Welcome to my site & blog! I'm a Computer Science & Statistics student at the University of Waterloo interested in machine learning and programming languages.

Previously, I did deep learning research on collaborative self-driving at Uber ATG, helped improve the neural network optimization algorithm library K-FAC at Google Brain, accelerated BERT inference at NVIDIA TensorRT, and developed data-driven models to identify fraud at John Hancock Financial. I've also worked as a Research Assistant for Prof. Gautam Kamath in differential privacy, Prof. Lin Tan in deep learning-driven software analysis, and Prof. Pascal Poupart on neural network parameter learning.

Follow me on twitter, I mostly tweet about technical topics! Checkout my resources page for links to cool blog posts, talks, and other gems. Feel free to reach out through email: nicholas.vadivelu [at] gmail [dot] com or book some time with me through calendly--I love to chat!


Papers


Talks


Blog Posts

Jan 2021

Interactive Data Visualization with Altair [preview]

Jan 2021

Comparing Array Partition Algorithms [preview]

Sep 2020

How to get your first Undergraduate Research Assistant Role [preview]

Aug 2020

First Steps for Learning Data Science [preview]

Nov 2019

Introduction to Neural Networks in TensorFlow 2 [preview]

Sep 2019

Introduction to Random Forests [preview]

Sep 2019

Introduction to Data Cleaning with Pandas [preview]

Sep 2018

Communicating Data Science to Professionals [preview]

Sep 2018

Lessons Learned from Analyzing Competitive Pokemon [preview]