Shubhra Mishra

About Shubhra Mishra

I\'m a senior studying Computer Science and Math at Stanford University. I take pride in my ability to connect with others, problem-solve, think quickly and make decisions (especially under pressure), learn new things, and explain difficult concepts to students/peers. Courses (both in and out of school) I\'ve taken include Operating Systems Principles, Design and Analysis of Algorithms, Logic Programming, Number Theory for Cryptography, Math for Quantitative Finance, Intro. to Neural Networks, and Quantum Computing. Through these courses and some self-directed projects, skills I\'ve gained includePython, C/C++, ML Algorithms, TensorFlow, Keras, Natural Language Processing, Computer Vision, LangChain, LLM Application Development, Swift, Figma, iOS Dev, React, JavaScript, Docker, Deep Learning, LaTeX, MATLAB, Mathematica. I\'m also involved with Graph Theory Research regarding Harris Graphs with Dr. Doug Shaw. Ask me about it (or my favorite unsolved problem in Graph Theory)! I love talking about math. I\'ve shown a strong track record of leadership across the following activities: 1. Asha for Education, a club I lead, where Stanford students come together to organize the Holi fundraiser. This year, we raised over 2 days for educational non profits in India. Stanford Flipside, a satire publication where I\'m VP and write about world- and campus-related events. South Asian Society, a club that puts on programming across campus to promote South Asian community and celebrate out culture. Tutoring. I\'ve had a passion for teaching for as long as I can remember. I tutor students from all across the K-12 range — some virtually, and others in person who live close to campus. Delta Delta Delta, where I served as President for a chapter with 150+ members.

Experience

1. Research Assistant, Stanford Computation and Cognition Lab (Cocolab)

   Stanford Artificial Intelligence Laboratory Sail

   Sep 2023 — Present

   Developing a dataset generation process that maps math problems to their corresponding Common Core standards. The synthetic nature of the dataset serves the dual purpose of preventing contamination from LLMs’ training sets and facilitating education benchmark-backed evaluations.* Training a language model to measure the minimal size requirement for a model to accurately solve computational problems

Education

• Walnut Hills High School

  High School Diploma, N/A

  2017 — 2021

• KTH Royal Institute of Technology

  Doctor of Philosophy - PhD, Computer Science

• Stanford University

  Master's of Science, Computer Science

• Stanford University

  Bachelor's of Science, Computer Science and Mathematics