by 12 generator matrices, likely a result of a smaller polynomial degree and suboptimal coefficient selection.
Finally, we take a look at the limits of the DQI algorithm and how it can be applied to similar problems.
We introduce the notion of a stabilizer code, provide an example of using it for quantum error correction, and understand why it is a promising area of research for quantum computation.
We introduce the notion of a stabilizer code, provide an example of using it for quantum error correction, and understand why it is a promising area of research for quantum computation. A short review paper format for MIT's 8.06, Quantum Physics III, class.
Projects
AWS Braket MCM Simulator
Julia-based and Python-based simulators for running mid-circuit measurement
circuits on AWS Braket.
Qiskit-Stim Converter
A Stim backend in Qiskit to perform fast stabilizer circuit simulation.
SmartSolve
Algorithmic heuristic generation using Julia and LLMs.
CurbToCar
Voice and haptics car navigator app for visually impaired users.
Physics Genie
Interactive physics visualizations and problem-solving tools.
Handouts
Over the past few years from tutoring, I have written a variety of STEM handouts including school curriculum and olympiad
preparation. I have decided to release some of the handouts that I have written and will release more
as I polish them.
Summer is here again! It's been a while since I have updated the website, but since I have a few weeks
without anything critical to do, I decided to make a few changes and include some new developments from the past 3 years.
Ideally, I will try to get out some more handouts too, and hopefully I will be more consistent with updating this in the future.
6/5/2024
Summer time is finally here! Few notes about the website: to-do list (first draft) has been added, physics simulations
will come soon, and there have been some more dark mode bug fixes. I am hoping to add some of my handouts
later as well as make the items in the to-do list movable and saveable after existing the site. After that,
I will probably start adding the physics simulations. To anyone reading, have a great summer!
5/5/2024
Just a quick update regarding some features: dark mode feature has been added and issues regarding
aspect ratios should be fixed.
5/2/2024
It is closing in on the end of my freshman year of college. It has been quite the experience to say
the least. The mix between academics, social life, and personal life has been something I have never
experience before, and I am excited to spend the next 3 years at MIT. I decided to make this website
to start my adventure into computer science. I have always been interested in physics, but not so much
in computer science. However, after reaching MIT, it's come to me the necessity of computer science in
everything, especially physics. As I work on new projects, I will put them on this website to highlight
all of the cool things that computer science and physics can do. By the end of the semester, I want to
make the website look cleaner, add a dark mode feature, and add some of the projects I have already done.
