• Sensitivity of ℓ₁ minimization to parameter choice

    Details PDF

  • Parameter instability regimes in sparse proximal denoising programs

    Details PDF

  • Enrichment map profiling of the cancer invasion front suggests regulation of colorectal cancer progression by the bone morphogenetic protein antagonist, gremlin-1

    Details PDF

Recent Posts

More Posts

Install python3 using Homebrew.


Day 2 — Coding in Python Welcome to Day 3 of the Math section of Future Science Leaders! Today, you will get to explore a series of activities that will have you coding and problem solving in Python. If you don’t have Python already installed your laptop, no worries! Simply go to There should be no need to make an account. We’ll be walking around to make sure you’re able to get up and running.


A brief summary and some incomplete reflections from the 2018 BC Data Science workshop.


A kind of repository for some links to blogs and resources that I’ve found useful over the years.


A post describing the code for a matrix completion tutorial I wrote for the 2017 BC Data Science workshop



Host a website on GitHub with Hugo

A tutorial on how to create, customize and host a website using Hugo and GitHub Pages.

Neural Networks in Keras

A mini-project I designed for the 2017 BC Data Science Workshop

Matrix Completion

A matrix completion mini-project that I designed for the 2017 BC Data Science Workshop

Video Compression Analysis

My take on the video compression project from the bcdata workshop

Gradient Descent

Gradient descent concepts from Mark Schmidt’s 540 course at UBC (with code ported to Python).

An example machine learning package featuring different gradient descent methods.

Slides from the UBC MGC seminar series

A Proof of Calderón's Formula

A proof of Calderón’s convolutional reproducing formula for functions in L^2 with the Haar measure.

MSc project submission

On Multiscale Analysis and PDE Methods on Graphs in Image Processing

Parameter Stability in CS

My 5 minute presentation for the 2017 UBC IAM retreat.


I was a teaching assistant for the 2017 and 2018 UBC MDS programs. In 2017: Descriptive Statistics and Probability, Data Wrangling, Supervised Learning I, Feature and Model Selection, Statistical Inference and Computation II and Experimentation and Causal Inference. In 2018: Communication & Argumentation, Data Wrangling, Databases and Data Retrieval, Unsupervised Learning, Spatial & Temporal Models, Web and Cloud Computing.

I was co-organizer and workshop TA for the 2017 BC Data Science workshop and 2018 BC Data Science Workshop.

Past TA duties include: ODEs, Vector Calculus, Calculus I and Mathematics for Biology.