Brahm Capoor

Stanford Symbolic Systems '19 · brahm@stanford.edu

Like a monkey with a typewriter, I occasionally make sense. This website serves as proof of that.

Experience

Natural Language Processing Intern

CloudMinds Technologies

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.

June 2017 - September 2017

CS106 Section Leader

Department of Computer Science, Stanford University

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.

Jan 2017 - Present

Research Intern

Stanford Unviersity Human-Computer Interaction Group

Worked on the HabitLab Google Chrome Extension, which intelligently offers interventions to increase one’s productivity on the web.

September 2016 - December 2016

Research Intern

Center for Cognitive Neuroscience, Duke-NUS Medical School, Singapore

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.

June 2016 - August 2016

High School Intern

European Center for Nuclear Research (CERN)

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)..

June 2014 - July 2014

Projects

Heroes and Villains: What A.I. Can Tell Us About Movies

Python

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.

November 2017

L.A.I.R: Leveraging A.I. For Requests

Python

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.

November 2017

BlueBook

Java, Javascript, React + Redux, Python

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.

April 2017 - Present

Heap Allocator

C

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.

November 2016

Mercury

Python

A twitter bot that chooses a random emotion every day and generates tweets based on that mood using Markov Chaining on a corpus of around 2000 quotes per emotion, webscraped from GoodReads. View the code here or the (now inactive) bot here.

May 2016