Siddharth Sharma

Hi! 👋 I am a second year student and engineer studying CS and Math at Stanford.

I enjoy building things and making products that users love. This page is more of an extended "about" page.

Feel free to reach out at sidshr 'at' 😀

A bit about me

My coursework spans the gamut from nuclear physics with Prof. Robert Laughlin to complexity theory with Prof. Paul Milgrom, both being Nobel Prize winners in their respective fields. In high school, I was lucky enough to work with Professor Emeritus Bernard Widrow (Stanford EE), Dr. Daniel Rubin (Stanford Biomedical Data Science). I've also led a team to author a 280 page textbook on AI and Machine Learning. To enable more ML education opportunities, I founded StartOnAI, an educational platform which provides introductory content for topics in machine learning. During summer 2022, I led the engineering and deployment of a new transformer model for NER at Abacus.AI, a series C startup working on ML platforms and deep learning at scale.

What I'm up to on campus

I help teach CS 106A and CS 106B, Stanford's largest introductory CS courses as part of the CS 198 program at Stanford.

On campus, I'm a reading group co-director for Stanford ACM and startup development co-director at Stanford BASES. I'm also also fortunate to serve as Class President for Stanford's class of 2025.


I've taken classes in areas like Simplicity and Complexity Theory, Computer Vision with Deep Learning, Large Language Models, Computer Systems, OS, etc. Cryptography, RL, and security are next on the list. 👀



Here's an article I recently penned following Federer's retirement. One of my favorite questions is if you could have dinner with any 6 people in the world who would it be?. My answer to that question would be Roger Federer, Michael Schumacher, Peter Thiel, Barack Obama, Michael Moritz, and Jamie Dimon. Some of my favorite movies: Dead Poets Society, The Dark Knight Trilogy, Inception, Midnight in Paris, the Social Network, and Life is Beautiful. I really enjoy listening to bits and pieces of wisdom from Stanford's GSB View from the Top series. Some good books: Genius Makers (Metz), Outliers (Gladwell), Zero to One (Thiel), The Inevitable (Kelly), The Beginning of Infinity (Deutsch), The Inner Game of Tennis (Gallwey).


  • February 2022, Goldman Sachs Walter F. Blaine Scholarship Winner
  • January 2021, Regeneron Science Talent Search Scholar
  • November 2020, Presented at the 2020 IEEE International Conference on Quantum Computing and Engineering
  • October 2020, Presented at IEEE MIT Undergraduate Research and Technology Conference
  • October 2020, Presenter at Pioneering NeuroHealth Conference (Stanford Wu Tsai Institutes)
  • October 2020, Speaker at UMich AI Symposium (AI + Health)
  • September 2020, Presented at the 7th IEEE International Conference on Data Science and Advanced Analytics
  • November 2019, Invited Presenter at Stanford Data Science Initiative (SDSI) Annual Health Meeting
  • May 2019, Invited Presenter at Stanford Big Data in Precision Medicine Conference