Like a monkey with a typewriter, I occasionally make sense. This website serves as proof of that.
Worked on signal processing for speech recognition, deep learning for language understanding and designing and building a backend system to integrate various TensorFlow models with data collection pipelines.
TA (Teaching Assistant) for Stanford’s introductory Computer Science 2-course sequence. Teach a section of 10-12 students, grade homework and exams, hold office hours and interactive grading sessions for students. Courses are in Java and C++. Have given multiple guest lectures and written new assignments for the class, alongside autograders for these assignments. Also helping to train new TAs.
Worked on the HabitLab Google Chrome Extension, which intelligently offers interventions to increase one’s productivity on the web.
Assisted with two psychophysics experiments in the Brain & Consciousness Lab. Designed, implemented and tested both experiments (using python and the psychopy package), and ran one of the experiments on test subjects, followed by subsequent data analysis. Both experiments are on my github.
Part of a team of summer students & engineers helping to build and test resistive plate chambers (RPCs), a type of particle detector in the Compact Muon Solenoid (CMS) experiment, a part of the Large Hadron Collider (LHC)..
Final Project for Stanford's CS221: Artificial Intelligence Techniques and Principles. I used various Artificial Intelligence Techniques on Movie Scripts to identify protagonists and antagonists, find factions of characters, and cluster scripts based on their archetype. View the code here or read the paper here.
Final Project for Stanford's CS229: Introduction to Machine Learning. I used various Machine Learning Algorithms to predict how long students would need to wait for help at office hours and subsequently, how long it would take a TA to help them. View the code here or read the paper here.
A suite of tools to allow programming exams to be taken on a computer. Includes frontend application for students to take exams at a specified time, backend infrastrucure for automated exam creation and submission, and a variety of tools (including autograding) to expedite exam grading. The codebase is currently private for security reasons, but will likely eventually be opensourced.
Final Project for Stanford's CS 107: Computer Organization and Systems. Implements a dynamic memory allocator. Code is private due to Stanford's Honor Code.