About

I am a PhD candidate in Applied Mathematics at the University of British Columbia being advised by Özgür Yilmaz and Yaniv Plan. My research is in the area of compressed sensing, convex optimization and machine learning — comprising aspects of high-dimensional probability, applications of random matrix theory, convex analysis and geometric functional analysis.

During October 2016 – February 2017 I completed an internship with Awake Labs, where I worked as a data scientist developing online algorithms for performing learning tasks on structured high-dimensional physiological data.

I completed my MSc Mathematics in August 2014 at the University of Toronto. My supervisor was Dr. Adrian Nachman, under whom I researched fast computational methods in image processing with applications in medical imaging. Before that, I completed my BSc in Mathematics & Statistics at McMaster University in Hamilton, ON.

• Parameter instability regimes in sparse proximal denoising programs

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• Sensitivity of ℓ₁ minimization to parameter choice

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

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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.

• aberk@math.ubc.ca
• LSK 309, University of British Columbia, Vancouver BC